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Factors Associated with Radiation Toxicity and Survival in Patients with Presumed Early-Stage Non-Small Cell Lung Cancer Receiving Empiric Stereotactic Ablative Radiotherapy
Stereotactic ablative radiotherapy (SABR) has become the standard of care for inoperable early-stage non-small cell lung cancer (NSCLC). Many patients are unable to undergo a biopsy safely because of poor pulmonary function or underlying emphysema and are then empirically treated with radiotherapy if they meet criteria. In these patients, local control can be achieved with SABR with minimal toxicity.1 Considering that median overall survival (OS) among patients with untreated stage I NSCLC has been reported to be as low as 9 months, early treatment with SABR could lead to increased survival of 29 to 60 months.2-4
The RTOG 0236 trial showed a median OS of 48 months and the randomized phase III CHISEL trial showed a median OS of 60 months; however, these survival data were reported in patients who were able to safely undergo a biopsy and had confirmed NSCLC.4,5 For patients without a diagnosis confirmed by biopsy and who are treated with empiric SABR, patient factors that influence radiation toxicity and OS are not well defined.
It is not clear if empiric radiation benefits survival or if treatment causes decline in lung function, considering that underlying chronic lung disease precludes these patients from biopsy. The purpose of this study was to evaluate the factors associated with radiation toxicity with empiric SABR and to evaluate OS in this population without a biopsy-confirmed diagnosis.
Methods
This was a single center retrospective review of patients treated at the radiation oncology department at the Kansas City Veterans Affairs Medical Center from August 2014 to February 2019. Data were collected on 69 patients with pulmonary nodules identified by chest computed tomography (CT) and/or positron emission tomography (PET)-CT that were highly suspicious for primary NSCLC.
These patients were presented at a multidisciplinary meeting that involved pulmonologists, oncologists, radiation oncologists, and thoracic surgeons. Patients were deemed to be poor candidates for biopsy because of severe underlying emphysema, which would put them at high risk for pneumothorax with a percutaneous needle biopsy, or were unable to tolerate general anesthesia for navigational bronchoscopy or surgical biopsy because of poor lung function. These patients were diagnosed with presumed stage I NSCLC using the criteria: minimum of 2 sequential CT scans with enlarging nodule; absence of metastases on PET-CT; the single nodule had to be fluorodeoxyglucose avid with a minimum standardized uptake value of 2.5, and absence of clinical history or physical examination consistent with small cell lung cancer or infection.
After a consensus was reached that patients met these criteria, individuals were referred for empiric SABR. Follow-up visits were at 1 month, 3 months, and every 6 months. Variables analyzed included: patient demographics, pre- and posttreatment pulmonary function tests (PFT) when available, pre-treatment oxygen use, tumor size and location (peripheral, central, or ultra-central), radiation doses, and grade of toxicity as defined by Human and Health Services Common Terminology Criteria for Adverse Events version 5.0 (dyspnea and cough both counted as pulmonary toxicity): acute ≤ 90 days and late > 90 days (Table 1).
SPSS versions 24 and 26 were used for statistical analysis. Median and range were obtained for continuous variables with a normal distribution. Kaplan-Meier log-rank testing was used to analyze OS. χ2 and Mann-Whitney U tests were used to analyze association between independent variables and OS. Analysis of significant findings were repeated with operable patients excluded for further analysis.
Results
The median follow-up was 18 months (range, 1 to 54). The median age was 71 years (range, 59 to 95) (Table 2). Most patients (97.1%) were male. The majority of patients (79.4%) had a 0 or 1 for the Eastern Cooperative Oncology group performance status, indicating fully active or restricted in physically strenuous activity but ambulatory and able to perform light work. All patients were either current or former smokers with an average pack-year history of 69.4. Only 11.6% of patients had operable disease, but received empiric SABR because they declined surgery. Four patients did not have pretreatment spirometry available and 37 did not have pretreatment diffusing capacity for carbon monoxide (DLCO) data.
Most patients had a pretreatment forced expiratory volume during the first seconds (FEV1) value and DLCO < 60% of predicted (60% and 84% of the patients, respectively). The median tumor diameter was 2 cm. Of the 68.2% of patients who did not have chronic hypoxemic respiratory failure before SABR, 16% developed a new requirement for supplemental oxygen. Sixty-two tumors (89.9%) were peripheral. There were 4 local recurrences (5.7%), 10 regional (different lobe and nodal) failures (14.3%), and 15 distant metastases (21.4%).
Nineteen of 67 patients (26.3%) had acute toxicity of which 9 had acute grade ≥ 2 toxicity; information regarding toxicity was missing on 2 patients. Thirty-two of 65 (49.9%) patients had late toxicity of which 20 (30.8%) had late grade ≥ 2 toxicity. The main factor associated with development of acute toxicity was pretreatment oxygendependence (P = .047). This was not significant when comparing only inoperable patients. Twenty patients (29.9%) developed some type of acute toxicity; pulmonary toxicity was most common (22.4%) (Table 3). All patients with acute toxicity also developed late toxicity except for 1 who died before 3 months. Predominantly, the deaths in our sample were from causes other than the malignancy or treatment, such as sepsis, deconditioning after a fall, cardiovascular complications, etc. Acute toxicity of grade ≥ 2 was significantly associated with late toxicity (P < .001 for both) in both operable and inoperable patients (P < .001).
Development of any acute toxicity grade ≥ 2 was significantly associated with oxygendependence at baseline (P = .003), central location (P < .001), and new oxygen requirement (P = .02). Only central tumor location was found to be significant (P = .001) within the inoperable cohort. There were no significant differences in outcome based on pulmonary function testing (FEV1, forced vital capacity, or DLCO) or the analyzed PFT subgroups (FEV1 < 1.0 L, FEV1 < 1.5 L, FEV1 < 30%, and FEV1 < 35%).
At the time of data collection, 30 patients were deceased (43.5%). There was a statistically significant association between OS and operability (P = .03; Table 4, Figure 1). Decreased OS was significantly associated with acute toxicity (P = .001) and acute toxicity grade ≥ 2 (P = .005; Figures 2 and 3). For the inoperable patients, both acute toxicity (P < .001) and acute toxicity grade ≥ 2 (P = .026) remained significant.
Discussion
SABR is an effective treatment for inoperable early-stage NSCLC, however its therapeutic ratio in a more frail population who cannot withstand biopsy is not well established. Additionally, the prevalence of benign disease in patients with solitary pulmonary nodules can be between 9% and 21%.6 Haidar and colleagues looked at 55 patients who received empiric SABR and found a median OS of 30.2 months with an 8.7% risk of local failure, 13% risk of regional failure with 8.7% acute toxicity, and 13% chronic toxicity.7 Data from Harkenrider and colleagues (n = 34) revealed similar results with a 2-year OS of 85%, local control of 97.1%, and regional control of 80%. The authors noted no grade ≥ 3 acute toxicities and an incidence of grade ≥ 3 late toxicities of 8.8%.1 These findings are concordant with our study results, confirming the safety and efficacy of SABR. Furthermore, a National Cancer Database analysis of observation vs empiric SABR found an OS of 10.1 months and 29 months respectively, with a hazard ratio of 0.64 (P < .001).3 Additionally, Fischer-Valuck and colleagues (n = 88) compared biopsy confirmed vs unbiopsied patients treated with SABR and found no difference in the 3-year local progression-free survival (93.1% vs 94.1%), regional lymph node metastasis and distant metastases free survival (92.5% vs 87.4%), or OS (59.9% vs 58.9%).8 With a median OS of ≤ 1 year for untreated stage I NSCLC,these studies support treating patients with empiric SABR.4
Other researchers have sought parameters to identify patients for whom radiation therapy would be too toxic. Guckenberger and colleagues aimed to establish a lower limit of pretreatment PFT to exclude patients and found only a 7% incidence of grade ≥ 2 adverse effects and toxicity did not increase with lower pulmonary function.9 They concluded that SABR was safe even for patients with poor pulmonary function. Other institutions have confirmed such findings and have been unable to find a cut-off PFT to exclude patients from empiric SABR.10,11 An analysis from the RTOG 0236 trial also noted that poor baseline PFT could not predict pulmonary toxicity or survival. Additionally, the study demonstrated only minimal decreases in patients’ FEV1 (5.8%) and DLCO (6%) at 2 years.12
Our study sought to identify a cut-off on FEV1 or DLCO that could be associated with increased toxicity. We also evaluated the incidence of acute toxicities grade ≥ 2 by stratifying patients according to FEV1 into subgroups: FEV1 < 1.0 L, FEV1 < 1.5 L, FEV1 < 30% of predicted and FEV1 < 35% of predicted. However, similar to other studies, we did not find any value that was significantly associated with increased toxicity that could preclude empiric SABR. One possible reason is that no treatment is offered for patients with extremely poor lung function as deemed by clinical judgement, therefore data on these patients is unavailable. In contradiction to other studies, our study found that oxygen dependence before treatment was significantly associated with development of acute toxicities. The exact mechanism for this association is unknown and could not be elucidated by baseline PFT. One possible explanation is that SABR could lead to oxygen free radical generation. In addition, our study indicated that those who developed acute toxicities had worse OS.
Limitations
Our study is limited by caveats of a retrospective study and its small sample size, but is in line with the reported literature (ranging from 33 to 88 patients).1,7,8 Another limitation is that data on pretreatment DLCO was missing in 37 patients and the lack of statistical robustness in terms of the smaller inoperable cohort, which limits the analyses of these factors in regards to anticipated morbidity from SABR. Also, given this is data collected from the US Department of Veterans Affairs, only 3% of our sample was female.
Conclusions
Empiric SABR for patients with presumed early-stage NSCLC appears to be safe and might positively impact OS. Development of any acute toxicity grade ≥ 2 was significantly associated with dependence on supplemental oxygen before treatment, central tumor location, and development of new oxygen requirement. No association was found in patients with poor pulmonary function before treatment because we could not find a FEV1 or DLCO cutoff that could preclude patients from empiric SABR. Considering the poor survival of untreated early-stage NSCLC, coupled with the efficacy and safety of empiric SABR for those with presumed disease, definitive SABR should be offered selectively within this patient population.
Acknowledgments
Drs. Park, Whiting and Castillo contributed to data collection. Drs. Park, Govindan and Castillo contributed to the statistical analysis and writing the first draft and final manuscript. Drs. Park, Govindan, Huang, and Reddy contributed to the discussion section.
1. Harkenrider MM, Bertke MH, Dunlap NE. Stereotactic body radiation therapy for unbiopsied early-stage lung cancer: a multi-institutional analysis. Am J Clin Oncol. 2014;37(4):337-342. doi:10.1097/COC.0b013e318277d822
2. Raz DJ, Zell JA, Ou SH, Gandara DR, Anton-Culver H, Jablons DM. Natural history of stage I non-small cell lung cancer: implications for early detection. Chest. 2007;132(1):193-199. doi:10.1378/chest.06-3096
3. Nanda RH, Liu Y, Gillespie TW, et al. Stereotactic body radiation therapy versus no treatment for early stage non-small cell lung cancer in medically inoperable elderly patients: a National Cancer Data Base analysis. Cancer. 2015;121(23):4222-4230. doi:10.1002/cncr.29640
4. Ball D, Mai GT, Vinod S, et al. Stereotactic ablative radiotherapy versus standard radiotherapy in stage 1 non-small-cell lung cancer (TROG 09.02 CHISEL): a phase 3, open-label, randomised controlled trial. Lancet Oncol. 2019;20(4):494-503. doi:10.1016/S1470-2045(18)30896-9
5. Timmerman R, Paulus R, Galvin J, et al. Stereotactic body radiation therapy for inoperable early stage lung cancer. JAMA. 2010;303(11):1070-1076. doi:10.1001/jama.2010.261
6. Smith MA, Battafarano RJ, Meyers BF, Zoole JB, Cooper JD, Patterson GA. Prevalence of benign disease in patients undergoing resection for suspected lung cancer. Ann Thorac Surg. 2006;81(5):1824-1828. doi:10.1016/j.athoracsur.2005.11.010
7. Haidar YM, Rahn DA 3rd, Nath S, et al. Comparison of outcomes following stereotactic body radiotherapy for nonsmall cell lung cancer in patients with and without pathological confirmation. Ther Adv Respir Dis. 2014;8(1):3-12. doi:10.1177/1753465813512545
8. Fischer-Valuck BW, Boggs H, Katz S, Durci M, Acharya S, Rosen LR. Comparison of stereotactic body radiation therapy for biopsy-proven versus radiographically diagnosed early-stage non-small lung cancer: a single-institution experience. Tumori. 2015;101(3):287-293. doi:10.5301/tj.5000279
9. Guckenberger M, Kestin LL, Hope AJ, et al. Is there a lower limit of pretreatment pulmonary function for safe and effective stereotactic body radiotherapy for early-stage non-small cell lung cancer? J Thorac Oncol. 2012;7:542-551. doi:10.1097/JTO.0b013e31824165d7
10. Wang J, Cao J, Yuan S, et al. Poor baseline pulmonary function may not increase the risk of radiation-induced lung toxicity. Int J Radiat Oncol Biol Phys. 2013;85(3):798-804. doi:10.1016/j.ijrobp.2012.06.040
11. Henderson M, McGarry R, Yiannoutsos C, et al. Baseline pulmonary function as a predictor for survival and decline in pulmonary function over time in patients undergoing stereotactic body radiotherapy for the treatment of stage I non-small-cell lung cancer. Int J Radiat Oncol Biol Phys. 2008;72(2):404-409. doi:10.1016/j.ijrobp.2007.12.051
12. Stanic S, Paulus R, Timmerman RD, et al. No clinically significant changes in pulmonary function following stereotactic body radiation therapy for early- stage peripheral non-small cell lung cancer: an analysis of RTOG 0236. Int J Radiat Oncol Biol Phys. 2014;88(5):1092-1099. doi:10.1016/j.ijrobp.2013.12.050
Stereotactic ablative radiotherapy (SABR) has become the standard of care for inoperable early-stage non-small cell lung cancer (NSCLC). Many patients are unable to undergo a biopsy safely because of poor pulmonary function or underlying emphysema and are then empirically treated with radiotherapy if they meet criteria. In these patients, local control can be achieved with SABR with minimal toxicity.1 Considering that median overall survival (OS) among patients with untreated stage I NSCLC has been reported to be as low as 9 months, early treatment with SABR could lead to increased survival of 29 to 60 months.2-4
The RTOG 0236 trial showed a median OS of 48 months and the randomized phase III CHISEL trial showed a median OS of 60 months; however, these survival data were reported in patients who were able to safely undergo a biopsy and had confirmed NSCLC.4,5 For patients without a diagnosis confirmed by biopsy and who are treated with empiric SABR, patient factors that influence radiation toxicity and OS are not well defined.
It is not clear if empiric radiation benefits survival or if treatment causes decline in lung function, considering that underlying chronic lung disease precludes these patients from biopsy. The purpose of this study was to evaluate the factors associated with radiation toxicity with empiric SABR and to evaluate OS in this population without a biopsy-confirmed diagnosis.
Methods
This was a single center retrospective review of patients treated at the radiation oncology department at the Kansas City Veterans Affairs Medical Center from August 2014 to February 2019. Data were collected on 69 patients with pulmonary nodules identified by chest computed tomography (CT) and/or positron emission tomography (PET)-CT that were highly suspicious for primary NSCLC.
These patients were presented at a multidisciplinary meeting that involved pulmonologists, oncologists, radiation oncologists, and thoracic surgeons. Patients were deemed to be poor candidates for biopsy because of severe underlying emphysema, which would put them at high risk for pneumothorax with a percutaneous needle biopsy, or were unable to tolerate general anesthesia for navigational bronchoscopy or surgical biopsy because of poor lung function. These patients were diagnosed with presumed stage I NSCLC using the criteria: minimum of 2 sequential CT scans with enlarging nodule; absence of metastases on PET-CT; the single nodule had to be fluorodeoxyglucose avid with a minimum standardized uptake value of 2.5, and absence of clinical history or physical examination consistent with small cell lung cancer or infection.
After a consensus was reached that patients met these criteria, individuals were referred for empiric SABR. Follow-up visits were at 1 month, 3 months, and every 6 months. Variables analyzed included: patient demographics, pre- and posttreatment pulmonary function tests (PFT) when available, pre-treatment oxygen use, tumor size and location (peripheral, central, or ultra-central), radiation doses, and grade of toxicity as defined by Human and Health Services Common Terminology Criteria for Adverse Events version 5.0 (dyspnea and cough both counted as pulmonary toxicity): acute ≤ 90 days and late > 90 days (Table 1).
SPSS versions 24 and 26 were used for statistical analysis. Median and range were obtained for continuous variables with a normal distribution. Kaplan-Meier log-rank testing was used to analyze OS. χ2 and Mann-Whitney U tests were used to analyze association between independent variables and OS. Analysis of significant findings were repeated with operable patients excluded for further analysis.
Results
The median follow-up was 18 months (range, 1 to 54). The median age was 71 years (range, 59 to 95) (Table 2). Most patients (97.1%) were male. The majority of patients (79.4%) had a 0 or 1 for the Eastern Cooperative Oncology group performance status, indicating fully active or restricted in physically strenuous activity but ambulatory and able to perform light work. All patients were either current or former smokers with an average pack-year history of 69.4. Only 11.6% of patients had operable disease, but received empiric SABR because they declined surgery. Four patients did not have pretreatment spirometry available and 37 did not have pretreatment diffusing capacity for carbon monoxide (DLCO) data.
Most patients had a pretreatment forced expiratory volume during the first seconds (FEV1) value and DLCO < 60% of predicted (60% and 84% of the patients, respectively). The median tumor diameter was 2 cm. Of the 68.2% of patients who did not have chronic hypoxemic respiratory failure before SABR, 16% developed a new requirement for supplemental oxygen. Sixty-two tumors (89.9%) were peripheral. There were 4 local recurrences (5.7%), 10 regional (different lobe and nodal) failures (14.3%), and 15 distant metastases (21.4%).
Nineteen of 67 patients (26.3%) had acute toxicity of which 9 had acute grade ≥ 2 toxicity; information regarding toxicity was missing on 2 patients. Thirty-two of 65 (49.9%) patients had late toxicity of which 20 (30.8%) had late grade ≥ 2 toxicity. The main factor associated with development of acute toxicity was pretreatment oxygendependence (P = .047). This was not significant when comparing only inoperable patients. Twenty patients (29.9%) developed some type of acute toxicity; pulmonary toxicity was most common (22.4%) (Table 3). All patients with acute toxicity also developed late toxicity except for 1 who died before 3 months. Predominantly, the deaths in our sample were from causes other than the malignancy or treatment, such as sepsis, deconditioning after a fall, cardiovascular complications, etc. Acute toxicity of grade ≥ 2 was significantly associated with late toxicity (P < .001 for both) in both operable and inoperable patients (P < .001).
Development of any acute toxicity grade ≥ 2 was significantly associated with oxygendependence at baseline (P = .003), central location (P < .001), and new oxygen requirement (P = .02). Only central tumor location was found to be significant (P = .001) within the inoperable cohort. There were no significant differences in outcome based on pulmonary function testing (FEV1, forced vital capacity, or DLCO) or the analyzed PFT subgroups (FEV1 < 1.0 L, FEV1 < 1.5 L, FEV1 < 30%, and FEV1 < 35%).
