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Resilience correlates to outcomes after total shoulder arthroplasty
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J Shoulder Elbow Surg Volume 26, Number 5
Table 3
Effect of preoperative depression, and anxiety on postoperative outcome measurements
Preoperative parameter HADS-Depression Score Coefficient 95% CI P value HADS-Anxiety Score Coefficient 95% CI P value
12 months after surgery VAS pain score
ASES score
SSV
WHOQOL-BREF score
0.01 −0.232 to 0.252 0.934
−0.086 −2.138 to 1.966 0.933
0.524 −0.712 to 1.761 0.397
−0.927 −1.986 to 0.133 0.085
−0.068 −0.298 to 0.163 0.558
0.254 −1.698 to 2.206 0.794
−0.191 −1.367 to 0.984 0.744
−0.329 −1.336 to 0.678 0.514
Paper #19 RESILIENCE CORRELATES TO OUTCOMES AFTER TOTAL SHOULDER ARTHROPLASTY
Ellen Shanley, PhD, PT, Michael J. Kissenberth, MD, Stefan J. Tolan, MD, Keith T. Lonergan, MD, Richard J. Hawkins, MD, Tariq I. Salim, BS, Josh Tadlock, BS, Thomas Kellam, BS, Catherine Long, BS, Ashley Crawford, BS, Jennifer M. Mercuri, MS, John M. Tokish, MD, Steadman Hawkins Clinic of the Carolinas, ATI Physical Therapy, Greenville Health System, Greenville, South Carolina, USA Introduction: Resilience, characterized by toughness, elasticity, and the ability to recover,1 is increasingly recognized as a psychometric property affecting many outcomes’ domains including quality of life, suicide risk in active duty military, and recovery in cancer patients. While extensively studied in response to stressful events, no study has evaluated the relationship between resiliency and outcomes after surgical intervention. The purpose of this study was to examine the correlation between resilience as measured by the Brief Resilience Score (BRS), and traditional outcomes scores including the American Shoulder and Elbow (ASES), Single Assessment Numeric Evaluation (SANE), and PENN Scores in a population of patients undergoing Total Shoulder Arthroplasty (TSA). Methods: Seventy patients undergoing TSA were followed for a minimum of 2 yrs (average = 39 months). There were 19 males and 51 females, with an average age of 65.0 ± 10.1 yrs. All patients had outcomes scores at final followup including ASES, PENN, and BRS scores. Patients were stratified into groups based on deviation from the mean of the BRS, into low (LR), normal (NR), and high resilience (HR) patients, and outcomes scores were calculated for each group. Results: Postoperative BRS scores significantly correlated with ASES, PENN, and SANE scores (r = .41-.44, P < .004 for all scores). When evaluating patients based on resiliency group, the low resilience group (LR) had PENN scores that were 34 points lower than the high group (HR). Likewise, the LR group had a SANE score that averaged 40 points lower than the HR group. (SANE 53 in LR Group, 92 in HR group P = .05). When evaluating ASES subscores, it appeared that the pain subscale was responsible for most of the difference between the LR and HR groups (29 vs 48 points out of 50, respectively, P = .03). Conclusions: Resilience is a major predictor of postoperative outcomes after total shoulder arthroplasty. Patients who are classified as low resilience have outcomes scores that are 30-40 points lower on traditional outcomes scores than patients who are highly resilient. Further study is warranted to determine whether this resilience is modifiable and whether preoperative resilience optimization may result in improved postoperative outcomes.
Reference 1. Leppin AL, Gionfriddo MR, Sood A, Montori VM, Erwin PJ, Zeballos-Palacios C, et al. The efficacy of resilience training programs: a systematic review protocol. Syst Rev 2014;3:20.
