Patientsʼ Preoperative Expectations Predict the Outcome of Rotator Cuff Repair

Abstract

We are not aware of any previous studies of the relationship between patients' expectations regarding rotator cuff repair and the actual outcome. We hypothesized that preoperative expectations are predictive of the outcome of rotator cuff repair. One hundred and twenty-five patients who underwent unilateral primary repair of a chronic rotator cuff tear were included in the study. All operations were performed by a single surgeon. Each patient prospectively completed the Simple Shoulder Test (SST); the Disabilities of the Arm, Shoulder and Hand (DASH) questionnaire; three visual analogue scales for shoulder pain, shoulder function, and quality of life; and the Short Form-36 (SF-36) preoperatively and at one year (mean and standard deviation, 54.1 +/- 7.6 weeks) postoperatively. Preoperative expectations were quantified with use of six questions from the Musculoskeletal Outcomes Data Evaluation and Management System (MODEMS) questionnaire. Greater preoperative expectations correlated with better postoperative performance on the SST, DASH, each visual analogue scale, and the SF-36 (p values ranging from <0.0001 to 0.03) as well as with greater improvement from the baseline scores on the DASH and SF-36 (p values ranging from <0.0001 to 0.018). A rigorous multivariate analysis controlling for age, gender, smoking, Workers' Compensation status, symptom duration, number of previous operations, number of comorbidities, tear size, and repair technique confirmed that greater expectations were a significant independent predictor of both better performance at one year and greater improvement on the SST, the DASH, each visual analogue scale, and the SF-36 (p values ranging from <0.001 to 0.042). Patients' preoperative expectations regarding rotator cuff repair are associated with their actual self-assessed outcome. Variations in patient expectations may help to explain divergent results in published series as well as among various patient populations.