At the time of data collection, 30 patients were deceased (43.5%). There was a statistically significant association between OS and operability (P = .03; Table 4, Figure 1). Decreased OS was significantly associated with acute toxicity (P = .001) and acute toxicity grade ≥ 2 (P = .005; Figures 2 and 3). For the inoperable patients, both acute toxicity (P < .001) and acute toxicity grade ≥ 2 (P = .026) remained significant.
Discussion
SABR is an effective treatment for inoperable early-stage NSCLC, however its therapeutic ratio in a more frail population who cannot withstand biopsy is not well established. Additionally, the prevalence of benign disease in patients with solitary pulmonary nodules can be between 9% and 21%.6 Haidar and colleagues looked at 55 patients who received empiric SABR and found a median OS of 30.2 months with an 8.7% risk of local failure, 13% risk of regional failure with 8.7% acute toxicity, and 13% chronic toxicity.7 Data from Harkenrider and colleagues (n = 34) revealed similar results with a 2-year OS of 85%, local control of 97.1%, and regional control of 80%. The authors noted no grade ≥ 3 acute toxicities and an incidence of grade ≥ 3 late toxicities of 8.8%.1 These findings are concordant with our study results, confirming the safety and efficacy of SABR. Furthermore, a National Cancer Database analysis of observation vs empiric SABR found an OS of 10.1 months and 29 months respectively, with a hazard ratio of 0.64 (P < .001).3 Additionally, Fischer-Valuck and colleagues (n = 88) compared biopsy confirmed vs unbiopsied patients treated with SABR and found no difference in the 3-year local progression-free survival (93.1% vs 94.1%), regional lymph node metastasis and distant metastases free survival (92.5% vs 87.4%), or OS (59.9% vs 58.9%).8 With a median OS of ≤ 1 year for untreated stage I NSCLC,these studies support treating patients with empiric SABR.4
Other researchers have sought parameters to identify patients for whom radiation therapy would be too toxic. Guckenberger and colleagues aimed to establish a lower limit of pretreatment PFT to exclude patients and found only a 7% incidence of grade ≥ 2 adverse effects and toxicity did not increase with lower pulmonary function.9 They concluded that SABR was safe even for patients with poor pulmonary function. Other institutions have confirmed such findings and have been unable to find a cut-off PFT to exclude patients from empiric SABR.10,11 An analysis from the RTOG 0236 trial also noted that poor baseline PFT could not predict pulmonary toxicity or survival. Additionally, the study demonstrated only minimal decreases in patients’ FEV1 (5.8%) and DLCO (6%) at 2 years.12
Our study sought to identify a cut-off on FEV1 or DLCO that could be associated with increased toxicity. We also evaluated the incidence of acute toxicities grade ≥ 2 by stratifying patients according to FEV1 into subgroups: FEV1 < 1.0 L, FEV1 < 1.5 L, FEV1 < 30% of predicted and FEV1 < 35% of predicted. However, similar to other studies, we did not find any value that was significantly associated with increased toxicity that could preclude empiric SABR. One possible reason is that no treatment is offered for patients with extremely poor lung function as deemed by clinical judgement, therefore data on these patients is unavailable. In contradiction to other studies, our study found that oxygen dependence before treatment was significantly associated with development of acute toxicities. The exact mechanism for this association is unknown and could not be elucidated by baseline PFT. One possible explanation is that SABR could lead to oxygen free radical generation. In addition, our study indicated that those who developed acute toxicities had worse OS.
Limitations
Our study is limited by caveats of a retrospective study and its small sample size, but is in line with the reported literature (ranging from 33 to 88 patients).1,7,8 Another limitation is that data on pretreatment DLCO was missing in 37 patients and the lack of statistical robustness in terms of the smaller inoperable cohort, which limits the analyses of these factors in regards to anticipated morbidity from SABR. Also, given this is data collected from the US Department of Veterans Affairs, only 3% of our sample was female.
Conclusions
Empiric SABR for patients with presumed early-stage NSCLC appears to be safe and might positively impact OS. Development of any acute toxicity grade ≥ 2 was significantly associated with dependence on supplemental oxygen before treatment, central tumor location, and development of new oxygen requirement. No association was found in patients with poor pulmonary function before treatment because we could not find a FEV1 or DLCO cutoff that could preclude patients from empiric SABR. Considering the poor survival of untreated early-stage NSCLC, coupled with the efficacy and safety of empiric SABR for those with presumed disease, definitive SABR should be offered selectively within this patient population.
Acknowledgments
Drs. Park, Whiting and Castillo contributed to data collection. Drs. Park, Govindan and Castillo contributed to the statistical analysis and writing the first draft and final manuscript. Drs. Park, Govindan, Huang, and Reddy contributed to the discussion section.
Stereotactic ablative radiotherapy (SABR) has become the standard of care for inoperable early-stage non-small cell lung cancer (NSCLC). Many patients are unable to undergo a biopsy safely because of poor pulmonary function or underlying emphysema and are then empirically treated with radiotherapy if they meet criteria. In these patients, local control can be achieved with SABR with minimal toxicity.1 Considering that median overall survival (OS) among patients with untreated stage I NSCLC has been reported to be as low as 9 months, early treatment with SABR could lead to increased survival of 29 to 60 months.2-4
The RTOG 0236 trial showed a median OS of 48 months and the randomized phase III CHISEL trial showed a median OS of 60 months; however, these survival data were reported in patients who were able to safely undergo a biopsy and had confirmed NSCLC.4,5 For patients without a diagnosis confirmed by biopsy and who are treated with empiric SABR, patient factors that influence radiation toxicity and OS are not well defined.
It is not clear if empiric radiation benefits survival or if treatment causes decline in lung function, considering that underlying chronic lung disease precludes these patients from biopsy. The purpose of this study was to evaluate the factors associated with radiation toxicity with empiric SABR and to evaluate OS in this population without a biopsy-confirmed diagnosis.
Methods
This was a single center retrospective review of patients treated at the radiation oncology department at the Kansas City Veterans Affairs Medical Center from August 2014 to February 2019. Data were collected on 69 patients with pulmonary nodules identified by chest computed tomography (CT) and/or positron emission tomography (PET)-CT that were highly suspicious for primary NSCLC.
These patients were presented at a multidisciplinary meeting that involved pulmonologists, oncologists, radiation oncologists, and thoracic surgeons. Patients were deemed to be poor candidates for biopsy because of severe underlying emphysema, which would put them at high risk for pneumothorax with a percutaneous needle biopsy, or were unable to tolerate general anesthesia for navigational bronchoscopy or surgical biopsy because of poor lung function. These patients were diagnosed with presumed stage I NSCLC using the criteria: minimum of 2 sequential CT scans with enlarging nodule; absence of metastases on PET-CT; the single nodule had to be fluorodeoxyglucose avid with a minimum standardized uptake value of 2.5, and absence of clinical history or physical examination consistent with small cell lung cancer or infection.
After a consensus was reached that patients met these criteria, individuals were referred for empiric SABR. Follow-up visits were at 1 month, 3 months, and every 6 months. Variables analyzed included: patient demographics, pre- and posttreatment pulmonary function tests (PFT) when available, pre-treatment oxygen use, tumor size and location (peripheral, central, or ultra-central), radiation doses, and grade of toxicity as defined by Human and Health Services Common Terminology Criteria for Adverse Events version 5.0 (dyspnea and cough both counted as pulmonary toxicity): acute ≤ 90 days and late > 90 days (Table 1).
SPSS versions 24 and 26 were used for statistical analysis. Median and range were obtained for continuous variables with a normal distribution. Kaplan-Meier log-rank testing was used to analyze OS. χ2 and Mann-Whitney U tests were used to analyze association between independent variables and OS. Analysis of significant findings were repeated with operable patients excluded for further analysis.
Results
The median follow-up was 18 months (range, 1 to 54). The median age was 71 years (range, 59 to 95) (Table 2). Most patients (97.1%) were male. The majority of patients (79.4%) had a 0 or 1 for the Eastern Cooperative Oncology group performance status, indicating fully active or restricted in physically strenuous activity but ambulatory and able to perform light work. All patients were either current or former smokers with an average pack-year history of 69.4. Only 11.6% of patients had operable disease, but received empiric SABR because they declined surgery. Four patients did not have pretreatment spirometry available and 37 did not have pretreatment diffusing capacity for carbon monoxide (DLCO) data.
Most patients had a pretreatment forced expiratory volume during the first seconds (FEV1) value and DLCO < 60% of predicted (60% and 84% of the patients, respectively). The median tumor diameter was 2 cm. Of the 68.2% of patients who did not have chronic hypoxemic respiratory failure before SABR, 16% developed a new requirement for supplemental oxygen. Sixty-two tumors (89.9%) were peripheral. There were 4 local recurrences (5.7%), 10 regional (different lobe and nodal) failures (14.3%), and 15 distant metastases (21.4%).
Nineteen of 67 patients (26.3%) had acute toxicity of which 9 had acute grade ≥ 2 toxicity; information regarding toxicity was missing on 2 patients. Thirty-two of 65 (49.9%) patients had late toxicity of which 20 (30.8%) had late grade ≥ 2 toxicity. The main factor associated with development of acute toxicity was pretreatment oxygendependence (P = .047). This was not significant when comparing only inoperable patients. Twenty patients (29.9%) developed some type of acute toxicity; pulmonary toxicity was most common (22.4%) (Table 3). All patients with acute toxicity also developed late toxicity except for 1 who died before 3 months. Predominantly, the deaths in our sample were from causes other than the malignancy or treatment, such as sepsis, deconditioning after a fall, cardiovascular complications, etc. Acute toxicity of grade ≥ 2 was significantly associated with late toxicity (P < .001 for both) in both operable and inoperable patients (P < .001).
Development of any acute toxicity grade ≥ 2 was significantly associated with oxygendependence at baseline (P = .003), central location (P < .001), and new oxygen requirement (P = .02). Only central tumor location was found to be significant (P = .001) within the inoperable cohort. There were no significant differences in outcome based on pulmonary function testing (FEV1, forced vital capacity, or DLCO) or the analyzed PFT subgroups (FEV1 < 1.0 L, FEV1 < 1.5 L, FEV1 < 30%, and FEV1 < 35%).
At the time of data collection, 30 patients were deceased (43.5%). There was a statistically significant association between OS and operability (P = .03; Table 4, Figure 1). Decreased OS was significantly associated with acute toxicity (P = .001) and acute toxicity grade ≥ 2 (P = .005; Figures 2 and 3). For the inoperable patients, both acute toxicity (P < .001) and acute toxicity grade ≥ 2 (P = .026) remained significant.
Discussion
SABR is an effective treatment for inoperable early-stage NSCLC, however its therapeutic ratio in a more frail population who cannot withstand biopsy is not well established. Additionally, the prevalence of benign disease in patients with solitary pulmonary nodules can be between 9% and 21%.6 Haidar and colleagues looked at 55 patients who received empiric SABR and found a median OS of 30.2 months with an 8.7% risk of local failure, 13% risk of regional failure with 8.7% acute toxicity, and 13% chronic toxicity.7 Data from Harkenrider and colleagues (n = 34) revealed similar results with a 2-year OS of 85%, local control of 97.1%, and regional control of 80%. The authors noted no grade ≥ 3 acute toxicities and an incidence of grade ≥ 3 late toxicities of 8.8%.1 These findings are concordant with our study results, confirming the safety and efficacy of SABR. Furthermore, a National Cancer Database analysis of observation vs empiric SABR found an OS of 10.1 months and 29 months respectively, with a hazard ratio of 0.64 (P < .001).3 Additionally, Fischer-Valuck and colleagues (n = 88) compared biopsy confirmed vs unbiopsied patients treated with SABR and found no difference in the 3-year local progression-free survival (93.1% vs 94.1%), regional lymph node metastasis and distant metastases free survival (92.5% vs 87.4%), or OS (59.9% vs 58.9%).8 With a median OS of ≤ 1 year for untreated stage I NSCLC,these studies support treating patients with empiric SABR.4
Other researchers have sought parameters to identify patients for whom radiation therapy would be too toxic. Guckenberger and colleagues aimed to establish a lower limit of pretreatment PFT to exclude patients and found only a 7% incidence of grade ≥ 2 adverse effects and toxicity did not increase with lower pulmonary function.9 They concluded that SABR was safe even for patients with poor pulmonary function. Other institutions have confirmed such findings and have been unable to find a cut-off PFT to exclude patients from empiric SABR.10,11 An analysis from the RTOG 0236 trial also noted that poor baseline PFT could not predict pulmonary toxicity or survival. Additionally, the study demonstrated only minimal decreases in patients’ FEV1 (5.8%) and DLCO (6%) at 2 years.12
Our study sought to identify a cut-off on FEV1 or DLCO that could be associated with increased toxicity. We also evaluated the incidence of acute toxicities grade ≥ 2 by stratifying patients according to FEV1 into subgroups: FEV1 < 1.0 L, FEV1 < 1.5 L, FEV1 < 30% of predicted and FEV1 < 35% of predicted. However, similar to other studies, we did not find any value that was significantly associated with increased toxicity that could preclude empiric SABR. One possible reason is that no treatment is offered for patients with extremely poor lung function as deemed by clinical judgement, therefore data on these patients is unavailable. In contradiction to other studies, our study found that oxygen dependence before treatment was significantly associated with development of acute toxicities. The exact mechanism for this association is unknown and could not be elucidated by baseline PFT. One possible explanation is that SABR could lead to oxygen free radical generation. In addition, our study indicated that those who developed acute toxicities had worse OS.
Limitations
Our study is limited by caveats of a retrospective study and its small sample size, but is in line with the reported literature (ranging from 33 to 88 patients).1,7,8 Another limitation is that data on pretreatment DLCO was missing in 37 patients and the lack of statistical robustness in terms of the smaller inoperable cohort, which limits the analyses of these factors in regards to anticipated morbidity from SABR. Also, given this is data collected from the US Department of Veterans Affairs, only 3% of our sample was female.
Conclusions
Empiric SABR for patients with presumed early-stage NSCLC appears to be safe and might positively impact OS. Development of any acute toxicity grade ≥ 2 was significantly associated with dependence on supplemental oxygen before treatment, central tumor location, and development of new oxygen requirement. No association was found in patients with poor pulmonary function before treatment because we could not find a FEV1 or DLCO cutoff that could preclude patients from empiric SABR. Considering the poor survival of untreated early-stage NSCLC, coupled with the efficacy and safety of empiric SABR for those with presumed disease, definitive SABR should be offered selectively within this patient population.
Acknowledgments
Drs. Park, Whiting and Castillo contributed to data collection. Drs. Park, Govindan and Castillo contributed to the statistical analysis and writing the first draft and final manuscript. Drs. Park, Govindan, Huang, and Reddy contributed to the discussion section.
1. Harkenrider MM, Bertke MH, Dunlap NE. Stereotactic body radiation therapy for unbiopsied early-stage lung cancer: a multi-institutional analysis. Am J Clin Oncol. 2014;37(4):337-342. doi:10.1097/COC.0b013e318277d822
2. Raz DJ, Zell JA, Ou SH, Gandara DR, Anton-Culver H, Jablons DM. Natural history of stage I non-small cell lung cancer: implications for early detection. Chest. 2007;132(1):193-199. doi:10.1378/chest.06-3096
3. Nanda RH, Liu Y, Gillespie TW, et al. Stereotactic body radiation therapy versus no treatment for early stage non-small cell lung cancer in medically inoperable elderly patients: a National Cancer Data Base analysis. Cancer. 2015;121(23):4222-4230. doi:10.1002/cncr.29640
4. Ball D, Mai GT, Vinod S, et al. Stereotactic ablative radiotherapy versus standard radiotherapy in stage 1 non-small-cell lung cancer (TROG 09.02 CHISEL): a phase 3, open-label, randomised controlled trial. Lancet Oncol. 2019;20(4):494-503. doi:10.1016/S1470-2045(18)30896-9
5. Timmerman R, Paulus R, Galvin J, et al. Stereotactic body radiation therapy for inoperable early stage lung cancer. JAMA. 2010;303(11):1070-1076. doi:10.1001/jama.2010.261
6. Smith MA, Battafarano RJ, Meyers BF, Zoole JB, Cooper JD, Patterson GA. Prevalence of benign disease in patients undergoing resection for suspected lung cancer. Ann Thorac Surg. 2006;81(5):1824-1828. doi:10.1016/j.athoracsur.2005.11.010
7. Haidar YM, Rahn DA 3rd, Nath S, et al. Comparison of outcomes following stereotactic body radiotherapy for nonsmall cell lung cancer in patients with and without pathological confirmation. Ther Adv Respir Dis. 2014;8(1):3-12. doi:10.1177/1753465813512545
8. Fischer-Valuck BW, Boggs H, Katz S, Durci M, Acharya S, Rosen LR. Comparison of stereotactic body radiation therapy for biopsy-proven versus radiographically diagnosed early-stage non-small lung cancer: a single-institution experience. Tumori. 2015;101(3):287-293. doi:10.5301/tj.5000279
9. Guckenberger M, Kestin LL, Hope AJ, et al. Is there a lower limit of pretreatment pulmonary function for safe and effective stereotactic body radiotherapy for early-stage non-small cell lung cancer? J Thorac Oncol. 2012;7:542-551. doi:10.1097/JTO.0b013e31824165d7
10. Wang J, Cao J, Yuan S, et al. Poor baseline pulmonary function may not increase the risk of radiation-induced lung toxicity. Int J Radiat Oncol Biol Phys. 2013;85(3):798-804. doi:10.1016/j.ijrobp.2012.06.040
11. Henderson M, McGarry R, Yiannoutsos C, et al. Baseline pulmonary function as a predictor for survival and decline in pulmonary function over time in patients undergoing stereotactic body radiotherapy for the treatment of stage I non-small-cell lung cancer. Int J Radiat Oncol Biol Phys. 2008;72(2):404-409. doi:10.1016/j.ijrobp.2007.12.051
12. Stanic S, Paulus R, Timmerman RD, et al. No clinically significant changes in pulmonary function following stereotactic body radiation therapy for early- stage peripheral non-small cell lung cancer: an analysis of RTOG 0236. Int J Radiat Oncol Biol Phys. 2014;88(5):1092-1099. doi:10.1016/j.ijrobp.2013.12.050
1. Harkenrider MM, Bertke MH, Dunlap NE. Stereotactic body radiation therapy for unbiopsied early-stage lung cancer: a multi-institutional analysis. Am J Clin Oncol. 2014;37(4):337-342. doi:10.1097/COC.0b013e318277d822
2. Raz DJ, Zell JA, Ou SH, Gandara DR, Anton-Culver H, Jablons DM. Natural history of stage I non-small cell lung cancer: implications for early detection. Chest. 2007;132(1):193-199. doi:10.1378/chest.06-3096
3. Nanda RH, Liu Y, Gillespie TW, et al. Stereotactic body radiation therapy versus no treatment for early stage non-small cell lung cancer in medically inoperable elderly patients: a National Cancer Data Base analysis. Cancer. 2015;121(23):4222-4230. doi:10.1002/cncr.29640
4. Ball D, Mai GT, Vinod S, et al. Stereotactic ablative radiotherapy versus standard radiotherapy in stage 1 non-small-cell lung cancer (TROG 09.02 CHISEL): a phase 3, open-label, randomised controlled trial. Lancet Oncol. 2019;20(4):494-503. doi:10.1016/S1470-2045(18)30896-9
5. Timmerman R, Paulus R, Galvin J, et al. Stereotactic body radiation therapy for inoperable early stage lung cancer. JAMA. 2010;303(11):1070-1076. doi:10.1001/jama.2010.261
6. Smith MA, Battafarano RJ, Meyers BF, Zoole JB, Cooper JD, Patterson GA. Prevalence of benign disease in patients undergoing resection for suspected lung cancer. Ann Thorac Surg. 2006;81(5):1824-1828. doi:10.1016/j.athoracsur.2005.11.010
7. Haidar YM, Rahn DA 3rd, Nath S, et al. Comparison of outcomes following stereotactic body radiotherapy for nonsmall cell lung cancer in patients with and without pathological confirmation. Ther Adv Respir Dis. 2014;8(1):3-12. doi:10.1177/1753465813512545
8. Fischer-Valuck BW, Boggs H, Katz S, Durci M, Acharya S, Rosen LR. Comparison of stereotactic body radiation therapy for biopsy-proven versus radiographically diagnosed early-stage non-small lung cancer: a single-institution experience. Tumori. 2015;101(3):287-293. doi:10.5301/tj.5000279
9. Guckenberger M, Kestin LL, Hope AJ, et al. Is there a lower limit of pretreatment pulmonary function for safe and effective stereotactic body radiotherapy for early-stage non-small cell lung cancer? J Thorac Oncol. 2012;7:542-551. doi:10.1097/JTO.0b013e31824165d7
10. Wang J, Cao J, Yuan S, et al. Poor baseline pulmonary function may not increase the risk of radiation-induced lung toxicity. Int J Radiat Oncol Biol Phys. 2013;85(3):798-804. doi:10.1016/j.ijrobp.2012.06.040
11. Henderson M, McGarry R, Yiannoutsos C, et al. Baseline pulmonary function as a predictor for survival and decline in pulmonary function over time in patients undergoing stereotactic body radiotherapy for the treatment of stage I non-small-cell lung cancer. Int J Radiat Oncol Biol Phys. 2008;72(2):404-409. doi:10.1016/j.ijrobp.2007.12.051
12. Stanic S, Paulus R, Timmerman RD, et al. No clinically significant changes in pulmonary function following stereotactic body radiation therapy for early- stage peripheral non-small cell lung cancer: an analysis of RTOG 0236. Int J Radiat Oncol Biol Phys. 2014;88(5):1092-1099. doi:10.1016/j.ijrobp.2013.12.050
Do Clinicians Understand Quality Metric Data?