Paper #20 THIRTY AND NINETY-DAY READMISSION FOLLOWING TOTAL SHOULDER ARTHROPLASTY: A CRITICAL ANALYSIS OF RATE, RISK AND REASON FOR READMISSION
Justin W. Griffin, MD, Bryce A. Basques, MD, Timothy S. Leroux, MD, Rachel M. Frank, MD, Nikhil N. Verma, MD, Anthony A. Romeo, MD, Department of Orthopaedic Surgery, Rush University Medical Center, Chicago, Illinois, USA Introduction: Health care payers are increasingly evaluating reimbursement based on quality measures. Recent initiatives to improve hospital quality of care include critically assessing unplanned hospital readmission rates. The purpose of this study was to evaluate readmission rates and risk factors for readmission after total shoulder arthroplasty (TSA) in order to identify patient factors and medical comorbidities that may variably impact rates of readmission. Methods: Using Current Procedural Terminology (CPT) and International Classification of Diseases, 9th Revision (ICD-9) procedure codes, we queried a national Medicare database for patients undergoing TSA between 2005 and 2012. Patients were divided into various cohorts utilizing ICD-9 codes and other comorbidities and analyzed accordingly. Readmission rates were assessed with ICD-9 and CPT codes. Patient characteristics were compared between procedure groups with chisquared analysis. Multivariate logistic regression was used to compare groups in terms of postoperative complications within 90 days, and
J Shoulder Elbow Surg Volume 26, Number 5
Table 3
Effect of preoperative depression, and anxiety on postoperative outcome measurements
Preoperative parameter HADS-Depression Score Coefficient 95% CI P value HADS-Anxiety Score Coefficient 95% CI P value
12 months after surgery VAS pain score
ASES score
SSV
WHOQOL-BREF score
0.01 −0.232 to 0.252 0.934
−0.086 −2.138 to 1.966 0.933
0.524 −0.712 to 1.761 0.397
−0.927 −1.986 to 0.133 0.085
−0.068 −0.298 to 0.163 0.558
0.254 −1.698 to 2.206 0.794
−0.191 −1.367 to 0.984 0.744
−0.329 −1.336 to 0.678 0.514
Paper #19 RESILIENCE CORRELATES TO OUTCOMES AFTER TOTAL SHOULDER ARTHROPLASTY
Ellen Shanley, PhD, PT, Michael J. Kissenberth, MD, Stefan J. Tolan, MD, Keith T. Lonergan, MD, Richard J. Hawkins, MD, Tariq I. Salim, BS, Josh Tadlock, BS, Thomas Kellam, BS, Catherine Long, BS, Ashley Crawford, BS, Jennifer M. Mercuri, MS, John M. Tokish, MD, Steadman Hawkins Clinic of the Carolinas, ATI Physical Therapy, Greenville Health System, Greenville, South Carolina, USA Introduction: Resilience, characterized by toughness, elasticity, and the ability to recover,1 is increasingly recognized as a psychometric property affecting many outcomes’ domains including quality of life, suicide risk in active duty military, and recovery in cancer patients. While extensively studied in response to stressful events, no study has evaluated the relationship between resiliency and outcomes after surgical intervention. The purpose of this study was to examine the correlation between resilience as measured by the Brief Resilience Score (BRS), and traditional outcomes scores including the American Shoulder and Elbow (ASES), Single Assessment Numeric Evaluation (SANE), and PENN Scores in a population of patients undergoing Total Shoulder Arthroplasty (TSA). Methods: Seventy patients undergoing TSA were followed for a minimum of 2 yrs (average = 39 months). There were 19 males and 51 females, with an average age of 65.0 ± 10.1 yrs. All patients had outcomes scores at final followup including ASES, PENN, and BRS scores. Patients were stratified into groups based on deviation from the mean of the BRS, into low (LR), normal (NR), and high resilience (HR) patients, and outcomes scores were calculated for each group. Results: Postoperative BRS scores significantly correlated with ASES, PENN, and SANE scores (r = .41-.44, P < .004 for all scores). When evaluating patients based on resiliency group, the low resilience group (LR) had PENN scores that were 34 points lower than the high group (HR). Likewise, the LR group had a SANE score that averaged 40 points lower than the HR group. (SANE 53 in LR Group, 92 in HR group P = .05). When evaluating ASES subscores, it appeared that the pain subscale was responsible for most of the difference between the LR and HR groups (29 vs 48 points out of 50, respectively, P = .03). Conclusions: Resilience is a major predictor of postoperative outcomes after total shoulder arthroplasty. Patients who are classified as low resilience have outcomes scores that are 30-40 points lower on traditional outcomes scores than patients who are highly resilient. Further study is warranted to determine whether this resilience is modifiable and whether preoperative resilience optimization may result in improved postoperative outcomes.
Reference 1. Leppin AL, Gionfriddo MR, Sood A, Montori VM, Erwin PJ, Zeballos-Palacios C, et al. The efficacy of resilience training programs: a systematic review protocol. Syst Rev 2014;3:20.
Paper #20 THIRTY AND NINETY-DAY READMISSION FOLLOWING TOTAL SHOULDER ARTHROPLASTY: A CRITICAL ANALYSIS OF RATE, RISK AND REASON FOR READMISSION
Justin W. Griffin, MD, Bryce A. Basques, MD, Timothy S. Leroux, MD, Rachel M. Frank, MD, Nikhil N. Verma, MD, Anthony A. Romeo, MD, Department of Orthopaedic Surgery, Rush University Medical Center, Chicago, Illinois, USA Introduction: Health care payers are increasingly evaluating reimbursement based on quality measures. Recent initiatives to improve hospital quality of care include critically assessing unplanned hospital readmission rates. The purpose of this study was to evaluate readmission rates and risk factors for readmission after total shoulder arthroplasty (TSA) in order to identify patient factors and medical comorbidities that may variably impact rates of readmission. Methods: Using Current Procedural Terminology (CPT) and International Classification of Diseases, 9th Revision (ICD-9) procedure codes, we queried a national Medicare database for patients undergoing TSA between 2005 and 2012. Patients were divided into various cohorts utilizing ICD-9 codes and other comorbidities and analyzed accordingly. Readmission rates were assessed with ICD-9 and CPT codes. Patient characteristics were compared between procedure groups with chisquared analysis. Multivariate logistic regression was used to compare groups in terms of postoperative complications within 90 days, and