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AIM: Rotator cuff tears (RCTs) are a major cause of shoulder pain and disability, affecting millions worldwide. Understanding the risk factors and developing reliable predictive measures for RCTs is essential for early diagnosis, targeted prevention, and effective treatment of this patient population. This study seeks to enhance our understanding by analyzing the acromiohumeral distance (AHD) and Constant-Murley Score (CMS) in patients with and without RCTs, thereby aiding the development of a predictive model aimed at improving clinical outcomes and prevention strategies in rotator cuff pathology. METHODS: This retrospective analysis involved 201 patients with shoulder pain, categorized into RCT (n = 72) and no RCTs (N-RCTs, n = 129) groups based on Magnetic Resonance Imaging (MRI) findings. We compared demographics, AHD, CMS, and rotator cuff status between groups and utilized logistic regression for identifying RCT predictors, leading to the development of a multifactorial predictive model. RESULTS: The mean AHD was 6.60 ± 1.12 mm. The RCT group showed a marginally higher AHD than the N-RCT group (p = 0.669). CMS scores were significantly lower in the RCT group (p < 0.001). Dominant side involvement (Odds Ratio (OR) 2.244), type III acromion (OR 6.106), and lower CMS (OR 0.938) significantly correlated with RCTs. The predictive model demonstrated an area under the curve (AUC) of 0.701 for RCT diagnosis. CONCLUSIONS: Reduced CMS, dominance of the affected side, and type III acromion emerged as key risk factors for RCTs. Our predictive model, incorporating these factors, holds promise for RCT diagnosis, with future studies needed for further validation.
Xu et al. (Tue,) studied this question.