Central line-associated bloodstream infections (CLABSIs) are common and serious occurrences across healthcare systems, with an attributable mortality of 12% to 25%.1,2 Given this burden,3–5 CLABSI is a focus for both high-profile public reporting and quality improvement interventions. An integral component of such interventions is audit and feedback via quality metrics. These measures are intended to allow decision makers to assess their own performance and appropriately allocate resources. Quality metrics present a substantial cost to health systems, with an estimated $15.4 billion dollars spent annually simply for reporting.6 Despite this toll, “audit and feedback” interventions have proven to be variably successful.7–9 The mechanisms that limit the effectiveness of these interventions remain
poorly understood.
One plausible explanation for limited efficacy of quality metrics is inadequate clinician numeracy—that is, “the ability to understand the quantitative aspects of clinical medicine, original research, quality improvement, and financial matters.”10 Indeed, clinicians are not consistently able to interpret probabilities and or clinical test characteristics. For example, Wegwarth et al. identified shortcomings in physician application of lead-time bias toward cancer screening.11 Additionally, studies have demonstrated systematic misinterpretations of probabilistic information in clinical settings, along with misconceptions regarding the impact of prevalence on post-test probabilities.12,13 Effective interpretation of rates may be a key—if unstated—requirement of many CLABSI quality improvement efforts.14–19 Our broader hypothesis is that clinicians who can more accurately interpret quality data, even if only from their own institution, are more likely to act on it appropriately and persistently than those who feel they must depend on a preprocessed interpretation of that same data by some other expert.
Therefore, we designed a survey to assess the numeracy of clinicians on CLABSI data presented in a prototypical feedback report. We studied 3 domains of comprehension: (1) basic numeracy: numerical tasks related to simple data; (2) risk-adjustment numeracy: numerical tasks related to risk-adjusted data; and (3) risk-adjustment interpretation: inferential tasks concerning risk-adjusted data. We hypothesized that clinician performance would vary substantially across domains, with the poorest performance in risk-
adjusted data.
METHODS
We conducted a cross-sectional survey of clinician numeracy regarding CLABSI feedback data. Respondents were also asked to provide demographic information and opinions regarding the reliability of quality metric data. Survey recruitment occurred on Twitter, a novel approach that leveraged social media to facilitate rapid recruitment of participants. The study instrument was administered using a web survey with randomized question order to preclude any possibility of order effects between questions. The study was deemed Institutional Review Board exempt by the University of Michigan: protocol HUM00106696.
Data Presentation Method
To determine the optimal mode of presenting data, we reviewed the literature on quality metric numeracy and presentation methods. Additionally, we evaluated quality metric presentation methods used by the Centers for Disease Control and Prevention (CDC), Centers for Medicare & Medicaid Services (CMS), and a tertiary academic medical center. After assessing the available literature and options, we adapted a CLABSI data presentation array from a study that had qualitatively validated the format using physician feedback (Appendix).20 We used hypothetical CLABSI data for our survey.
Survey Development
We developed a survey that included an 11-item test regarding CLABSI numeracy and data interpretation. Additional questions related to quality metric reliability and demographic information were included. No preexisting assessment tools existed for our areas of interest. Therefore, we developed a novel instrument using a broad, exploratory approach as others have employed.21
First, we defined 3 conceptual categories related to CLABSI data. Within this conceptual framework, an iterative process of development and revision was used to assemble a question bank from which the survey would be constructed. A series of think-aloud sessions were held to evaluate each prompt for precision, clarity, and accuracy in assessing the conceptual categories. Correct and incorrect answers were defined based on literature review in conjunction with input from methodological and content experts (TJI and VC) (see Appendix for answer explanations).
Within the conceptual categories related to CLABSI risk-adjustment, a key measure is the standardized infection ratio (SIR). This value is defined as the ratio of observed number of CLABSI over the expected number of CLABSIs.22 This is the primary measure to stratify hospital performance, and it was used in our assessment of risk-adjustment comprehension. In total, 54 question prompts were developed and subsequently narrowed to 11 study questions for the initial survey.
The instrument was then pretested in a cohort of 8 hospitalists and intensivists to ensure appropriate comprehension, retrieval, and judgment processes.23 Questions were revised based on feedback from this cognitive testing to constitute the final instrument. During the survey, the data table was reshown on each page directly above each question and so was always on the same screen for the respondents.
Survey Sample
We innovated by using Twitter as an online platform for recruiting participants; we used Survey Monkey to host the electronic instrument. Two authors (TJI, VC) systematically sent out solicitation tweets to their followers. These tweets clearly indicated that the recruitment was for the purpose of a research study, and participants would receive no financial reward/incentive (Appendix). A link to the survey was provided in each tweet, and the period of recruitment was 30 days. To ensure respondents were clinicians, they needed to first answer a screening question recognizing that central lines were placed in the subclavian site but not the aorta, iliac, or radial sites.
To prevent systematic or anchoring biases, the order of questions was electronically randomized for each respondent. The primary outcome was the percentage correct of attempted questions.
Statistical Analysis
Descriptive statistics were calculated for all demographic variables. The primary outcome was evaluated as a dichotomous variable for each question (correct vs. incorrect response), and as a continuous variable when assessing mean percent correct on the overall survey. Demographic and conceptual associations were assessed via t-tests, chi-square, or Fisher exact tests. Point biserial correlations were calculated to assess for associations between response to a single question and overall performance on the survey.
To evaluate the association between various respondent characteristics and responses, logistic regression analyses were performed. An ANOVA was performed to assess the association between self-reported reliability of quality metric data and the overall performance on attempted items. Analyses were conducted using STATA MP 14.0 (College Station, TX); P <0.05 was considered statistically significant.
RESULTS
A total of 97 respondents attempted at least 1 question on the survey, and 72 respondents attempted all 11 questions, yielding 939 unique responses for analysis. Seventy respondents (87%) identified as doctors or nurses, and 44 (55%) reported having 6 to 20 years of experience; the survey cohort also came from 6 nations (Table 1). All respondents answered the CLABSI knowledge filter question correctly.
Primary Outcome
The mean percent correct of attempted questions was 61% (standard deviation 21%, interquartile range 50%-75%) (Figure 1). Of those who answered all 11 CLABSI questions, the mean percent correct was 63% (95% CI, 59%-67%). Some questions were answered correctly more often than others—ranging from 17% to 95% (Table 2). Doctors answered 68% of questions correctly (95% CI, 63%-73%), while nurses and other respondents answered 57% of questions correctly (95% CI, 52%-62%) (P = 0.003). Other demographic variables—including self-reported involvement in a quality improvement committee and being from the United States versus elsewhere—were not associated with survey performance. The point biserial correlations for each individual question with overall performance were all more than 0.2 (range 0.24–0.62) and all statistically significant at P < 0.05.
Concept-Specific Performance
Average percent correct declined across categories as numeracy requirements increased (P < 0.05 for all pairwise comparisons). In the area of basic numeracy, respondents’ mean percent correct was 82% (95% CI, 77%-87%) of attempted. This category had 4 questions, with a performance range of 77% to 90%. For example, on the question, “Which hospital has the lowest CLABSI rate?”, 80% of respondents answered correctly. For risk-adjustment numeracy, the mean percent correct was 70% (95% CI, 64%-76%); 2 items assessed this category. For “Which is better: a higher or lower SIR?”, 95% of the cohort answered correctly. However, on “If hospital B had its number of projected infection halved, what is its SIR?”, only 46% of those who attempted the question answered correctly.
Questions featuring risk-adjustment interpretation had an average percent correct of 43% (95% CI, 37%-49%). Five questions made up this category, with a percent correct range of 17% to 75%. For example, on the question, “Which hospital’s patients are the most predisposed to developing CLABSI?”, only 32% of respondents answered this correctly. In contrast, for the question “Which hospital is most effective at preventing CLABSI?”, 51% answered correctly. Figure 2 illustrates the cohort’s performance on each conceptual category while Table 2 displays question-by-question results.
Opinions Regarding CLABSI Data Reliability
Respondents were also asked about their opinion regarding the reliability of CLABSI quality metric data. Forty-three percent of respondents stated that such data were reliable at best 50% of the time. Notably, 10% of respondents indicated that CLABSI quality metric data were rarely or never reliable. There was no association between perceived reliability of quality metric data and survey performance (P = 0.87).
DISCUSSION
This Twitter-based study found wide variation in clinician interpretation of CLABSI quality data, with low overall performance. In particular, comprehension and interpretation of risk-adjusted data were substantially worse than unadjusted data. Although doctors performed somewhat better than nurses and other respondents, those involved in quality improvement initiatives performed no better than respondents who were not. Collectively, these findings suggest clinicians may not reliably comprehend quality metric data, potentially affecting their ability to utilize audit and feedback data. These results may have important implications for policy efforts that seek to leverage quality metric data to improve patient safety.
An integral component of many contemporary quality improvement initiatives is audit and feedback through metrics.6 Unfortunately, formal audit and feedback, along with other similar methods that benchmark data, have not consistently improved outcomes.24–27 A recent meta-analysis noted that audit and feedback interventions are not becoming more efficacious over time; the study further asserted that “new trials have provided little new knowledge regarding key effect modifiers.”9 Our findings suggest that numeracy and comprehension of quality metrics may be important candidate effect modifiers not previously considered. Simply put: we hypothesize that without intrinsic comprehension of data, impetus or insight to change practice might be diminished. In other words, clinicians may be more apt to act on insights they themselves derive from the data than when they are simply told what the data “mean.”
The present study further demonstrates that clinicians do not understand risk-adjusted data as well as raw data. Risk-adjustment has long been recognized as necessary to compare outcomes among hospitals.28,29 However, risk-adjustment is complex and, by its nature, difficult to understand. Although efforts have focused on improving the statistical reliability of quality metrics, this may represent but one half of the equation. Numeracy and interpretation of the data by decision makers are potentially equally important to effecting change. Because clinicians seem to have difficulty understanding risk-adjusted data, this deficit may be of growing importance as our risk-adjustment techniques become more sophisticated.
We note that clinicians expressed concerns regarding the reliability of quality metric feedback. These findings corroborate recent research that has reported reservations from hospital leaders concerning quality data.30,31 However, as shown in the context of patients and healthcare decisions, the aversion associated with quality metrics may be related to incomplete understanding of the data.32 Whether perceptions of unreliability drive lack of understanding or, conversely, whether lack of understanding fuels perceived unreliability is an important question that requires further study.
This study has several strengths. First, we used rigorous survey development techniques to evaluate the understudied issue of quality metric numeracy. Second, our sample size was sufficient to show statistically significant differences in numeracy and comprehension of CLABSI quality metric data. Third, we leveraged social media to rapidly acquire this sample. Finally, our results provided new insights that may have important implications in the area of quality metrics.
There were also limitations to our study. First, the Twitter-derived sample precludes the calculation of a response rate and may not be representative of individuals engaged in CLABSI prevention. However, respondents were solicited from the Twitter-followers of 2 health services researchers (TJI, VC) who are actively engaged in scholarly activities pertaining to critically ill patients and hospital-acquired complications. Thus, our sample likely represents a highly motivated subset that engages in these topics on a regular basis—potentially making them more numerate than average clinicians. Second, we did not ask whether the respondents had previously seen CLABSI data specifically, so we cannot stratify by exposure to such data. Third, this study assessed only CLABSI quality metric data; generalizations regarding numeracy with other metrics should be made with caution. However, as many such data are presented in similar formats, we suspect our findings are applicable to similar audit-and-feedback initiatives.
The findings of this study serve as a stimulus for further inquiry. Research of this nature needs to be carried out in samples drawn from specific, policy-relevant populations (eg, infection control practitioners, bedside nurses, intensive care unit directors). Such studies should include longitudinal assessments of numeracy that attempt to mechanistically examine its impact on CLABSI prevention efforts and outcomes. The latter is an important issue as the link between numeracy and behavioral response, while plausible, cannot be assumed, particularly given the complexity of issues related to behavioral modification.33 Additionally, whether alternate presentations of quality data affect numeracy, interpretation, and performance is worthy of further testing; indeed, this has been shown to be the case in other forms of communication.34–37 Until data from larger samples are available, it may be prudent for quality improvement leaders to assess the comprehension of local clinicians regarding feedback and whether lack of adequate comprehension is a barrier to deploying quality improvement interventions.
Quality measurement is a cornerstone of patient safety as it seeks to assess and improve the care delivered at the bedside. Rigorous metric development is important; however, ensuring that decision makers understand complex quality metrics may be equally fundamental. Given the cost of examining quality, elucidating the mechanisms of numeracy and interpretation as decision makers engage with quality metric data is necessary, along with whether improved comprehension leads to behavior change. Such inquiry may provide an evidence-base to shape alterations in quality metric deployment that will ensure maximal efficacy in driving practice change.
Disclosures
This work was supported by VA HSR&D IIR-13-079 (TJI). Dr. Chopra is supported by a career development award from the Agency of Healthcare Research and Quality (1-K08-HS022835-01). The views expressed here are the authors’ own and do not necessarily represent the view of the US Government or the Department of Veterans’ Affairs. The authors report no conflicts of interest.
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34. Hamstra DA, Johnson SB, Daignault S, et al. The impact of numeracy on verbatim knowledge of the longitudinal risk for prostate cancer recurrence following radiation therapy. Med Decis Making. 2015;35(1):27-36. PubMed
35. Hawley ST, Zikmund-Fisher B, Ubel P, Jancovic A, Lucas T, Fagerlin A. The impact of the format of graphical presentation on health-related knowledge and treatment choices. Patient Educ Couns. 2008;73(3):448-455. PubMed
36. Zikmund-Fisher BJ, Witteman HO, Dickson M, et al. Blocks, ovals, or people? Icon type affects risk perceptions and recall of pictographs. Med Decis Making. 2014;34(4):443-453. PubMed
37. Korfage IJ, Fuhrel-Forbis A, Ubel PA, et al. Informed choice about breast cancer prevention: randomized controlled trial of an online decision aid intervention. Breast Cancer Res. 2013;15(5):R74. PubMed
Central line-associated bloodstream infections (CLABSIs) are common and serious occurrences across healthcare systems, with an attributable mortality of 12% to 25%.1,2 Given this burden,3–5 CLABSI is a focus for both high-profile public reporting and quality improvement interventions. An integral component of such interventions is audit and feedback via quality metrics. These measures are intended to allow decision makers to assess their own performance and appropriately allocate resources. Quality metrics present a substantial cost to health systems, with an estimated $15.4 billion dollars spent annually simply for reporting.6 Despite this toll, “audit and feedback” interventions have proven to be variably successful.7–9 The mechanisms that limit the effectiveness of these interventions remain
poorly understood.
One plausible explanation for limited efficacy of quality metrics is inadequate clinician numeracy—that is, “the ability to understand the quantitative aspects of clinical medicine, original research, quality improvement, and financial matters.”10 Indeed, clinicians are not consistently able to interpret probabilities and or clinical test characteristics. For example, Wegwarth et al. identified shortcomings in physician application of lead-time bias toward cancer screening.11 Additionally, studies have demonstrated systematic misinterpretations of probabilistic information in clinical settings, along with misconceptions regarding the impact of prevalence on post-test probabilities.12,13 Effective interpretation of rates may be a key—if unstated—requirement of many CLABSI quality improvement efforts.14–19 Our broader hypothesis is that clinicians who can more accurately interpret quality data, even if only from their own institution, are more likely to act on it appropriately and persistently than those who feel they must depend on a preprocessed interpretation of that same data by some other expert.
Therefore, we designed a survey to assess the numeracy of clinicians on CLABSI data presented in a prototypical feedback report. We studied 3 domains of comprehension: (1) basic numeracy: numerical tasks related to simple data; (2) risk-adjustment numeracy: numerical tasks related to risk-adjusted data; and (3) risk-adjustment interpretation: inferential tasks concerning risk-adjusted data. We hypothesized that clinician performance would vary substantially across domains, with the poorest performance in risk-
adjusted data.
METHODS
We conducted a cross-sectional survey of clinician numeracy regarding CLABSI feedback data. Respondents were also asked to provide demographic information and opinions regarding the reliability of quality metric data. Survey recruitment occurred on Twitter, a novel approach that leveraged social media to facilitate rapid recruitment of participants. The study instrument was administered using a web survey with randomized question order to preclude any possibility of order effects between questions. The study was deemed Institutional Review Board exempt by the University of Michigan: protocol HUM00106696.
Data Presentation Method
To determine the optimal mode of presenting data, we reviewed the literature on quality metric numeracy and presentation methods. Additionally, we evaluated quality metric presentation methods used by the Centers for Disease Control and Prevention (CDC), Centers for Medicare & Medicaid Services (CMS), and a tertiary academic medical center. After assessing the available literature and options, we adapted a CLABSI data presentation array from a study that had qualitatively validated the format using physician feedback (Appendix).20 We used hypothetical CLABSI data for our survey.
Survey Development
We developed a survey that included an 11-item test regarding CLABSI numeracy and data interpretation. Additional questions related to quality metric reliability and demographic information were included. No preexisting assessment tools existed for our areas of interest. Therefore, we developed a novel instrument using a broad, exploratory approach as others have employed.21
First, we defined 3 conceptual categories related to CLABSI data. Within this conceptual framework, an iterative process of development and revision was used to assemble a question bank from which the survey would be constructed. A series of think-aloud sessions were held to evaluate each prompt for precision, clarity, and accuracy in assessing the conceptual categories. Correct and incorrect answers were defined based on literature review in conjunction with input from methodological and content experts (TJI and VC) (see Appendix for answer explanations).
