Physical Therapy Utilization and 12-Month Pain and Functional Improvement in Patients Undergoing Arthroscopic Rotator Cuff Repair Surgery: A Case Series
Pierson, C. J.; Moore, B. P.; Elias, T.; Harris, J. C.; Somerson, J.
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BackgroundArthroscopic rotator cuff repair (RCR) is a common surgical intervention used to address rotator cuff-related pain after other conservative interventions have been exhausted. With a continuing increase in procedures, evidence-based outcomes research is needed to identify key parameters of postoperative rehabilitation planning. ObjectiveWe aim to identify rehabilitation planning factors leading to better outcomes while also providing clinicians with reference data to describe the magnitude of pain and functional improvement following RCR. MethodsFor this observational study of patients undergoing RCR surgery and physical therapy, demographic variables and patient-reported outcome measures (PRO) were collected preoperatively and up to 12 months postoperatively Four multiple linear regression models were created, one for 12-month Visual Analog Scale (VAS) score, the second for VAS improvement, the third for 12-month American Shoulder and Elbow Surgeons (ASES) function score, and the fourth for ASES function improvement. ResultsThe 29 participants had a median age of 62 years, median baseline VAS of 4.9, ASES composite score of 45, and Veterans-Rand 12 Mental Component Score of 53.5. In univariate analysis, one variable was associated with 12-month VAS score and two were associated with 12-month VAS improvement. No associations were found with 12-month ASES function score, and one variable was associated with ASES function improvement. With our sample, multivariable analyses provided no significant association or predictor for VAS or ASES function scores. ConclusionsOur hypothesis was not supported, and we did not find an association between physical therapy wait time prior to evaluation or visit frequency and PRO measures or improvements. We observed that 12-month PRO measures and improvements can be predicted using baseline measures among this population.
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