ArticleBMC musculoskeletal disorders2022
Identifying key factors associated with subscapularis tendon tears and developing a risk prediction model to assist diagnosis.
Article in BMC musculoskeletal disorders, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 2 of them syntheses that pooled it.
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Who cites it
6 citing papers in PubMed, 2 syntheses or guidelines pooled it, 10 citations in OpenAlex.
- Which radiological parameters of the coracoid process influence the diagnosis of atraumatic subscapularis tears? Systematic review and meta-analysis.European journal of orthopaedic surgery & traumatology : orthopedie traumatologie · 2025Pooled it
- Clinical Approach to Inconclusive Subscapularis Tear Diagnosis: a Meta-analysis.International journal of sports medicine · 2024Pooled it
- Subscapularis Partial Thickness Tears by Yoo and Rhee Classification: Identifying MRI Predictors for Type IIB, Requiring Surgical Repair.Diagnostics (Basel, Switzerland) · 2025Article
- Defining surgical indications in subcoracoid cysts: 3D volumetric analysis and elastography guide tendon-preserving arthroscopic decompression.BMC musculoskeletal disorders · 2025Article
- The impact of supraspinatus tear on subscapularis muscle atrophy and fatty infiltration.Clinics in shoulder and elbow · 2024Article
- Preoperative Shoulder MRI Findings to Predict Subscapularis Tendon Tear Requiring Surgical Repair.Journal of the Korean Society of Radiology · 2024Article
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Authors and funding
3 authors at 1 institution in 1 country.
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No grant is acknowledged in the PubMed record.
Abstract
backgroundThere are still some challenges in diagnosing subscapularis (SSC) tendon tears as accurately as posterosuperior rotator cuff tears on MRI. The omission of SSC tendon tear can lead to muscle atrophy, fatty infiltration, and increased tearing accompanied by aggravated shoulder pain and loss of function. An effective non-invasive evaluation tool will be beneficial to early identification and intervention. The study aims to identify sensitive predictors associated with SSC tendon tears and develop a risk prediction model to assist in diagnosis.
methodsData on 660 patients who received shoulder arthroscopic surgery with preoperative shoulder MRI were collected retrospectively. Of these, patients with SSC tendon tears were defined as the SSC tear group, and patients with intact SSC tendon were enrolled in the non-SSC tear group. Logistic regression analysis was used to identify the key predictors of SSC tendon tears which were then incorporated into the nomogram.
resultsAmong 22 candidate factors, five independent factors including coracohumeral distance (CHD, oblique sagittal plane) (OR, 0.75; 95%CI, [0.67-0.84]), fluid accumulation (Y-face) (OR, 2.29; 95%CI, [1.20-4.38]), long head of biceps tendon (LHB) dislocation/subluxation (OR, 3.62; 95%CI, [1.96-6.68]), number of posterosuperior (PS) rotator cuff tears (OR, 5.36; 95%CI, [3.12-9.22]), and MRI diagnosis (based on direct signs) (OR, 1.88; 95%CI, [1.06-3.32]) were identified as key predictors associated with SSC tendon tears. Incorporating these predictors, the nomogram achieved a good C index with a good agreement on the risk estimation of calibration plots. Higher total points of the nomogram were associated with a greater risk of SSC tendon tears.
conclusionWhen evaluating the severity of SSC tendon injury, the combination of reliable predictors can improve the sensitivity and diagnostic performance of MRI. This model provides an individualized probability of risk prediction, which is convenient for clinicians to identify patients at high risk for SSC tendon tears to avoid missed diagnosis.
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