Within the conceptual categories related to CLABSI risk-adjustment, a key measure is the standardized infection ratio (SIR). This value is defined as the ratio of observed number of CLABSI over the expected number of CLABSIs.22 This is the primary measure to stratify hospital performance, and it was used in our assessment of risk-adjustment comprehension. In total, 54 question prompts were developed and subsequently narrowed to 11 study questions for the initial survey.
The instrument was then pretested in a cohort of 8 hospitalists and intensivists to ensure appropriate comprehension, retrieval, and judgment processes.23 Questions were revised based on feedback from this cognitive testing to constitute the final instrument. During the survey, the data table was reshown on each page directly above each question and so was always on the same screen for the respondents.
Survey Sample
We innovated by using Twitter as an online platform for recruiting participants; we used Survey Monkey to host the electronic instrument. Two authors (TJI, VC) systematically sent out solicitation tweets to their followers. These tweets clearly indicated that the recruitment was for the purpose of a research study, and participants would receive no financial reward/incentive (Appendix). A link to the survey was provided in each tweet, and the period of recruitment was 30 days. To ensure respondents were clinicians, they needed to first answer a screening question recognizing that central lines were placed in the subclavian site but not the aorta, iliac, or radial sites.
To prevent systematic or anchoring biases, the order of questions was electronically randomized for each respondent. The primary outcome was the percentage correct of attempted questions.
Statistical Analysis
Descriptive statistics were calculated for all demographic variables. The primary outcome was evaluated as a dichotomous variable for each question (correct vs. incorrect response), and as a continuous variable when assessing mean percent correct on the overall survey. Demographic and conceptual associations were assessed via t-tests, chi-square, or Fisher exact tests. Point biserial correlations were calculated to assess for associations between response to a single question and overall performance on the survey.
To evaluate the association between various respondent characteristics and responses, logistic regression analyses were performed. An ANOVA was performed to assess the association between self-reported reliability of quality metric data and the overall performance on attempted items. Analyses were conducted using STATA MP 14.0 (College Station, TX); P <0.05 was considered statistically significant.
RESULTS
A total of 97 respondents attempted at least 1 question on the survey, and 72 respondents attempted all 11 questions, yielding 939 unique responses for analysis. Seventy respondents (87%) identified as doctors or nurses, and 44 (55%) reported having 6 to 20 years of experience; the survey cohort also came from 6 nations (Table 1). All respondents answered the CLABSI knowledge filter question correctly.
Primary Outcome
The mean percent correct of attempted questions was 61% (standard deviation 21%, interquartile range 50%-75%) (Figure 1). Of those who answered all 11 CLABSI questions, the mean percent correct was 63% (95% CI, 59%-67%). Some questions were answered correctly more often than others—ranging from 17% to 95% (Table 2). Doctors answered 68% of questions correctly (95% CI, 63%-73%), while nurses and other respondents answered 57% of questions correctly (95% CI, 52%-62%) (P = 0.003). Other demographic variables—including self-reported involvement in a quality improvement committee and being from the United States versus elsewhere—were not associated with survey performance. The point biserial correlations for each individual question with overall performance were all more than 0.2 (range 0.24–0.62) and all statistically significant at P < 0.05.
Concept-Specific Performance
Average percent correct declined across categories as numeracy requirements increased (P < 0.05 for all pairwise comparisons). In the area of basic numeracy, respondents’ mean percent correct was 82% (95% CI, 77%-87%) of attempted. This category had 4 questions, with a performance range of 77% to 90%. For example, on the question, “Which hospital has the lowest CLABSI rate?”, 80% of respondents answered correctly. For risk-adjustment numeracy, the mean percent correct was 70% (95% CI, 64%-76%); 2 items assessed this category. For “Which is better: a higher or lower SIR?”, 95% of the cohort answered correctly. However, on “If hospital B had its number of projected infection halved, what is its SIR?”, only 46% of those who attempted the question answered correctly.
Questions featuring risk-adjustment interpretation had an average percent correct of 43% (95% CI, 37%-49%). Five questions made up this category, with a percent correct range of 17% to 75%. For example, on the question, “Which hospital’s patients are the most predisposed to developing CLABSI?”, only 32% of respondents answered this correctly. In contrast, for the question “Which hospital is most effective at preventing CLABSI?”, 51% answered correctly. Figure 2 illustrates the cohort’s performance on each conceptual category while Table 2 displays question-by-question results.
Opinions Regarding CLABSI Data Reliability
Respondents were also asked about their opinion regarding the reliability of CLABSI quality metric data. Forty-three percent of respondents stated that such data were reliable at best 50% of the time. Notably, 10% of respondents indicated that CLABSI quality metric data were rarely or never reliable. There was no association between perceived reliability of quality metric data and survey performance (P = 0.87).
DISCUSSION
This Twitter-based study found wide variation in clinician interpretation of CLABSI quality data, with low overall performance. In particular, comprehension and interpretation of risk-adjusted data were substantially worse than unadjusted data. Although doctors performed somewhat better than nurses and other respondents, those involved in quality improvement initiatives performed no better than respondents who were not. Collectively, these findings suggest clinicians may not reliably comprehend quality metric data, potentially affecting their ability to utilize audit and feedback data. These results may have important implications for policy efforts that seek to leverage quality metric data to improve patient safety.
An integral component of many contemporary quality improvement initiatives is audit and feedback through metrics.6 Unfortunately, formal audit and feedback, along with other similar methods that benchmark data, have not consistently improved outcomes.24–27 A recent meta-analysis noted that audit and feedback interventions are not becoming more efficacious over time; the study further asserted that “new trials have provided little new knowledge regarding key effect modifiers.”9 Our findings suggest that numeracy and comprehension of quality metrics may be important candidate effect modifiers not previously considered. Simply put: we hypothesize that without intrinsic comprehension of data, impetus or insight to change practice might be diminished. In other words, clinicians may be more apt to act on insights they themselves derive from the data than when they are simply told what the data “mean.”
The present study further demonstrates that clinicians do not understand risk-adjusted data as well as raw data. Risk-adjustment has long been recognized as necessary to compare outcomes among hospitals.28,29 However, risk-adjustment is complex and, by its nature, difficult to understand. Although efforts have focused on improving the statistical reliability of quality metrics, this may represent but one half of the equation. Numeracy and interpretation of the data by decision makers are potentially equally important to effecting change. Because clinicians seem to have difficulty understanding risk-adjusted data, this deficit may be of growing importance as our risk-adjustment techniques become more sophisticated.
We note that clinicians expressed concerns regarding the reliability of quality metric feedback. These findings corroborate recent research that has reported reservations from hospital leaders concerning quality data.30,31 However, as shown in the context of patients and healthcare decisions, the aversion associated with quality metrics may be related to incomplete understanding of the data.32 Whether perceptions of unreliability drive lack of understanding or, conversely, whether lack of understanding fuels perceived unreliability is an important question that requires further study.
This study has several strengths. First, we used rigorous survey development techniques to evaluate the understudied issue of quality metric numeracy. Second, our sample size was sufficient to show statistically significant differences in numeracy and comprehension of CLABSI quality metric data. Third, we leveraged social media to rapidly acquire this sample. Finally, our results provided new insights that may have important implications in the area of quality metrics.
There were also limitations to our study. First, the Twitter-derived sample precludes the calculation of a response rate and may not be representative of individuals engaged in CLABSI prevention. However, respondents were solicited from the Twitter-followers of 2 health services researchers (TJI, VC) who are actively engaged in scholarly activities pertaining to critically ill patients and hospital-acquired complications. Thus, our sample likely represents a highly motivated subset that engages in these topics on a regular basis—potentially making them more numerate than average clinicians. Second, we did not ask whether the respondents had previously seen CLABSI data specifically, so we cannot stratify by exposure to such data. Third, this study assessed only CLABSI quality metric data; generalizations regarding numeracy with other metrics should be made with caution. However, as many such data are presented in similar formats, we suspect our findings are applicable to similar audit-and-feedback initiatives.
The findings of this study serve as a stimulus for further inquiry. Research of this nature needs to be carried out in samples drawn from specific, policy-relevant populations (eg, infection control practitioners, bedside nurses, intensive care unit directors). Such studies should include longitudinal assessments of numeracy that attempt to mechanistically examine its impact on CLABSI prevention efforts and outcomes. The latter is an important issue as the link between numeracy and behavioral response, while plausible, cannot be assumed, particularly given the complexity of issues related to behavioral modification.33 Additionally, whether alternate presentations of quality data affect numeracy, interpretation, and performance is worthy of further testing; indeed, this has been shown to be the case in other forms of communication.34–37 Until data from larger samples are available, it may be prudent for quality improvement leaders to assess the comprehension of local clinicians regarding feedback and whether lack of adequate comprehension is a barrier to deploying quality improvement interventions.
Quality measurement is a cornerstone of patient safety as it seeks to assess and improve the care delivered at the bedside. Rigorous metric development is important; however, ensuring that decision makers understand complex quality metrics may be equally fundamental. Given the cost of examining quality, elucidating the mechanisms of numeracy and interpretation as decision makers engage with quality metric data is necessary, along with whether improved comprehension leads to behavior change. Such inquiry may provide an evidence-base to shape alterations in quality metric deployment that will ensure maximal efficacy in driving practice change.
Disclosures
This work was supported by VA HSR&D IIR-13-079 (TJI). Dr. Chopra is supported by a career development award from the Agency of Healthcare Research and Quality (1-K08-HS022835-01). The views expressed here are the authors’ own and do not necessarily represent the view of the US Government or the Department of Veterans’ Affairs. The authors report no conflicts of interest.
Central line-associated bloodstream infections (CLABSIs) are common and serious occurrences across healthcare systems, with an attributable mortality of 12% to 25%.1,2 Given this burden,3–5 CLABSI is a focus for both high-profile public reporting and quality improvement interventions. An integral component of such interventions is audit and feedback via quality metrics. These measures are intended to allow decision makers to assess their own performance and appropriately allocate resources. Quality metrics present a substantial cost to health systems, with an estimated $15.4 billion dollars spent annually simply for reporting.6 Despite this toll, “audit and feedback” interventions have proven to be variably successful.7–9 The mechanisms that limit the effectiveness of these interventions remain
poorly understood.
One plausible explanation for limited efficacy of quality metrics is inadequate clinician numeracy—that is, “the ability to understand the quantitative aspects of clinical medicine, original research, quality improvement, and financial matters.”10 Indeed, clinicians are not consistently able to interpret probabilities and or clinical test characteristics. For example, Wegwarth et al. identified shortcomings in physician application of lead-time bias toward cancer screening.11 Additionally, studies have demonstrated systematic misinterpretations of probabilistic information in clinical settings, along with misconceptions regarding the impact of prevalence on post-test probabilities.12,13 Effective interpretation of rates may be a key—if unstated—requirement of many CLABSI quality improvement efforts.14–19 Our broader hypothesis is that clinicians who can more accurately interpret quality data, even if only from their own institution, are more likely to act on it appropriately and persistently than those who feel they must depend on a preprocessed interpretation of that same data by some other expert.
Therefore, we designed a survey to assess the numeracy of clinicians on CLABSI data presented in a prototypical feedback report. We studied 3 domains of comprehension: (1) basic numeracy: numerical tasks related to simple data; (2) risk-adjustment numeracy: numerical tasks related to risk-adjusted data; and (3) risk-adjustment interpretation: inferential tasks concerning risk-adjusted data. We hypothesized that clinician performance would vary substantially across domains, with the poorest performance in risk-
adjusted data.
METHODS
We conducted a cross-sectional survey of clinician numeracy regarding CLABSI feedback data. Respondents were also asked to provide demographic information and opinions regarding the reliability of quality metric data. Survey recruitment occurred on Twitter, a novel approach that leveraged social media to facilitate rapid recruitment of participants. The study instrument was administered using a web survey with randomized question order to preclude any possibility of order effects between questions. The study was deemed Institutional Review Board exempt by the University of Michigan: protocol HUM00106696.
Data Presentation Method
To determine the optimal mode of presenting data, we reviewed the literature on quality metric numeracy and presentation methods. Additionally, we evaluated quality metric presentation methods used by the Centers for Disease Control and Prevention (CDC), Centers for Medicare & Medicaid Services (CMS), and a tertiary academic medical center. After assessing the available literature and options, we adapted a CLABSI data presentation array from a study that had qualitatively validated the format using physician feedback (Appendix).20 We used hypothetical CLABSI data for our survey.
Survey Development
We developed a survey that included an 11-item test regarding CLABSI numeracy and data interpretation. Additional questions related to quality metric reliability and demographic information were included. No preexisting assessment tools existed for our areas of interest. Therefore, we developed a novel instrument using a broad, exploratory approach as others have employed.21
First, we defined 3 conceptual categories related to CLABSI data. Within this conceptual framework, an iterative process of development and revision was used to assemble a question bank from which the survey would be constructed. A series of think-aloud sessions were held to evaluate each prompt for precision, clarity, and accuracy in assessing the conceptual categories. Correct and incorrect answers were defined based on literature review in conjunction with input from methodological and content experts (TJI and VC) (see Appendix for answer explanations).
Within the conceptual categories related to CLABSI risk-adjustment, a key measure is the standardized infection ratio (SIR). This value is defined as the ratio of observed number of CLABSI over the expected number of CLABSIs.22 This is the primary measure to stratify hospital performance, and it was used in our assessment of risk-adjustment comprehension. In total, 54 question prompts were developed and subsequently narrowed to 11 study questions for the initial survey.
The instrument was then pretested in a cohort of 8 hospitalists and intensivists to ensure appropriate comprehension, retrieval, and judgment processes.23 Questions were revised based on feedback from this cognitive testing to constitute the final instrument. During the survey, the data table was reshown on each page directly above each question and so was always on the same screen for the respondents.
Survey Sample
We innovated by using Twitter as an online platform for recruiting participants; we used Survey Monkey to host the electronic instrument. Two authors (TJI, VC) systematically sent out solicitation tweets to their followers. These tweets clearly indicated that the recruitment was for the purpose of a research study, and participants would receive no financial reward/incentive (Appendix). A link to the survey was provided in each tweet, and the period of recruitment was 30 days. To ensure respondents were clinicians, they needed to first answer a screening question recognizing that central lines were placed in the subclavian site but not the aorta, iliac, or radial sites.
To prevent systematic or anchoring biases, the order of questions was electronically randomized for each respondent. The primary outcome was the percentage correct of attempted questions.
Statistical Analysis
Descriptive statistics were calculated for all demographic variables. The primary outcome was evaluated as a dichotomous variable for each question (correct vs. incorrect response), and as a continuous variable when assessing mean percent correct on the overall survey. Demographic and conceptual associations were assessed via t-tests, chi-square, or Fisher exact tests. Point biserial correlations were calculated to assess for associations between response to a single question and overall performance on the survey.
To evaluate the association between various respondent characteristics and responses, logistic regression analyses were performed. An ANOVA was performed to assess the association between self-reported reliability of quality metric data and the overall performance on attempted items. Analyses were conducted using STATA MP 14.0 (College Station, TX); P <0.05 was considered statistically significant.
RESULTS
A total of 97 respondents attempted at least 1 question on the survey, and 72 respondents attempted all 11 questions, yielding 939 unique responses for analysis. Seventy respondents (87%) identified as doctors or nurses, and 44 (55%) reported having 6 to 20 years of experience; the survey cohort also came from 6 nations (Table 1). All respondents answered the CLABSI knowledge filter question correctly.
Primary Outcome
The mean percent correct of attempted questions was 61% (standard deviation 21%, interquartile range 50%-75%) (Figure 1). Of those who answered all 11 CLABSI questions, the mean percent correct was 63% (95% CI, 59%-67%). Some questions were answered correctly more often than others—ranging from 17% to 95% (Table 2). Doctors answered 68% of questions correctly (95% CI, 63%-73%), while nurses and other respondents answered 57% of questions correctly (95% CI, 52%-62%) (P = 0.003). Other demographic variables—including self-reported involvement in a quality improvement committee and being from the United States versus elsewhere—were not associated with survey performance. The point biserial correlations for each individual question with overall performance were all more than 0.2 (range 0.24–0.62) and all statistically significant at P < 0.05.
Concept-Specific Performance
Average percent correct declined across categories as numeracy requirements increased (P < 0.05 for all pairwise comparisons). In the area of basic numeracy, respondents’ mean percent correct was 82% (95% CI, 77%-87%) of attempted. This category had 4 questions, with a performance range of 77% to 90%. For example, on the question, “Which hospital has the lowest CLABSI rate?”, 80% of respondents answered correctly. For risk-adjustment numeracy, the mean percent correct was 70% (95% CI, 64%-76%); 2 items assessed this category. For “Which is better: a higher or lower SIR?”, 95% of the cohort answered correctly. However, on “If hospital B had its number of projected infection halved, what is its SIR?”, only 46% of those who attempted the question answered correctly.
Questions featuring risk-adjustment interpretation had an average percent correct of 43% (95% CI, 37%-49%). Five questions made up this category, with a percent correct range of 17% to 75%. For example, on the question, “Which hospital’s patients are the most predisposed to developing CLABSI?”, only 32% of respondents answered this correctly. In contrast, for the question “Which hospital is most effective at preventing CLABSI?”, 51% answered correctly. Figure 2 illustrates the cohort’s performance on each conceptual category while Table 2 displays question-by-question results.
Opinions Regarding CLABSI Data Reliability
Respondents were also asked about their opinion regarding the reliability of CLABSI quality metric data. Forty-three percent of respondents stated that such data were reliable at best 50% of the time. Notably, 10% of respondents indicated that CLABSI quality metric data were rarely or never reliable. There was no association between perceived reliability of quality metric data and survey performance (P = 0.87).
DISCUSSION
This Twitter-based study found wide variation in clinician interpretation of CLABSI quality data, with low overall performance. In particular, comprehension and interpretation of risk-adjusted data were substantially worse than unadjusted data. Although doctors performed somewhat better than nurses and other respondents, those involved in quality improvement initiatives performed no better than respondents who were not. Collectively, these findings suggest clinicians may not reliably comprehend quality metric data, potentially affecting their ability to utilize audit and feedback data. These results may have important implications for policy efforts that seek to leverage quality metric data to improve patient safety.
An integral component of many contemporary quality improvement initiatives is audit and feedback through metrics.6 Unfortunately, formal audit and feedback, along with other similar methods that benchmark data, have not consistently improved outcomes.24–27 A recent meta-analysis noted that audit and feedback interventions are not becoming more efficacious over time; the study further asserted that “new trials have provided little new knowledge regarding key effect modifiers.”9 Our findings suggest that numeracy and comprehension of quality metrics may be important candidate effect modifiers not previously considered. Simply put: we hypothesize that without intrinsic comprehension of data, impetus or insight to change practice might be diminished. In other words, clinicians may be more apt to act on insights they themselves derive from the data than when they are simply told what the data “mean.”
The present study further demonstrates that clinicians do not understand risk-adjusted data as well as raw data. Risk-adjustment has long been recognized as necessary to compare outcomes among hospitals.28,29 However, risk-adjustment is complex and, by its nature, difficult to understand. Although efforts have focused on improving the statistical reliability of quality metrics, this may represent but one half of the equation. Numeracy and interpretation of the data by decision makers are potentially equally important to effecting change. Because clinicians seem to have difficulty understanding risk-adjusted data, this deficit may be of growing importance as our risk-adjustment techniques become more sophisticated.
