Prediction of Shoulder Stiffness After Arthroscopic Rotator Cuff Repair.

Abstract

Postoperative shoulder stiffness (POSS) is a prevalent adverse event after arthroscopic rotator cuff repair (ARCR) that is associated with major limitations in everyday activities and prolonged rehabilitation. The purpose was to develop a predictive model for determining the risk of POSS within 6 months after primary ARCR. We hypothesized that sufficient discrimination ability of such a model could be achieved using a local institutional database. Case-control study; Level of evidence, 3. Consecutive primary ARCRs documented in a local clinical registry between 2013 and 2017 were included, and patients who experienced POSS before the final clinical 6-month follow-up were identified. A total of 29 prognostic factor candidates were considered, including patient-related factors (n = 7), disease-related factors (n = 9), rotator cuff integrity factors (n = 6), and operative details (n = 7). We used imputed data for the primary analysis, and a sensitivity analysis was conducted using complete case data. Logistic regression was applied to develop a model based on clinical relevance and statistical criteria. To avoid overfitting in the multivariable model, highly correlated predictors were not included together in any model. A final prognostic model with a maximum of 8 prognostic factors was considered. The model's predictive accuracy was assessed by the area under the receiver operating characteristic curve (AUC). Internal validation was performed using bootstrapping. Of 1330 ARCR cases (N = 1330 patients), 112 (8.4%) patients had POSS. Our final model had a moderate predictive ability with an AUC of 0.67. The predicted risks of POSS ranged from 2.3% to 38.9% and were significantly higher in women; patients with partial tears, low baseline passive shoulder abduction, and lack of tendon degeneration; and when no acromioplasty was performed. A prognostic model for POSS was developed for patients with ARCR, offering a personalized risk evaluation to support the future decision process for surgery and rehabilitation.