2013 Neer Award: predictors of failure of nonoperative treatment of chronic, symptomatic, full-thickness rotator cuff tears

Background

The purpose of this study is to help define the indications for rotator cuff repair by identifying predictors of failure of nonoperative treatment.

Methods

A prospective, multicenter, cohort study design was used. All patients with full-thickness rotator cuff tears on magnetic resonance imaging were offered participation. Baseline data from this cohort were used to examine risk factors for failing a standard rehabilitation protocol. Patients who underwent surgery were defined as failing nonoperative treatment. A Cox proportional hazards model was fit to determinethe baseline factors that predicted failure. The dependent variable was time to surgery. The independent variables were tear severity and baseline patient factors: age, activity level, body mass index, sex, Single Assessment Numeric Evaluation score, visual analog scale score for pain, education, handedness, comorbidities, duration of symptoms, strength, employment, smoking status, and patient expectations.

Results

Of the 433 subjects in this study, 87 underwent surgery with 93% follow-up at 1 year and 88% follow-up at 2 years. The median age was 62 years, and 49% were female patients. Multivariate modeling, adjusted for the covariates listed previously, identified patient expectations regarding physical therapy (P < .0001) as the strongest predictor of surgery. Higher activity level (P = .011) and not smoking (P = .023) were also significant predictors of surgery. Conclusion A patient's decision to undergo surgery is influenced more by low expectations regarding the effectiveness of physical therapy than by patient symptoms or anatomic features of the rotator cuff tear. As such, patient symptoms and anatomic features of the chronic rotator cuff tear may not be the best features to use when deciding on surgical intervention. [pdflink url="/pdf/2013NeerAward_PredictorsOfFailureOfNonoperativeTreatment_RotatorCuff.pdf"]

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