We note that clinicians expressed concerns regarding the reliability of quality metric feedback. These findings corroborate recent research that has reported reservations from hospital leaders concerning quality data.30,31 However, as shown in the context of patients and healthcare decisions, the aversion associated with quality metrics may be related to incomplete understanding of the data.32 Whether perceptions of unreliability drive lack of understanding or, conversely, whether lack of understanding fuels perceived unreliability is an important question that requires further study.
This study has several strengths. First, we used rigorous survey development techniques to evaluate the understudied issue of quality metric numeracy. Second, our sample size was sufficient to show statistically significant differences in numeracy and comprehension of CLABSI quality metric data. Third, we leveraged social media to rapidly acquire this sample. Finally, our results provided new insights that may have important implications in the area of quality metrics.
There were also limitations to our study. First, the Twitter-derived sample precludes the calculation of a response rate and may not be representative of individuals engaged in CLABSI prevention. However, respondents were solicited from the Twitter-followers of 2 health services researchers (TJI, VC) who are actively engaged in scholarly activities pertaining to critically ill patients and hospital-acquired complications. Thus, our sample likely represents a highly motivated subset that engages in these topics on a regular basis—potentially making them more numerate than average clinicians. Second, we did not ask whether the respondents had previously seen CLABSI data specifically, so we cannot stratify by exposure to such data. Third, this study assessed only CLABSI quality metric data; generalizations regarding numeracy with other metrics should be made with caution. However, as many such data are presented in similar formats, we suspect our findings are applicable to similar audit-and-feedback initiatives.
The findings of this study serve as a stimulus for further inquiry. Research of this nature needs to be carried out in samples drawn from specific, policy-relevant populations (eg, infection control practitioners, bedside nurses, intensive care unit directors). Such studies should include longitudinal assessments of numeracy that attempt to mechanistically examine its impact on CLABSI prevention efforts and outcomes. The latter is an important issue as the link between numeracy and behavioral response, while plausible, cannot be assumed, particularly given the complexity of issues related to behavioral modification.33 Additionally, whether alternate presentations of quality data affect numeracy, interpretation, and performance is worthy of further testing; indeed, this has been shown to be the case in other forms of communication.34–37 Until data from larger samples are available, it may be prudent for quality improvement leaders to assess the comprehension of local clinicians regarding feedback and whether lack of adequate comprehension is a barrier to deploying quality improvement interventions.
Quality measurement is a cornerstone of patient safety as it seeks to assess and improve the care delivered at the bedside. Rigorous metric development is important; however, ensuring that decision makers understand complex quality metrics may be equally fundamental. Given the cost of examining quality, elucidating the mechanisms of numeracy and interpretation as decision makers engage with quality metric data is necessary, along with whether improved comprehension leads to behavior change. Such inquiry may provide an evidence-base to shape alterations in quality metric deployment that will ensure maximal efficacy in driving practice change.
Disclosures
This work was supported by VA HSR&D IIR-13-079 (TJI). Dr. Chopra is supported by a career development award from the Agency of Healthcare Research and Quality (1-K08-HS022835-01). The views expressed here are the authors’ own and do not necessarily represent the view of the US Government or the Department of Veterans’ Affairs. The authors report no conflicts of interest.
1. Scott RD II. The direct medical costs of healthcare-associated infections in us hospitals and the benefits of prevention. Centers for Disease Control and Prevention. Available at: http://www.cdc.gov/HAI/pdfs/hai/Scott_CostPaper.pdf. Published March 2009. Accessed November 8, 2016.
2. O’Grady NP, Alexander M, Burns LA, et al. Guidelines for the prevention of intravascular catheter-related infections. Am J Infect Control. 2011;39(4 suppl 1)::S1-S34. PubMed
3. Blot K, Bergs J, Vogelaers D, Blot S, Vandijck D. Prevention of central line-associated bloodstream infections through quality improvement interventions: a systematic review and meta-analysis. Clin Infect Dis. 2014;59(1):96-105. PubMed
4. Mermel LA. Prevention of intravascular catheter-related infections. Ann Intern Med. 2000;132(5):391-402. PubMed
5. Siempos II, Kopterides P, Tsangaris I, Dimopoulou I, Armaganidis AE. Impact of catheter-related bloodstream infections on the mortality of critically ill patients: a meta-analysis. Crit Care Med. 2009;37(7):2283-2289. PubMed
6. Casalino LP, Gans D, Weber R, et al. US physician practices spend more than $15.4 billion annually to report quality measures. Health Aff (Millwood). 2016;35(3):401-406. PubMed
7. Hysong SJ. Meta-analysis: audit and feedback features impact effectiveness on care quality. Med Care. 2009;47(3):356-363. PubMed
8. Ilgen DR, Fisher CD, Taylor MS. Consequences of individual feedback on behavior in organizations. J Appl Psychol. 1979;64:349-371.
9. Ivers NM, Grimshaw JM, Jamtvedt G, et al. Growing literature, stagnant science? Systematic review, meta-regression and cumulative analysis of audit and feedback interventions in health care. J Gen Intern Med. 2014;29(11):1534-1541. PubMed
10. Rao G. Physician numeracy: essential skills for practicing evidence-based medicine. Fam Med. 2008;40(5):354-358. PubMed
11. Wegwarth O, Schwartz LM, Woloshin S, Gaissmaier W, Gigerenzer G. Do physicians understand cancer screening statistics? A national survey of primary care physicians in the United States. Ann Intern Med. 2012;156(5):340-349. PubMed
12. Bramwell R, West H, Salmon P. Health professionals’ and service users’ interpretation of screening test results: experimental study. BMJ. 2006;333(7562):284. PubMed
13. Agoritsas T, Courvoisier DS, Combescure C, Deom M, Perneger TV. Does prevalence matter to physicians in estimating post-test probability of disease? A randomized trial. J Gen Intern Med. 2011;26(4):373-378. PubMed
14. Warren DK, Zack JE, Mayfield JL, et al. The effect of an education program on the incidence of central venous catheter-associated bloodstream infection in a medical ICU. Chest. 2004;126(5):1612-1618. PubMed
15. Rinke ML, Bundy DG, Chen AR, et al. Central line maintenance bundles and CLABSIs in ambulatory oncology patients. Pediatrics. 2013;132(5):e1403-e1412. PubMed
16. Pronovost P, Needham D, Berenholtz S, et al. An intervention to decrease catheter-related bloodstream infections in the ICU. N Engl J Med. 2006;355(26):
2725-2732. PubMed
17. Rinke ML, Chen AR, Bundy DG, et al. Implementation of a central line maintenance care bundle in hospitalized pediatric oncology patients. Pediatrics. 2012;130(4):e996-e1004. PubMed
18. Sacks GD, Diggs BS, Hadjizacharia P, Green D, Salim A, Malinoski DJ. Reducing the rate of catheter-associated bloodstream infections in a surgical intensive care unit using the Institute for Healthcare Improvement Central Line Bundle. Am J Surg. 2014;207(6):817-823. PubMed
19. Berenholtz SM, Pronovost PJ, Lipsett PA, et al. Eliminating catheter-related bloodstream infections in the intensive care unit. Crit Care Med. 2004;32(10):2014-2020. PubMed
20. Rajwan YG, Barclay PW, Lee T, Sun IF, Passaretti C, Lehmann H. Visualizing central line-associated blood stream infection (CLABSI) outcome data for decision making by health care consumers and practitioners—an evaluation study. Online J Public Health Inform. 2013;5(2):218. PubMed
21. Fagerlin A, Zikmund-Fisher BJ, Ubel PA, Jankovic A, Derry HA, Smith DM. Measuring numeracy without a math test: development of the Subjective Numeracy Scale. Med Decis Making 2007;27(5):672-680. PubMed
22. HAI progress report FAQ. 2016. Available at: http://www.cdc.gov/hai/surveillance/progress-report/faq.html. Last updated March 2, 2016. Accessed November 8, 2016.
23. Collins D. Pretesting survey instruments: an overview of cognitive methods. Qual Life Res. 2003;12(3):229-238. PubMed
24. Ivers N, Jamtvedt G, Flottorp S, et al. Audit and feedback: effects on professional practice and healthcare outcomes. Cochrane Database Syst Rev. 2012;(6):CD000259. PubMed
25. Chatterjee P, Joynt KE. Do cardiology quality measures actually improve patient outcomes? J Am Heart Assoc. 2014;3(1):e000404. PubMed
26. Joynt KE, Blumenthal DM, Orav EJ, Resnic FS, Jha AK. Association of public reporting for percutaneous coronary intervention with utilization and outcomes among Medicare beneficiaries with acute myocardial infarction. JAMA. 2012;308(14):1460-1468. PubMed
27. Ryan AM, Nallamothu BK, Dimick JB. Medicare’s public reporting initiative on hospital quality had modest or no impact on mortality from three key conditions. Health Aff (Millwood). 2012;31(3):585-592. PubMed
28. Thomas JW. Risk adjustment for measuring health care outcomes, 3rd edition. Int J Qual Health Care. 2004;16(2):181-182.
29. Iezzoni LI. Risk Adjustment for Measuring Health Care Outcomes. Ann Arbor, Michigan: Health Administration Press; 1994.
30. Goff SL, Lagu T, Pekow PS, et al. A qualitative analysis of hospital leaders’ opinions about publicly reported measures of health care quality. Jt Comm J Qual Patient Saf. 2015;41(4):169-176. PubMed
31. Lindenauer PK, Lagu T, Ross JS, et al. Attitudes of hospital leaders toward publicly reported measures of health care quality. JAMA Intern Med. 2014;174(12):
1904-1911. PubMed
32. Peters E, Hibbard J, Slovic P, Dieckmann N. Numeracy skill and the communication, comprehension, and use of risk-benefit information. Health Aff (Millwood). 2007;26(3):741-748. PubMed
33. Montano DE, Kasprzyk D. Theory of reasoned action, theory of planned behavior, and the integrated behavioral model. In: Glanz K, Rimer BK, Viswanath K, eds. Health Behavior and Health Education: Theory, Research and Practice. 5th ed. San Francisco, CA: Jossey-Bass; 2015:95–124.
34. Hamstra DA, Johnson SB, Daignault S, et al. The impact of numeracy on verbatim knowledge of the longitudinal risk for prostate cancer recurrence following radiation therapy. Med Decis Making. 2015;35(1):27-36. PubMed
35. Hawley ST, Zikmund-Fisher B, Ubel P, Jancovic A, Lucas T, Fagerlin A. The impact of the format of graphical presentation on health-related knowledge and treatment choices. Patient Educ Couns. 2008;73(3):448-455. PubMed
36. Zikmund-Fisher BJ, Witteman HO, Dickson M, et al. Blocks, ovals, or people? Icon type affects risk perceptions and recall of pictographs. Med Decis Making. 2014;34(4):443-453. PubMed
37. Korfage IJ, Fuhrel-Forbis A, Ubel PA, et al. Informed choice about breast cancer prevention: randomized controlled trial of an online decision aid intervention. Breast Cancer Res. 2013;15(5):R74. PubMed
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2. O’Grady NP, Alexander M, Burns LA, et al. Guidelines for the prevention of intravascular catheter-related infections. Am J Infect Control. 2011;39(4 suppl 1)::S1-S34. PubMed
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6. Casalino LP, Gans D, Weber R, et al. US physician practices spend more than $15.4 billion annually to report quality measures. Health Aff (Millwood). 2016;35(3):401-406. PubMed
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14. Warren DK, Zack JE, Mayfield JL, et al. The effect of an education program on the incidence of central venous catheter-associated bloodstream infection in a medical ICU. Chest. 2004;126(5):1612-1618. PubMed
15. Rinke ML, Bundy DG, Chen AR, et al. Central line maintenance bundles and CLABSIs in ambulatory oncology patients. Pediatrics. 2013;132(5):e1403-e1412. PubMed
16. Pronovost P, Needham D, Berenholtz S, et al. An intervention to decrease catheter-related bloodstream infections in the ICU. N Engl J Med. 2006;355(26):
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17. Rinke ML, Chen AR, Bundy DG, et al. Implementation of a central line maintenance care bundle in hospitalized pediatric oncology patients. Pediatrics. 2012;130(4):e996-e1004. PubMed
18. Sacks GD, Diggs BS, Hadjizacharia P, Green D, Salim A, Malinoski DJ. Reducing the rate of catheter-associated bloodstream infections in a surgical intensive care unit using the Institute for Healthcare Improvement Central Line Bundle. Am J Surg. 2014;207(6):817-823. PubMed
19. Berenholtz SM, Pronovost PJ, Lipsett PA, et al. Eliminating catheter-related bloodstream infections in the intensive care unit. Crit Care Med. 2004;32(10):2014-2020. PubMed
20. Rajwan YG, Barclay PW, Lee T, Sun IF, Passaretti C, Lehmann H. Visualizing central line-associated blood stream infection (CLABSI) outcome data for decision making by health care consumers and practitioners—an evaluation study. Online J Public Health Inform. 2013;5(2):218. PubMed
21. Fagerlin A, Zikmund-Fisher BJ, Ubel PA, Jankovic A, Derry HA, Smith DM. Measuring numeracy without a math test: development of the Subjective Numeracy Scale. Med Decis Making 2007;27(5):672-680. PubMed
22. HAI progress report FAQ. 2016. Available at: http://www.cdc.gov/hai/surveillance/progress-report/faq.html. Last updated March 2, 2016. Accessed November 8, 2016.
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24. Ivers N, Jamtvedt G, Flottorp S, et al. Audit and feedback: effects on professional practice and healthcare outcomes. Cochrane Database Syst Rev. 2012;(6):CD000259. PubMed
25. Chatterjee P, Joynt KE. Do cardiology quality measures actually improve patient outcomes? J Am Heart Assoc. 2014;3(1):e000404. PubMed
26. Joynt KE, Blumenthal DM, Orav EJ, Resnic FS, Jha AK. Association of public reporting for percutaneous coronary intervention with utilization and outcomes among Medicare beneficiaries with acute myocardial infarction. JAMA. 2012;308(14):1460-1468. PubMed
27. Ryan AM, Nallamothu BK, Dimick JB. Medicare’s public reporting initiative on hospital quality had modest or no impact on mortality from three key conditions. Health Aff (Millwood). 2012;31(3):585-592. PubMed
28. Thomas JW. Risk adjustment for measuring health care outcomes, 3rd edition. Int J Qual Health Care. 2004;16(2):181-182.
29. Iezzoni LI. Risk Adjustment for Measuring Health Care Outcomes. Ann Arbor, Michigan: Health Administration Press; 1994.
30. Goff SL, Lagu T, Pekow PS, et al. A qualitative analysis of hospital leaders’ opinions about publicly reported measures of health care quality. Jt Comm J Qual Patient Saf. 2015;41(4):169-176. PubMed
31. Lindenauer PK, Lagu T, Ross JS, et al. Attitudes of hospital leaders toward publicly reported measures of health care quality. JAMA Intern Med. 2014;174(12):
1904-1911. PubMed
32. Peters E, Hibbard J, Slovic P, Dieckmann N. Numeracy skill and the communication, comprehension, and use of risk-benefit information. Health Aff (Millwood). 2007;26(3):741-748. PubMed
33. Montano DE, Kasprzyk D. Theory of reasoned action, theory of planned behavior, and the integrated behavioral model. In: Glanz K, Rimer BK, Viswanath K, eds. Health Behavior and Health Education: Theory, Research and Practice. 5th ed. San Francisco, CA: Jossey-Bass; 2015:95–124.
34. Hamstra DA, Johnson SB, Daignault S, et al. The impact of numeracy on verbatim knowledge of the longitudinal risk for prostate cancer recurrence following radiation therapy. Med Decis Making. 2015;35(1):27-36. PubMed
35. Hawley ST, Zikmund-Fisher B, Ubel P, Jancovic A, Lucas T, Fagerlin A. The impact of the format of graphical presentation on health-related knowledge and treatment choices. Patient Educ Couns. 2008;73(3):448-455. PubMed
36. Zikmund-Fisher BJ, Witteman HO, Dickson M, et al. Blocks, ovals, or people? Icon type affects risk perceptions and recall of pictographs. Med Decis Making. 2014;34(4):443-453. PubMed
37. Korfage IJ, Fuhrel-Forbis A, Ubel PA, et al. Informed choice about breast cancer prevention: randomized controlled trial of an online decision aid intervention. Breast Cancer Res. 2013;15(5):R74. PubMed
© 2017 Society of Hospital Medicine
Mobilization in Severe Sepsis
Severe sepsis, defined as an infection leading to systemic inflammatory response and acute organ dysfunction, is a significant cause of morbidity and mortality.[1, 2, 3] Although it has been a condition classically attributed to patients in the intensive care unit (ICU), accumulating data suggest that a substantial proportion of patients with severe sepsis are managed by hospitalists and floor teams in non‐ICU, general ward settings.[1, 4, 5] Although the incidence of severe sepsis continues to rise both in the United States and other developed nations,[2, 6, 7] advances in early recognition, management, and care of this condition have resulted in improved rates of survival.[8] The resultant increase in a severe sepsis survivor population[6] make the long‐term sequelae of this condition an important public health problem.[9]
In both the ICU and on general wards, severe sepsis survivors suffer from decreased functional status, worsened quality of life, increased cognitive dysfunction, and sarcopenia.[4, 6, 10, 11, 12, 13, 14] Not surprisingly, many such patients are discharged to long‐term care facilities for physical rehabilitation,[15] with escalating utilization of resources[16] and cost.[17, 18] Inexpensive interventions that improve outcomes following sepsis would thus be welcomed.
It is well known that physical therapy (PT) and early mobilization are beneficial in mitigating functional decline in a number of conditions.[19, 20, 21, 22] PT can improve outcomes in several ways: prevention of bed rest deconditioning, mitigation of mechanisms that lead to sarcopenia, increased pulmonary and tissue aerobic capacity, and improved sense of well‐being. Indeed, among the population cared for in ICU settings, early mobility and PT lead to more ventilator‐free days, better functional status at discharge, shorter duration of delirium, and even a potentially reduced risk of central line‐associated bloodstream infection (CLABSI).[23, 24] However, whether initiating early PT can improve outcomes in patients with severe sepsis treated by either intensivists or hospitalists/floor teams outside the ICU is unknown.
Therefore, to better understand this phenomenon, we systematically reviewed and integrated the literature regarding early mobilization and PT for severe sepsis outside the ICU. To be more inclusive, a secondary review including populations with any infectious etiology and severe sepsis treated within the ICU was also conducted. Our review begins by providing an overview of the pathophysiology behind functional decline in severe sepsis, along with existing evidence on early mobilization efficacy in other patient populations. We then proceed with a review of the extant literature on the aforementioned topic. We conclude with an evaluation of the current evidence on the subject, along with assertions regarding future research in the area.
