Year: 2025
Type: article
Study design: Observational Study
Abstract: Background Previous studies have successfully generated models for predicting retears after arthroscopic rotator cuff repair (RCR), but few models for predicting functional improvement have been developed. The purpose of this study was to evaluate factors influencing physical function after RCR and to create a model for predicting minimal clinically important difference (MCID) achievement. Methods A retrospective review of 221 patients undergoing arthroscopic RCR from May 2021 to February 2023 was performed. The primary outcome was achievement of MCID on the patient-reported outcomes measurement information system physical function (PROMIS-PF) instrument at 6 months postoperatively. A logistic regression model was generated to evaluate the association between demographics, comorbidities, surgical details, and MCID achievement. Results The following variables were retained as they improved model fit: age, sex, race, American Society of Anesthesiologists score, tear size, number of tendons, concomitant subacromial decompression, and baseline PROMIS-PF score. After controlling all other factors, only full-thickness tears were associated with increased odds of MCID achievement (odds ratio [OR] = 4.45, P = .002). Factors associated with decreased odds of MCID achievement included non-White race (OR = 0.32, P = .017), American Society of Anesthesiologists score ≥3 (OR = 0.39, P = .027), subacromial decompression (OR = 0.30, P = .043), and higher baseline PROMIS-PF (OR = 0.86, P < .001). The area under the curve of the model was 0.788, indicating moderate predictive accuracy. Conclusion At 6-month follow-up, 59% of patients undergoing arthroscopic RCR achieved MCID on the PROMIS-PF instrument. Using 8 variables, MCID achievement could be predicted with approximately 79% accuracy. These findings may aid surgeons in patient selection and managing patient expectations.
Source: JSES International
Institution: Anne Arundel Medical Center
Language: English
Subfield: Surgery
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $1,250
OpenAlex ID: W4407171924