PATHOPHYSIOLOGY OF DISABILITY FOLLOWING HOSPITALIZATION FOR SEVERE SEPSIS
The pathophysiology behind functional decline in patients hospitalized with severe sepsis is multifactorial (Figure 1). During hospitalization, it is well known that patients suffer from restricted mobility,[25] and that this impediment is linked to poor functional outcomes.[26] Described as far back as Hippocrates,[27] more recent studies have elucidated how prolonged bed rest leads to a multitude of physiological changes that promote deconditioning.[28] Specifically, skeletal muscle atrophy and decreased protein synthesis, independent of ongoing disease processes and acute illness, have been demonstrated in both animal and human models of prolonged inactivity.[29, 30] Additionally, bed rest leading to insensible fluid losses, a decline in stroke volume and effective cardiac output, bone loss, and decreased insulin sensitivity has been reported.[28, 31] There is little doubt that the aforementioned issues pertain to severe sepsis patients outside the ICU. In fact, nearly all of the acute mechanisms driving Creditor's hazards of hospitalization are noted among patients with severe sepsis.[32]
Furthermore, several factors preceding hospitalization may increase risk of disability. For example, Covinsky et al. described a number of risk factors, such as comorbid conditions, cognitive impairment, and various psychosocial aspects such as depression and limited social support, as being associated with increased risk of functional decline.[33] Thus, both in‐hospital and prehospital factors likely combine within an individual patient's context to determine risk of physical decline.
On this backdrop and the inherent immobilization associated with hospitalization, sepsis and inflammation catalyze physiologic changes that further propagate deconditioning.[7] Implicated pathways and proteins for this process include the mammalian target of rapamycin, human growth hormone, insulin‐like growth factors, interleukin‐1, and tumor necrosis factor‐. Through several metabolic alterations, sepsis independently promotes skeletal muscle breakdown and impairs skeletal muscle synthesis.[34, 35, 36] Inflammation associated with sepsis also increases oxidant burden, further leading to muscle dysfunction and dysregulation.[7, 31, 37, 38]
EFFECTS OF PHYSICAL THERAPY AND MOBILIZATION ON CLINICAL OUTCOMES
In patients with nonsepsis conditions who are at risk for functional decline, the effectiveness of physical therapy has been studied in multiple settings with positive outcomes. For example, in hospitalized elderly patients with general deconditioning, PT‐based interventions have demonstrated reductions in length of hospital stay.[39] Additionally, exercise in healthy subjects who have been subjected to bed rest has been shown to attenuate physiological changes, and maintain plasma and red cell volume and work capacity.[40] Adequate safety and improved outcomes have also been demonstrated in the general population of critically ill patients who receive early PT and mobilization. Improved functional capacity at discharge, decreases in duration of delirium, increased ventilator‐free days, decreased risk for CLABSI, and a better general sense of well‐being following these interventions have been widely reported in the literature.[14, 19, 23, 24, 41, 42, 43, 44, 45] Interestingly, critically ill patients may have a dose‐ and time‐dependent response to PT; that is, high intensity and early onset mobility‐based interventions are often associated with more ventilator‐free time and improved functional outcomes, resulting in shorter ICU and hospital length of stay.[42, 46, 47, 48]
Moderate intensity exercise has also been shown to improve 6‐minute walking distance in patients convalescing from coronary artery bypass grafting surgery.[49] Furthermore, in the postoperative setting, patients suffering traumatic hip fractures are known to benefit from physical and occupational therapies with shorter time to ambulation and improved locomotion in the recovery period.[21, 50, 51] Among patients with stroke, PT and gait training has led to improvements in speed, gait, independence during walking, activities of daily living, and extended activities of daily living.[52, 53, 54] A recent meta‐analysis also suggested that extra PT compared to regular treatment in patients with acute and subacute conditions such as stroke and postoperative states improved mobility and quality of life, while reducing length of hospital stay.[22]
Although this evidence suggests potential benefits for PT and mobilization, it is important to note that the effect of these treatments in dissimilar populations is unknown and may not necessarily be positive. For example, a recent study examining PT and its impact on patients with hip osteoarthritis showed no clinical benefit.[55] Mobilizing patients in severe illness may be associated with important risks, including falls, worsening of their clinical status, or moral discouragement in the setting of limited capacity. Therefore, understanding which elements of mobilization efforts create the greatest impact in the context of delivery of the intervention is critical to assessing the risk, benefit, and efficacy of PT‐based interventions.
EARLY PHYSICAL THERAPY FOR SEVERE SEPSIS OUTSIDE THE ICU: LITERATURE REVIEW
Given the functional decline associated with severe sepsis and the evidence of PT efficacy in other populations, we reviewed the current literature for studies evaluating physical therapy in severe sepsis patients outside the ICU. With the assistance of medical reference librarians, we searched MEDLINE via PubMed (1950present), EMBASE (1946present), Cochrane CENTRAL Register of Controlled Trials, and the Cochrane Database of Reviews of Effectiveness (1960present via Ovid). The search was last updated in June 2014.
We searched for studies that (1) involved human patients 18 years of age, (2) included patients with a primary diagnosis of sepsis or severe sepsis being treated outside the ICU, (3) featured a primary intervention that included PT or an early mobilization‐based initiative, and (4) reported a primary clinical or functional outcome of interest. Early was defined based on the included studies' definition. To be fully inclusive, we also conducted a secondary review with inclusion criteria expanded to studies of either any infectious pathology or severe sepsis patient in the ICU that employed PT interventions.
Our electronic search retrieved 815 records (Figure 2). Despite this approach, no publications met our primary inclusion criteria as we found no study that implemented a mobility intervention directed toward patients with sepsis treated outside the ICU. Our expanded secondary review included patients with any infectious pathology or those with severe sepsis in the ICU treated with PT; in this review, 2 studies met eligibility criteria.[56] In a 2003 cluster‐randomized trial, Mundy and colleagues randomized patients admitted with pneumonia to receive early PT or usual care. The outcomes of interest were hospital length of stay, mortality, number of chest radiographs, emergency department visits, and readmissions at 30 and 90 days after hospital admission. Although the study has important limitations (including patient‐level difference between trial arms, subjective definition of early mobilization), the authors found a significant decrease in length of stay among patients with pneumonia who received early PT compared to controls (5.8 vs 6.9 days, absolute difference 1.1 days, 95% confidence interval: 02.2 days). The study also reported a substantial decrease in adjusted mean hospital charges for the early mobilization group versus the usual care group ($10,159 per patient vs. $12,868 per patient, P=0.05). In the second study, Sossdorf et al. retrospectively evaluated a cohort of 999 patients with severe sepsis and septic shock and assessed whether onset and frequency of PT‐based interventions was associated with clinical benefit. After multivariate analysis, the authors reported a small mortality benefit associated with the relative number of PT interventions (hazard ratio: 0.982, P<0.001).[45]
EXPLAINING THE VOID
Our integrative review of the current literature reveals a gap in our understanding of the role of early mobilization in severe sepsis both within and beyond the ICU. Given the promise of PT‐based interventions and the toll of severe sepsis, one must ask: why may this be so?
First, the understanding that severe sepsis leads to significant, long‐term consequences for survivors has only been identified recently. Thus, it is possible that the burden and consequences related to this condition have not been fully recognized in clinical settings, leading to a paucity of research and interventions. Although the association between sepsis and mortality has been known since the 1990s,[57] long‐term complications and enduring morbidity of this disease continue to be realized. Indeed, many studies delineating the longer‐term effects of sepsis have been only recently published.[6, 10, 11, 12, 13]
Second, it is likely that many clinicians ascribe to the viewpoint that severe sepsis is an ICU‐only condition, a myth that has been discounted by multiple studies.[1, 4, 5] Although our study shows a paucity of evidence in both ICU and nonICU‐based severe sepsis, almost half of severe sepsis occurs outside the ICU, carrying with it many of the same clinical implications. Additionally, increased morbidity, mortality, and resource utilization are known to be true in all patients with severe sepsis, irrespective of where they receive treatment in the hospital.[4, 5, 6] Recent evidence has also shown that severe sepsis treated on the floor may be clinically, epidemiologically, and even prognostically unique from its ICU counterpart.[5, 58, 59] Therefore, it appears that research domains with tailored interventions to both ICU and non‐ICU severe sepsis patients are important areas of inquiry for clinicians. Such research may serve the purpose of assessing impact of early mobilization and unmasking any treatment heterogeneity that may exist when dealing with severe sepsis. Though trials of PT in ICU‐based severe sepsis are underway,[60] it is prudent that these also extend beyond the ICU‐setting.
Third, variability in early mobility practices and billing documentation for severe sepsis patients may exist, adding barriers to performing high‐quality research on this topic. In fact, administrative billing records for PT may offer insufficient granularity about services provided or therapies administered, particularly in the ICU where variability in early mobilization practices have been shown despite common employment of physiotherapists.[61]
Finally, many hospitalists may believe that patients with severe sepsis are simply too sick for early mobilization or PT, possibly limiting their participation in clinical or research‐based interventions. This perception has been well described in ICU populations, where it has been well studied and shown to be false.[41, 42, 43] Nevertheless, if severe sepsis patients are viewed as relatively sick hospitalized patients, it is plausible that resistance against early mobilization interventions may exist.[62] Understanding these biases and being mindful of such barriers when conducting studies in this area would be important.
CONCLUSION AND FUTURE DIRECTIONS
The cost burdens of severe sepsis are substantial. Elixhauser et al. suggest that it is currently the single most expensive cause of acute hospitalization in the United States.[63] Importantly, a large proportion of patients with severe sepsis receive care from hospitalists and/or floor teams on the general wards. Our integrative review has demonstrated a knowledge gap when it comes to rigorous assessments of PT and mobilization treatments in patients with severe sepsis within and beyond the ICU. Existing evidence provides a strong rationale for why functional decline occurs in patients with severe sepsis. A reasonable argument for PT‐based interventions to mitigate functional decline in this subset exists, but rigorous evaluation of such interventions is necessary. Physical and mobilization‐based treatments are routinely available and efficacious in several other settings and populations. It could be rapidly deployed and potentially improve outcomes in those with severe sepsis. Research would be welcomed to establish optimal dosing, efficacy, and cost effectiveness of PT and early mobilization for severe sepsis, particularly in patients treated on the general wards by hospitalists and floor teams.
How may such a research agenda be launched? A balanced multipronged approach is necessary. First, large‐scale epidemiological data to understand variation in practice are needed. Focused studies carried out by community and academic hospitalists on septic patients treated outside the ICU are the call of the hour. These data, in turn, can help create registries that assess for risk factors, quality of treatment, and long‐term outcomes among survivors of this condition. Second, evaluation and improvement of the coding and precision of physical and occupational therapy billing records is necessary so that their added value can be assessed and tracked using administrative data. Third, targeted prospective studies and clinical trials to directly evaluate the effect of PT in well‐defined patient populations with sepsis outside the ICU are needed. In this arena, hospitalist expertise and trained physical therapists will be crucial. The focus of this work should be directed toward both short‐term and long‐term functional outcomes, as well as mortality and morbidity assessments. Fourth, these patient‐centered efforts should loop back and inform the foundational biology of severe sepsis, thus illuminating patient‐centered end points, from biomarker analysis to physiometric measurements in basic and translational research.
In conclusion, this review sheds light on the fact that interventions that may mitigate the functional and cognitive decline in survivors of severe sepsis appear underdeveloped. Although the precise benefit of such interventions remains unclear, the low‐cost, widespread availability and generalizability of PT‐based interventions make it a worthy candidate for future research. As the numbers of survivors of sepsis expand, an unmet public health need for interventions to improve the long‐term outcomes of this population exists. Hospitalists and intensivists caring for severe sepsis patients must rise to meet this need. Together, we can help improve the lives of patients afflicted with severe sepsis, wherever they may receive care in the hospital.
Acknowledgements
The authors acknowledge the efforts of medical research librarians Andy Hickner, MSI, and Marissa Conte, MSI, on this project.
Disclosures
This work was supported by the National Institutes of HealthK08, HL091249 (T.J.I.) and VA HSR&D IIR‐11109 (T.J.I.). The views expressed here are the authors' own and do not necessarily represent the views of the US government or the Department of Veterans' Affairs. The authors report no conflicts of interest.
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- , , , et al. Effects of augmented exercise therapy on outcome of gait and gait‐related activities in the first 6 months after stroke: a meta‐analysis. Stroke. 2011;42:3311–3315.
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- , , , et al. Effect of physical therapy on pain and function in patients with hip osteoarthritis: a randomized clinical trial. JAMA. 2014;311:1987–1997.
- , , , et al. Early mobilization of patients hospitalized with community‐acquired pneumonia. Chest. 2003;124:883–889.
- , , , et al. Magnitude and duration of the effect of sepsis on survival. Department of Veterans Affairs Systemic Sepsis Cooperative Studies Group. JAMA. 1997;277:1058–1063.
- , , , et al. Epidemiology of sepsis in Victoria, Australia. Crit Care Med. 2005;33:71–80.
- , , , et al. Sepsis incidence and outcome: contrasting the intensive care unit with the hospital ward. Crit Care Med. 2007;35:1284–1289.
- , , . Early rehabilitation in sepsis: a prospective randomised controlled trial investigating functional and physiological outcomes The i‐PERFORM Trial (Protocol Article). BMC Anesthesiol. 2011;11:21.
- , , , et al. TEAM: a prospective multi‐centre cohort study of early activity and mobilisation in ICU. In: American Thoracic Society 2013 International Conference; May 17–22, 2013; Philadelphia, PA. Am J Respir Crit Care Med. 2013;187:A3625.
- , , , et al. Improving long‐term outcomes after discharge from intensive care unit: report from a stakeholders' conference. Crit Care Med. 2012;40:502–509.
- , , . Septicemia in U.S. hospitals, 2009: statistical brief #122. Healthcare Cost and Utilization Project (HCUP) Statistical Briefs. Rockville, MD; 2006.
Severe sepsis, defined as an infection leading to systemic inflammatory response and acute organ dysfunction, is a significant cause of morbidity and mortality.[1, 2, 3] Although it has been a condition classically attributed to patients in the intensive care unit (ICU), accumulating data suggest that a substantial proportion of patients with severe sepsis are managed by hospitalists and floor teams in non‐ICU, general ward settings.[1, 4, 5] Although the incidence of severe sepsis continues to rise both in the United States and other developed nations,[2, 6, 7] advances in early recognition, management, and care of this condition have resulted in improved rates of survival.[8] The resultant increase in a severe sepsis survivor population[6] make the long‐term sequelae of this condition an important public health problem.[9]
In both the ICU and on general wards, severe sepsis survivors suffer from decreased functional status, worsened quality of life, increased cognitive dysfunction, and sarcopenia.[4, 6, 10, 11, 12, 13, 14] Not surprisingly, many such patients are discharged to long‐term care facilities for physical rehabilitation,[15] with escalating utilization of resources[16] and cost.[17, 18] Inexpensive interventions that improve outcomes following sepsis would thus be welcomed.
It is well known that physical therapy (PT) and early mobilization are beneficial in mitigating functional decline in a number of conditions.[19, 20, 21, 22] PT can improve outcomes in several ways: prevention of bed rest deconditioning, mitigation of mechanisms that lead to sarcopenia, increased pulmonary and tissue aerobic capacity, and improved sense of well‐being. Indeed, among the population cared for in ICU settings, early mobility and PT lead to more ventilator‐free days, better functional status at discharge, shorter duration of delirium, and even a potentially reduced risk of central line‐associated bloodstream infection (CLABSI).[23, 24] However, whether initiating early PT can improve outcomes in patients with severe sepsis treated by either intensivists or hospitalists/floor teams outside the ICU is unknown.
Therefore, to better understand this phenomenon, we systematically reviewed and integrated the literature regarding early mobilization and PT for severe sepsis outside the ICU. To be more inclusive, a secondary review including populations with any infectious etiology and severe sepsis treated within the ICU was also conducted. Our review begins by providing an overview of the pathophysiology behind functional decline in severe sepsis, along with existing evidence on early mobilization efficacy in other patient populations. We then proceed with a review of the extant literature on the aforementioned topic. We conclude with an evaluation of the current evidence on the subject, along with assertions regarding future research in the area.
PATHOPHYSIOLOGY OF DISABILITY FOLLOWING HOSPITALIZATION FOR SEVERE SEPSIS
The pathophysiology behind functional decline in patients hospitalized with severe sepsis is multifactorial (Figure 1). During hospitalization, it is well known that patients suffer from restricted mobility,[25] and that this impediment is linked to poor functional outcomes.[26] Described as far back as Hippocrates,[27] more recent studies have elucidated how prolonged bed rest leads to a multitude of physiological changes that promote deconditioning.[28] Specifically, skeletal muscle atrophy and decreased protein synthesis, independent of ongoing disease processes and acute illness, have been demonstrated in both animal and human models of prolonged inactivity.[29, 30] Additionally, bed rest leading to insensible fluid losses, a decline in stroke volume and effective cardiac output, bone loss, and decreased insulin sensitivity has been reported.[28, 31] There is little doubt that the aforementioned issues pertain to severe sepsis patients outside the ICU. In fact, nearly all of the acute mechanisms driving Creditor's hazards of hospitalization are noted among patients with severe sepsis.[32]
Furthermore, several factors preceding hospitalization may increase risk of disability. For example, Covinsky et al. described a number of risk factors, such as comorbid conditions, cognitive impairment, and various psychosocial aspects such as depression and limited social support, as being associated with increased risk of functional decline.[33] Thus, both in‐hospital and prehospital factors likely combine within an individual patient's context to determine risk of physical decline.
On this backdrop and the inherent immobilization associated with hospitalization, sepsis and inflammation catalyze physiologic changes that further propagate deconditioning.[7] Implicated pathways and proteins for this process include the mammalian target of rapamycin, human growth hormone, insulin‐like growth factors, interleukin‐1, and tumor necrosis factor‐. Through several metabolic alterations, sepsis independently promotes skeletal muscle breakdown and impairs skeletal muscle synthesis.[34, 35, 36] Inflammation associated with sepsis also increases oxidant burden, further leading to muscle dysfunction and dysregulation.[7, 31, 37, 38]
EFFECTS OF PHYSICAL THERAPY AND MOBILIZATION ON CLINICAL OUTCOMES
In patients with nonsepsis conditions who are at risk for functional decline, the effectiveness of physical therapy has been studied in multiple settings with positive outcomes. For example, in hospitalized elderly patients with general deconditioning, PT‐based interventions have demonstrated reductions in length of hospital stay.[39] Additionally, exercise in healthy subjects who have been subjected to bed rest has been shown to attenuate physiological changes, and maintain plasma and red cell volume and work capacity.[40] Adequate safety and improved outcomes have also been demonstrated in the general population of critically ill patients who receive early PT and mobilization. Improved functional capacity at discharge, decreases in duration of delirium, increased ventilator‐free days, decreased risk for CLABSI, and a better general sense of well‐being following these interventions have been widely reported in the literature.[14, 19, 23, 24, 41, 42, 43, 44, 45] Interestingly, critically ill patients may have a dose‐ and time‐dependent response to PT; that is, high intensity and early onset mobility‐based interventions are often associated with more ventilator‐free time and improved functional outcomes, resulting in shorter ICU and hospital length of stay.[42, 46, 47, 48]
Moderate intensity exercise has also been shown to improve 6‐minute walking distance in patients convalescing from coronary artery bypass grafting surgery.[49] Furthermore, in the postoperative setting, patients suffering traumatic hip fractures are known to benefit from physical and occupational therapies with shorter time to ambulation and improved locomotion in the recovery period.[21, 50, 51] Among patients with stroke, PT and gait training has led to improvements in speed, gait, independence during walking, activities of daily living, and extended activities of daily living.[52, 53, 54] A recent meta‐analysis also suggested that extra PT compared to regular treatment in patients with acute and subacute conditions such as stroke and postoperative states improved mobility and quality of life, while reducing length of hospital stay.[22]
Although this evidence suggests potential benefits for PT and mobilization, it is important to note that the effect of these treatments in dissimilar populations is unknown and may not necessarily be positive. For example, a recent study examining PT and its impact on patients with hip osteoarthritis showed no clinical benefit.[55] Mobilizing patients in severe illness may be associated with important risks, including falls, worsening of their clinical status, or moral discouragement in the setting of limited capacity. Therefore, understanding which elements of mobilization efforts create the greatest impact in the context of delivery of the intervention is critical to assessing the risk, benefit, and efficacy of PT‐based interventions.
EARLY PHYSICAL THERAPY FOR SEVERE SEPSIS OUTSIDE THE ICU: LITERATURE REVIEW
Given the functional decline associated with severe sepsis and the evidence of PT efficacy in other populations, we reviewed the current literature for studies evaluating physical therapy in severe sepsis patients outside the ICU. With the assistance of medical reference librarians, we searched MEDLINE via PubMed (1950present), EMBASE (1946present), Cochrane CENTRAL Register of Controlled Trials, and the Cochrane Database of Reviews of Effectiveness (1960present via Ovid). The search was last updated in June 2014.
We searched for studies that (1) involved human patients 18 years of age, (2) included patients with a primary diagnosis of sepsis or severe sepsis being treated outside the ICU, (3) featured a primary intervention that included PT or an early mobilization‐based initiative, and (4) reported a primary clinical or functional outcome of interest. Early was defined based on the included studies' definition. To be fully inclusive, we also conducted a secondary review with inclusion criteria expanded to studies of either any infectious pathology or severe sepsis patient in the ICU that employed PT interventions.
Our electronic search retrieved 815 records (Figure 2). Despite this approach, no publications met our primary inclusion criteria as we found no study that implemented a mobility intervention directed toward patients with sepsis treated outside the ICU. Our expanded secondary review included patients with any infectious pathology or those with severe sepsis in the ICU treated with PT; in this review, 2 studies met eligibility criteria.[56] In a 2003 cluster‐randomized trial, Mundy and colleagues randomized patients admitted with pneumonia to receive early PT or usual care. The outcomes of interest were hospital length of stay, mortality, number of chest radiographs, emergency department visits, and readmissions at 30 and 90 days after hospital admission. Although the study has important limitations (including patient‐level difference between trial arms, subjective definition of early mobilization), the authors found a significant decrease in length of stay among patients with pneumonia who received early PT compared to controls (5.8 vs 6.9 days, absolute difference 1.1 days, 95% confidence interval: 02.2 days). The study also reported a substantial decrease in adjusted mean hospital charges for the early mobilization group versus the usual care group ($10,159 per patient vs. $12,868 per patient, P=0.05). In the second study, Sossdorf et al. retrospectively evaluated a cohort of 999 patients with severe sepsis and septic shock and assessed whether onset and frequency of PT‐based interventions was associated with clinical benefit. After multivariate analysis, the authors reported a small mortality benefit associated with the relative number of PT interventions (hazard ratio: 0.982, P<0.001).[45]
EXPLAINING THE VOID
Our integrative review of the current literature reveals a gap in our understanding of the role of early mobilization in severe sepsis both within and beyond the ICU. Given the promise of PT‐based interventions and the toll of severe sepsis, one must ask: why may this be so?
First, the understanding that severe sepsis leads to significant, long‐term consequences for survivors has only been identified recently. Thus, it is possible that the burden and consequences related to this condition have not been fully recognized in clinical settings, leading to a paucity of research and interventions. Although the association between sepsis and mortality has been known since the 1990s,[57] long‐term complications and enduring morbidity of this disease continue to be realized. Indeed, many studies delineating the longer‐term effects of sepsis have been only recently published.[6, 10, 11, 12, 13]
Second, it is likely that many clinicians ascribe to the viewpoint that severe sepsis is an ICU‐only condition, a myth that has been discounted by multiple studies.[1, 4, 5] Although our study shows a paucity of evidence in both ICU and nonICU‐based severe sepsis, almost half of severe sepsis occurs outside the ICU, carrying with it many of the same clinical implications. Additionally, increased morbidity, mortality, and resource utilization are known to be true in all patients with severe sepsis, irrespective of where they receive treatment in the hospital.[4, 5, 6] Recent evidence has also shown that severe sepsis treated on the floor may be clinically, epidemiologically, and even prognostically unique from its ICU counterpart.[5, 58, 59] Therefore, it appears that research domains with tailored interventions to both ICU and non‐ICU severe sepsis patients are important areas of inquiry for clinicians. Such research may serve the purpose of assessing impact of early mobilization and unmasking any treatment heterogeneity that may exist when dealing with severe sepsis. Though trials of PT in ICU‐based severe sepsis are underway,[60] it is prudent that these also extend beyond the ICU‐setting.
Third, variability in early mobility practices and billing documentation for severe sepsis patients may exist, adding barriers to performing high‐quality research on this topic. In fact, administrative billing records for PT may offer insufficient granularity about services provided or therapies administered, particularly in the ICU where variability in early mobilization practices have been shown despite common employment of physiotherapists.[61]
Finally, many hospitalists may believe that patients with severe sepsis are simply too sick for early mobilization or PT, possibly limiting their participation in clinical or research‐based interventions. This perception has been well described in ICU populations, where it has been well studied and shown to be false.[41, 42, 43] Nevertheless, if severe sepsis patients are viewed as relatively sick hospitalized patients, it is plausible that resistance against early mobilization interventions may exist.[62] Understanding these biases and being mindful of such barriers when conducting studies in this area would be important.
CONCLUSION AND FUTURE DIRECTIONS
The cost burdens of severe sepsis are substantial. Elixhauser et al. suggest that it is currently the single most expensive cause of acute hospitalization in the United States.[63] Importantly, a large proportion of patients with severe sepsis receive care from hospitalists and/or floor teams on the general wards. Our integrative review has demonstrated a knowledge gap when it comes to rigorous assessments of PT and mobilization treatments in patients with severe sepsis within and beyond the ICU. Existing evidence provides a strong rationale for why functional decline occurs in patients with severe sepsis. A reasonable argument for PT‐based interventions to mitigate functional decline in this subset exists, but rigorous evaluation of such interventions is necessary. Physical and mobilization‐based treatments are routinely available and efficacious in several other settings and populations. It could be rapidly deployed and potentially improve outcomes in those with severe sepsis. Research would be welcomed to establish optimal dosing, efficacy, and cost effectiveness of PT and early mobilization for severe sepsis, particularly in patients treated on the general wards by hospitalists and floor teams.
How may such a research agenda be launched? A balanced multipronged approach is necessary. First, large‐scale epidemiological data to understand variation in practice are needed. Focused studies carried out by community and academic hospitalists on septic patients treated outside the ICU are the call of the hour. These data, in turn, can help create registries that assess for risk factors, quality of treatment, and long‐term outcomes among survivors of this condition. Second, evaluation and improvement of the coding and precision of physical and occupational therapy billing records is necessary so that their added value can be assessed and tracked using administrative data. Third, targeted prospective studies and clinical trials to directly evaluate the effect of PT in well‐defined patient populations with sepsis outside the ICU are needed. In this arena, hospitalist expertise and trained physical therapists will be crucial. The focus of this work should be directed toward both short‐term and long‐term functional outcomes, as well as mortality and morbidity assessments. Fourth, these patient‐centered efforts should loop back and inform the foundational biology of severe sepsis, thus illuminating patient‐centered end points, from biomarker analysis to physiometric measurements in basic and translational research.
In conclusion, this review sheds light on the fact that interventions that may mitigate the functional and cognitive decline in survivors of severe sepsis appear underdeveloped. Although the precise benefit of such interventions remains unclear, the low‐cost, widespread availability and generalizability of PT‐based interventions make it a worthy candidate for future research. As the numbers of survivors of sepsis expand, an unmet public health need for interventions to improve the long‐term outcomes of this population exists. Hospitalists and intensivists caring for severe sepsis patients must rise to meet this need. Together, we can help improve the lives of patients afflicted with severe sepsis, wherever they may receive care in the hospital.
Acknowledgements
The authors acknowledge the efforts of medical research librarians Andy Hickner, MSI, and Marissa Conte, MSI, on this project.
Disclosures
This work was supported by the National Institutes of HealthK08, HL091249 (T.J.I.) and VA HSR&D IIR‐11109 (T.J.I.). The views expressed here are the authors' own and do not necessarily represent the views of the US government or the Department of Veterans' Affairs. The authors report no conflicts of interest.
Severe sepsis, defined as an infection leading to systemic inflammatory response and acute organ dysfunction, is a significant cause of morbidity and mortality.[1, 2, 3] Although it has been a condition classically attributed to patients in the intensive care unit (ICU), accumulating data suggest that a substantial proportion of patients with severe sepsis are managed by hospitalists and floor teams in non‐ICU, general ward settings.[1, 4, 5] Although the incidence of severe sepsis continues to rise both in the United States and other developed nations,[2, 6, 7] advances in early recognition, management, and care of this condition have resulted in improved rates of survival.[8] The resultant increase in a severe sepsis survivor population[6] make the long‐term sequelae of this condition an important public health problem.[9]
In both the ICU and on general wards, severe sepsis survivors suffer from decreased functional status, worsened quality of life, increased cognitive dysfunction, and sarcopenia.[4, 6, 10, 11, 12, 13, 14] Not surprisingly, many such patients are discharged to long‐term care facilities for physical rehabilitation,[15] with escalating utilization of resources[16] and cost.[17, 18] Inexpensive interventions that improve outcomes following sepsis would thus be welcomed.
It is well known that physical therapy (PT) and early mobilization are beneficial in mitigating functional decline in a number of conditions.[19, 20, 21, 22] PT can improve outcomes in several ways: prevention of bed rest deconditioning, mitigation of mechanisms that lead to sarcopenia, increased pulmonary and tissue aerobic capacity, and improved sense of well‐being. Indeed, among the population cared for in ICU settings, early mobility and PT lead to more ventilator‐free days, better functional status at discharge, shorter duration of delirium, and even a potentially reduced risk of central line‐associated bloodstream infection (CLABSI).[23, 24] However, whether initiating early PT can improve outcomes in patients with severe sepsis treated by either intensivists or hospitalists/floor teams outside the ICU is unknown.
Therefore, to better understand this phenomenon, we systematically reviewed and integrated the literature regarding early mobilization and PT for severe sepsis outside the ICU. To be more inclusive, a secondary review including populations with any infectious etiology and severe sepsis treated within the ICU was also conducted. Our review begins by providing an overview of the pathophysiology behind functional decline in severe sepsis, along with existing evidence on early mobilization efficacy in other patient populations. We then proceed with a review of the extant literature on the aforementioned topic. We conclude with an evaluation of the current evidence on the subject, along with assertions regarding future research in the area.
PATHOPHYSIOLOGY OF DISABILITY FOLLOWING HOSPITALIZATION FOR SEVERE SEPSIS
The pathophysiology behind functional decline in patients hospitalized with severe sepsis is multifactorial (Figure 1). During hospitalization, it is well known that patients suffer from restricted mobility,[25] and that this impediment is linked to poor functional outcomes.[26] Described as far back as Hippocrates,[27] more recent studies have elucidated how prolonged bed rest leads to a multitude of physiological changes that promote deconditioning.[28] Specifically, skeletal muscle atrophy and decreased protein synthesis, independent of ongoing disease processes and acute illness, have been demonstrated in both animal and human models of prolonged inactivity.[29, 30] Additionally, bed rest leading to insensible fluid losses, a decline in stroke volume and effective cardiac output, bone loss, and decreased insulin sensitivity has been reported.[28, 31] There is little doubt that the aforementioned issues pertain to severe sepsis patients outside the ICU. In fact, nearly all of the acute mechanisms driving Creditor's hazards of hospitalization are noted among patients with severe sepsis.[32]
Furthermore, several factors preceding hospitalization may increase risk of disability. For example, Covinsky et al. described a number of risk factors, such as comorbid conditions, cognitive impairment, and various psychosocial aspects such as depression and limited social support, as being associated with increased risk of functional decline.[33] Thus, both in‐hospital and prehospital factors likely combine within an individual patient's context to determine risk of physical decline.
On this backdrop and the inherent immobilization associated with hospitalization, sepsis and inflammation catalyze physiologic changes that further propagate deconditioning.[7] Implicated pathways and proteins for this process include the mammalian target of rapamycin, human growth hormone, insulin‐like growth factors, interleukin‐1, and tumor necrosis factor‐. Through several metabolic alterations, sepsis independently promotes skeletal muscle breakdown and impairs skeletal muscle synthesis.[34, 35, 36] Inflammation associated with sepsis also increases oxidant burden, further leading to muscle dysfunction and dysregulation.[7, 31, 37, 38]
EFFECTS OF PHYSICAL THERAPY AND MOBILIZATION ON CLINICAL OUTCOMES
In patients with nonsepsis conditions who are at risk for functional decline, the effectiveness of physical therapy has been studied in multiple settings with positive outcomes. For example, in hospitalized elderly patients with general deconditioning, PT‐based interventions have demonstrated reductions in length of hospital stay.[39] Additionally, exercise in healthy subjects who have been subjected to bed rest has been shown to attenuate physiological changes, and maintain plasma and red cell volume and work capacity.[40] Adequate safety and improved outcomes have also been demonstrated in the general population of critically ill patients who receive early PT and mobilization. Improved functional capacity at discharge, decreases in duration of delirium, increased ventilator‐free days, decreased risk for CLABSI, and a better general sense of well‐being following these interventions have been widely reported in the literature.[14, 19, 23, 24, 41, 42, 43, 44, 45] Interestingly, critically ill patients may have a dose‐ and time‐dependent response to PT; that is, high intensity and early onset mobility‐based interventions are often associated with more ventilator‐free time and improved functional outcomes, resulting in shorter ICU and hospital length of stay.[42, 46, 47, 48]
Moderate intensity exercise has also been shown to improve 6‐minute walking distance in patients convalescing from coronary artery bypass grafting surgery.[49] Furthermore, in the postoperative setting, patients suffering traumatic hip fractures are known to benefit from physical and occupational therapies with shorter time to ambulation and improved locomotion in the recovery period.[21, 50, 51] Among patients with stroke, PT and gait training has led to improvements in speed, gait, independence during walking, activities of daily living, and extended activities of daily living.[52, 53, 54] A recent meta‐analysis also suggested that extra PT compared to regular treatment in patients with acute and subacute conditions such as stroke and postoperative states improved mobility and quality of life, while reducing length of hospital stay.[22]
Although this evidence suggests potential benefits for PT and mobilization, it is important to note that the effect of these treatments in dissimilar populations is unknown and may not necessarily be positive. For example, a recent study examining PT and its impact on patients with hip osteoarthritis showed no clinical benefit.[55] Mobilizing patients in severe illness may be associated with important risks, including falls, worsening of their clinical status, or moral discouragement in the setting of limited capacity. Therefore, understanding which elements of mobilization efforts create the greatest impact in the context of delivery of the intervention is critical to assessing the risk, benefit, and efficacy of PT‐based interventions.
EARLY PHYSICAL THERAPY FOR SEVERE SEPSIS OUTSIDE THE ICU: LITERATURE REVIEW
Given the functional decline associated with severe sepsis and the evidence of PT efficacy in other populations, we reviewed the current literature for studies evaluating physical therapy in severe sepsis patients outside the ICU. With the assistance of medical reference librarians, we searched MEDLINE via PubMed (1950present), EMBASE (1946present), Cochrane CENTRAL Register of Controlled Trials, and the Cochrane Database of Reviews of Effectiveness (1960present via Ovid). The search was last updated in June 2014.
We searched for studies that (1) involved human patients 18 years of age, (2) included patients with a primary diagnosis of sepsis or severe sepsis being treated outside the ICU, (3) featured a primary intervention that included PT or an early mobilization‐based initiative, and (4) reported a primary clinical or functional outcome of interest. Early was defined based on the included studies' definition. To be fully inclusive, we also conducted a secondary review with inclusion criteria expanded to studies of either any infectious pathology or severe sepsis patient in the ICU that employed PT interventions.
Our electronic search retrieved 815 records (Figure 2). Despite this approach, no publications met our primary inclusion criteria as we found no study that implemented a mobility intervention directed toward patients with sepsis treated outside the ICU. Our expanded secondary review included patients with any infectious pathology or those with severe sepsis in the ICU treated with PT; in this review, 2 studies met eligibility criteria.[56] In a 2003 cluster‐randomized trial, Mundy and colleagues randomized patients admitted with pneumonia to receive early PT or usual care. The outcomes of interest were hospital length of stay, mortality, number of chest radiographs, emergency department visits, and readmissions at 30 and 90 days after hospital admission. Although the study has important limitations (including patient‐level difference between trial arms, subjective definition of early mobilization), the authors found a significant decrease in length of stay among patients with pneumonia who received early PT compared to controls (5.8 vs 6.9 days, absolute difference 1.1 days, 95% confidence interval: 02.2 days). The study also reported a substantial decrease in adjusted mean hospital charges for the early mobilization group versus the usual care group ($10,159 per patient vs. $12,868 per patient, P=0.05). In the second study, Sossdorf et al. retrospectively evaluated a cohort of 999 patients with severe sepsis and septic shock and assessed whether onset and frequency of PT‐based interventions was associated with clinical benefit. After multivariate analysis, the authors reported a small mortality benefit associated with the relative number of PT interventions (hazard ratio: 0.982, P<0.001).[45]
EXPLAINING THE VOID
Our integrative review of the current literature reveals a gap in our understanding of the role of early mobilization in severe sepsis both within and beyond the ICU. Given the promise of PT‐based interventions and the toll of severe sepsis, one must ask: why may this be so?
First, the understanding that severe sepsis leads to significant, long‐term consequences for survivors has only been identified recently. Thus, it is possible that the burden and consequences related to this condition have not been fully recognized in clinical settings, leading to a paucity of research and interventions. Although the association between sepsis and mortality has been known since the 1990s,[57] long‐term complications and enduring morbidity of this disease continue to be realized. Indeed, many studies delineating the longer‐term effects of sepsis have been only recently published.[6, 10, 11, 12, 13]
Second, it is likely that many clinicians ascribe to the viewpoint that severe sepsis is an ICU‐only condition, a myth that has been discounted by multiple studies.[1, 4, 5] Although our study shows a paucity of evidence in both ICU and nonICU‐based severe sepsis, almost half of severe sepsis occurs outside the ICU, carrying with it many of the same clinical implications. Additionally, increased morbidity, mortality, and resource utilization are known to be true in all patients with severe sepsis, irrespective of where they receive treatment in the hospital.[4, 5, 6] Recent evidence has also shown that severe sepsis treated on the floor may be clinically, epidemiologically, and even prognostically unique from its ICU counterpart.[5, 58, 59] Therefore, it appears that research domains with tailored interventions to both ICU and non‐ICU severe sepsis patients are important areas of inquiry for clinicians. Such research may serve the purpose of assessing impact of early mobilization and unmasking any treatment heterogeneity that may exist when dealing with severe sepsis. Though trials of PT in ICU‐based severe sepsis are underway,[60] it is prudent that these also extend beyond the ICU‐setting.
Third, variability in early mobility practices and billing documentation for severe sepsis patients may exist, adding barriers to performing high‐quality research on this topic. In fact, administrative billing records for PT may offer insufficient granularity about services provided or therapies administered, particularly in the ICU where variability in early mobilization practices have been shown despite common employment of physiotherapists.[61]
Finally, many hospitalists may believe that patients with severe sepsis are simply too sick for early mobilization or PT, possibly limiting their participation in clinical or research‐based interventions. This perception has been well described in ICU populations, where it has been well studied and shown to be false.[41, 42, 43] Nevertheless, if severe sepsis patients are viewed as relatively sick hospitalized patients, it is plausible that resistance against early mobilization interventions may exist.[62] Understanding these biases and being mindful of such barriers when conducting studies in this area would be important.
CONCLUSION AND FUTURE DIRECTIONS
The cost burdens of severe sepsis are substantial. Elixhauser et al. suggest that it is currently the single most expensive cause of acute hospitalization in the United States.[63] Importantly, a large proportion of patients with severe sepsis receive care from hospitalists and/or floor teams on the general wards. Our integrative review has demonstrated a knowledge gap when it comes to rigorous assessments of PT and mobilization treatments in patients with severe sepsis within and beyond the ICU. Existing evidence provides a strong rationale for why functional decline occurs in patients with severe sepsis. A reasonable argument for PT‐based interventions to mitigate functional decline in this subset exists, but rigorous evaluation of such interventions is necessary. Physical and mobilization‐based treatments are routinely available and efficacious in several other settings and populations. It could be rapidly deployed and potentially improve outcomes in those with severe sepsis. Research would be welcomed to establish optimal dosing, efficacy, and cost effectiveness of PT and early mobilization for severe sepsis, particularly in patients treated on the general wards by hospitalists and floor teams.
How may such a research agenda be launched? A balanced multipronged approach is necessary. First, large‐scale epidemiological data to understand variation in practice are needed. Focused studies carried out by community and academic hospitalists on septic patients treated outside the ICU are the call of the hour. These data, in turn, can help create registries that assess for risk factors, quality of treatment, and long‐term outcomes among survivors of this condition. Second, evaluation and improvement of the coding and precision of physical and occupational therapy billing records is necessary so that their added value can be assessed and tracked using administrative data. Third, targeted prospective studies and clinical trials to directly evaluate the effect of PT in well‐defined patient populations with sepsis outside the ICU are needed. In this arena, hospitalist expertise and trained physical therapists will be crucial. The focus of this work should be directed toward both short‐term and long‐term functional outcomes, as well as mortality and morbidity assessments. Fourth, these patient‐centered efforts should loop back and inform the foundational biology of severe sepsis, thus illuminating patient‐centered end points, from biomarker analysis to physiometric measurements in basic and translational research.
In conclusion, this review sheds light on the fact that interventions that may mitigate the functional and cognitive decline in survivors of severe sepsis appear underdeveloped. Although the precise benefit of such interventions remains unclear, the low‐cost, widespread availability and generalizability of PT‐based interventions make it a worthy candidate for future research. As the numbers of survivors of sepsis expand, an unmet public health need for interventions to improve the long‐term outcomes of this population exists. Hospitalists and intensivists caring for severe sepsis patients must rise to meet this need. Together, we can help improve the lives of patients afflicted with severe sepsis, wherever they may receive care in the hospital.
Acknowledgements
The authors acknowledge the efforts of medical research librarians Andy Hickner, MSI, and Marissa Conte, MSI, on this project.
Disclosures
This work was supported by the National Institutes of HealthK08, HL091249 (T.J.I.) and VA HSR&D IIR‐11109 (T.J.I.). The views expressed here are the authors' own and do not necessarily represent the views of the US government or the Department of Veterans' Affairs. The authors report no conflicts of interest.
- , . Epidemiology of sepsis: an update. Crit Care Med. 2001;29:S109–S116.
- , , , et al. Nationwide trends of severe sepsis in the 21st century (2000–2007). Chest. 2011;140:1223–1231.
- , , , et al. The epidemiology of sepsis in the United States from 1979 through 2000. N Engl J Med. 2003;348:1546–1554.
- , , , et al. Functional outcomes of general medical patients with severe sepsis. BMC Infect Dis. 2013;13:588.
- , , , et al. The epidemiology of acute organ system dysfunction from severe sepsis outside of the intensive care unit. J Hosp Med. 2013;8:243–247.
- , , , et al. Population burden of long‐term survivorship after severe sepsis in older Americans. J Am Geriatr Soc. 2012;60:1070–1077.
- , , , et al. Systemic inflammatory response syndrome increases immobility‐induced neuromuscular weakness. Crit Care Med. 2008;36:910–916.
- , , , et al. Early goal‐directed therapy in the treatment of severe sepsis and septic shock. N Engl J Med. 2001;345:1368–1377.
- . The lingering consequences of sepsis: a hidden public health disaster? JAMA. 2010;304:1833–1834.
- , , , et al. Long‐term cognitive impairment and functional disability among survivors of severe sepsis. JAMA. 2010;304:1787–1794.
- , , , et al. Spurious inferences about long‐term outcomes: the case of severe sepsis and geriatric conditions. Am J Respir Crit Care Med. 2012;185:835–841.
- , , , et al. Long‐term outcome and quality‐adjusted life years after severe sepsis. Crit Care Med. 2009;37:1268–1274.
- , , , et al. Long‐term mortality and quality of life in sepsis: a systematic review. Crit Care Med. 2010;38:1276–1283.
- , , , et al. Improving post‐intensive care unit neuropsychiatric outcomes: understanding cognitive effects of physical activity. Am J Respir Crit Care Med. 2012;186:1220–1228.
- , , , et al. Hospitalizations, costs, and outcomes of severe sepsis in the United States 2003 to 2007. Crit Care Med. 2012;40:754–761.
- , , , et al. Long‐term acute care hospital utilization after critical illness. JAMA. 2010;303:2253–2259.
- , , , et al. Long‐term survival and healthcare utilization outcomes attributable to sepsis and pneumonia. BMC Health Serv Res. 2012;12:432.
- , , , et al. Long‐term mortality and medical care charges in patients with severe sepsis. Crit Care Med. 2003;31:2316–2323.
- , , , et al. Early exercise in critically ill patients enhances short‐term functional recovery. Crit Care Med. 2009;37:2499–2505.
- , , , et al. Exercise‐based cardiac rehabilitation for coronary heart disease. Cochrane Database Syst Rev. 2011;(7):CD001800.
- , , , et al. What is the role of timing in the surgical and rehabilitative care of community‐dwelling older persons with acute hip fracture? Arch Intern Med. 1997;157:513–520.
- , , . Extra physical therapy reduces patient length of stay and improves functional outcomes and quality of life in people with acute or subacute conditions: a systematic review. Arch Phys Med Rehabilil. 2011;92:1490–1500.
- , , . Reduction of intensive care unit length of stay: the case of early mobilization. Health Care Manag (Frederick). 2014;33:128–135.
- , , , et al. Early physical and occupational therapy in mechanically ventilated, critically ill patients: a randomised controlled trial. Lancet. 2009;373:1874–1882.
- , , , et al. Hospitalization, restricted activity, and the development of disability among older persons. JAMA. 2004;292:2115–2124.
- , , , et al. Low mobility during hospitalization and functional decline in older adults. J Am Geriatr Soc. 2011;59:266–273.
- , . The Medical Works of Hippocrates. Oxford, United Kingdom: Blackwell; 1950.
- , , . An overview of the issues: physiological effects of bed rest and restricted physical activity. Med Sci Sports Exerc. 1997;29:187–190.
- , , , et al. Prolonged bed rest decreases skeletal muscle and whole body protein synthesis. Am J Physiol. 1996;270:E627–E633.
- , . Metabolic consequences of muscle disuse atrophy. J Nutr. 2005;135:1824S–1828S.
- . Inactivity and inflammation in the critically ill patient. Crit Care Clin. 2007;23:21–34.
- . Hazards of hospitalization of the elderly. Ann Intern Med. 1993;118:219–223.
- , , . Hospitalization‐associated disability: “She was probably able to ambulate, but I'm not sure”. JAMA. 2011;306:1782–1793.
- , , , et al. A sustained rat model for studying the long‐lasting catabolic state of sepsis. Infect Immun. 1999;67:1079–1085.
- . Regulation of skeletal muscle protein turnover during sepsis. Curr Opin Clin Nutr. Metab Care. 1998;1:217–224.
- , , . Regulation of muscle protein synthesis during sepsis and inflammation. Am J Physiol Endocrinol Metab. 2007;293:E453–E459.
- , . From muscle disuse to myopathy in COPD: potential contribution of oxidative stress. Eur Respir J. 2005;26:703–719.
- , , . Oxidative stress and gene expression in sepsis. Br J Anaesth. 2003;90:221–232.
- , , , et al. Early ambulation and length of stay in older adults hospitalized for acute illness. Arch Intern Med. 2010;170:1942–1943.
- . Intensive exercise training during bed rest attenuates deconditioning. Med Sci Sports Exerc. 1997;29:207–215.
- , , , et al. Early activity is feasible and safe in respiratory failure patients. Crit Care Med. 2007;35:139–145.
- , , , et al. Early intensive care unit mobility therapy in the treatment of acute respiratory failure. Crit Care Med. 2008;36:2238–2243.
- . Clinical trials of early mobilization of critically ill patients. Crit Care Med. 2009;37:S442–S447.
- . Mobilizing patients in the intensive care unit: improving neuromuscular weakness and physical function. JAMA. 2008;300:1685–1690.
- , , , et al. Potential effect of physiotherapeutic treatment on mortality rate in patients with severe sepsis and septic shock: a retrospective cohort analysis. J Crit Care. 2013;28:954–958.
- , , , et al. Effects of physical training on functional status in patients with prolonged mechanical ventilation. Phys Ther. 2006;86:1271–1281.
- , , , et al. Impact of whole‐body rehabilitation in patients receiving chronic mechanical ventilation. Crit Care Med. 2005;33:2259–2265.
- . Rehabilitation of patients admitted to a respiratory intensive care unit. Arch Phys Med Rehabil. 1998;79:849–854.
- , , , et al. Supervised moderate intensity exercise improves distance walked at hospital discharge following coronary artery bypass graft surgery—a randomised controlled trial. Heart Lung Circ. 2008;17:129–138.
- , , , et al. Systematic review of hip fracture rehabilitation practices in the elderly. Arch Phys Med Rehabil. 2009;90:246–262.
- , , , et al. Physical therapy and mobility 2 and 6 months after hip fracture. J Am Geriatr Soc. 2004;52:1114–1120.
- , , , et al. Physical fitness training for stroke patients. Cochrane Database Syst Rev. 2011;(11):CD003316.
- , , , et al. Effects of augmented exercise therapy on outcome of gait and gait‐related activities in the first 6 months after stroke: a meta‐analysis. Stroke. 2011;42:3311–3315.
- , , , et al. Effects of augmented exercise therapy time after stroke: a meta‐analysis. Stroke. 2004;35:2529–2539.
- , , , et al. Effect of physical therapy on pain and function in patients with hip osteoarthritis: a randomized clinical trial. JAMA. 2014;311:1987–1997.
- , , , et al. Early mobilization of patients hospitalized with community‐acquired pneumonia. Chest. 2003;124:883–889.
- , , , et al. Magnitude and duration of the effect of sepsis on survival. Department of Veterans Affairs Systemic Sepsis Cooperative Studies Group. JAMA. 1997;277:1058–1063.
- , , , et al. Epidemiology of sepsis in Victoria, Australia. Crit Care Med. 2005;33:71–80.
- , , , et al. Sepsis incidence and outcome: contrasting the intensive care unit with the hospital ward. Crit Care Med. 2007;35:1284–1289.
- , , . Early rehabilitation in sepsis: a prospective randomised controlled trial investigating functional and physiological outcomes The i‐PERFORM Trial (Protocol Article). BMC Anesthesiol. 2011;11:21.
- , , , et al. TEAM: a prospective multi‐centre cohort study of early activity and mobilisation in ICU. In: American Thoracic Society 2013 International Conference; May 17–22, 2013; Philadelphia, PA. Am J Respir Crit Care Med. 2013;187:A3625.
- , , , et al. Improving long‐term outcomes after discharge from intensive care unit: report from a stakeholders' conference. Crit Care Med. 2012;40:502–509.
- , , . Septicemia in U.S. hospitals, 2009: statistical brief #122. Healthcare Cost and Utilization Project (HCUP) Statistical Briefs. Rockville, MD; 2006.
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- , , , et al. Systemic inflammatory response syndrome increases immobility‐induced neuromuscular weakness. Crit Care Med. 2008;36:910–916.
- , , , et al. Early goal‐directed therapy in the treatment of severe sepsis and septic shock. N Engl J Med. 2001;345:1368–1377.
- . The lingering consequences of sepsis: a hidden public health disaster? JAMA. 2010;304:1833–1834.
- , , , et al. Long‐term cognitive impairment and functional disability among survivors of severe sepsis. JAMA. 2010;304:1787–1794.
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- , , , et al. Improving post‐intensive care unit neuropsychiatric outcomes: understanding cognitive effects of physical activity. Am J Respir Crit Care Med. 2012;186:1220–1228.
- , , , et al. Hospitalizations, costs, and outcomes of severe sepsis in the United States 2003 to 2007. Crit Care Med. 2012;40:754–761.
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- , , , et al. Long‐term survival and healthcare utilization outcomes attributable to sepsis and pneumonia. BMC Health Serv Res. 2012;12:432.
- , , , et al. Long‐term mortality and medical care charges in patients with severe sepsis. Crit Care Med. 2003;31:2316–2323.
- , , , et al. Early exercise in critically ill patients enhances short‐term functional recovery. Crit Care Med. 2009;37:2499–2505.
- , , , et al. Exercise‐based cardiac rehabilitation for coronary heart disease. Cochrane Database Syst Rev. 2011;(7):CD001800.
- , , , et al. What is the role of timing in the surgical and rehabilitative care of community‐dwelling older persons with acute hip fracture? Arch Intern Med. 1997;157:513–520.
- , , . Extra physical therapy reduces patient length of stay and improves functional outcomes and quality of life in people with acute or subacute conditions: a systematic review. Arch Phys Med Rehabilil. 2011;92:1490–1500.
- , , . Reduction of intensive care unit length of stay: the case of early mobilization. Health Care Manag (Frederick). 2014;33:128–135.
- , , , et al. Early physical and occupational therapy in mechanically ventilated, critically ill patients: a randomised controlled trial. Lancet. 2009;373:1874–1882.
- , , , et al. Hospitalization, restricted activity, and the development of disability among older persons. JAMA. 2004;292:2115–2124.
- , , , et al. Low mobility during hospitalization and functional decline in older adults. J Am Geriatr Soc. 2011;59:266–273.
- , . The Medical Works of Hippocrates. Oxford, United Kingdom: Blackwell; 1950.
- , , . An overview of the issues: physiological effects of bed rest and restricted physical activity. Med Sci Sports Exerc. 1997;29:187–190.
- , , , et al. Prolonged bed rest decreases skeletal muscle and whole body protein synthesis. Am J Physiol. 1996;270:E627–E633.
- , . Metabolic consequences of muscle disuse atrophy. J Nutr. 2005;135:1824S–1828S.
- . Inactivity and inflammation in the critically ill patient. Crit Care Clin. 2007;23:21–34.
- . Hazards of hospitalization of the elderly. Ann Intern Med. 1993;118:219–223.
- , , . Hospitalization‐associated disability: “She was probably able to ambulate, but I'm not sure”. JAMA. 2011;306:1782–1793.
- , , , et al. A sustained rat model for studying the long‐lasting catabolic state of sepsis. Infect Immun. 1999;67:1079–1085.
- . Regulation of skeletal muscle protein turnover during sepsis. Curr Opin Clin Nutr. Metab Care. 1998;1:217–224.
- , , . Regulation of muscle protein synthesis during sepsis and inflammation. Am J Physiol Endocrinol Metab. 2007;293:E453–E459.
- , . From muscle disuse to myopathy in COPD: potential contribution of oxidative stress. Eur Respir J. 2005;26:703–719.
- , , . Oxidative stress and gene expression in sepsis. Br J Anaesth. 2003;90:221–232.
- , , , et al. Early ambulation and length of stay in older adults hospitalized for acute illness. Arch Intern Med. 2010;170:1942–1943.
- . Intensive exercise training during bed rest attenuates deconditioning. Med Sci Sports Exerc. 1997;29:207–215.
- , , , et al. Early activity is feasible and safe in respiratory failure patients. Crit Care Med. 2007;35:139–145.
- , , , et al. Early intensive care unit mobility therapy in the treatment of acute respiratory failure. Crit Care Med. 2008;36:2238–2243.
- . Clinical trials of early mobilization of critically ill patients. Crit Care Med. 2009;37:S442–S447.
- . Mobilizing patients in the intensive care unit: improving neuromuscular weakness and physical function. JAMA. 2008;300:1685–1690.
- , , , et al. Potential effect of physiotherapeutic treatment on mortality rate in patients with severe sepsis and septic shock: a retrospective cohort analysis. J Crit Care. 2013;28:954–958.
- , , , et al. Effects of physical training on functional status in patients with prolonged mechanical ventilation. Phys Ther. 2006;86:1271–1281.
- , , , et al. Impact of whole‐body rehabilitation in patients receiving chronic mechanical ventilation. Crit Care Med. 2005;33:2259–2265.
- . Rehabilitation of patients admitted to a respiratory intensive care unit. Arch Phys Med Rehabil. 1998;79:849–854.
- , , , et al. Supervised moderate intensity exercise improves distance walked at hospital discharge following coronary artery bypass graft surgery—a randomised controlled trial. Heart Lung Circ. 2008;17:129–138.
- , , , et al. Systematic review of hip fracture rehabilitation practices in the elderly. Arch Phys Med Rehabil. 2009;90:246–262.
- , , , et al. Physical therapy and mobility 2 and 6 months after hip fracture. J Am Geriatr Soc. 2004;52:1114–1120.
- , , , et al. Physical fitness training for stroke patients. Cochrane Database Syst Rev. 2011;(11):CD003316.
- , , , et al. Effects of augmented exercise therapy on outcome of gait and gait‐related activities in the first 6 months after stroke: a meta‐analysis. Stroke. 2011;42:3311–3315.
- , , , et al. Effects of augmented exercise therapy time after stroke: a meta‐analysis. Stroke. 2004;35:2529–2539.
- , , , et al. Effect of physical therapy on pain and function in patients with hip osteoarthritis: a randomized clinical trial. JAMA. 2014;311:1987–1997.
- , , , et al. Early mobilization of patients hospitalized with community‐acquired pneumonia. Chest. 2003;124:883–889.
- , , , et al. Magnitude and duration of the effect of sepsis on survival. Department of Veterans Affairs Systemic Sepsis Cooperative Studies Group. JAMA. 1997;277:1058–1063.
- , , , et al. Epidemiology of sepsis in Victoria, Australia. Crit Care Med. 2005;33:71–80.
- , , , et al. Sepsis incidence and outcome: contrasting the intensive care unit with the hospital ward. Crit Care Med. 2007;35:1284–1289.
- , , . Early rehabilitation in sepsis: a prospective randomised controlled trial investigating functional and physiological outcomes The i‐PERFORM Trial (Protocol Article). BMC Anesthesiol. 2011;11:21.
- , , , et al. TEAM: a prospective multi‐centre cohort study of early activity and mobilisation in ICU. In: American Thoracic Society 2013 International Conference; May 17–22, 2013; Philadelphia, PA. Am J Respir Crit Care Med. 2013;187:A3625.
- , , , et al. Improving long‐term outcomes after discharge from intensive care unit: report from a stakeholders' conference. Crit Care Med. 2012;40:502–509.
- , , . Septicemia in U.S. hospitals, 2009: statistical brief #122. Healthcare Cost and Utilization Project (HCUP) Statistical Briefs. Rockville, MD; 2006.
