Evidence map›Paper›PMID 41393618›Full record

ArticleCureus2025

Radiographic Critical Shoulder Angle Combined With Greater Tuberosity Irregularities and Patient Age Accurately Predicts Rotator Cuff Pathology.

Sharo Naqar, Islam Hamarsheh, Jae Rhee, Anestis Iossifidis

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Article in Cureus, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

Authors and funding

4 authors.

Sharo NaqarTrauma and Orthopaedics, Croydon University Hospital, London, GBR.
Islam HamarshehTrauma and Orthopaedics, Croydon University Hospital, London, GBR.
Jae RheeTrauma and Orthopaedics, Croydon University Hospital, London, GBR.
Anestis IossifidisTrauma and Orthopaedics, Croydon University Hospital, London, GBR.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction The combination of a high critical shoulder angle (CSA), the presence of radiographic greater tuberosity (GT) irregularities, and the patient's age can aid surgeons in diagnosing rotator cuff tears (RCTs). This study aims to assess the usefulness of these simple radiographic measures in a clinical outpatient setting. We hypothesise that a high CSA, together with the presence of GT irregularities and the patient's age, is associated with a high probability of RCT. Methods Radiographs of 150 patients were examined retrospectively. The final cohort consisted of 150 patients: 50 with normal shoulders (group A), diagnosed clinically and radiologically using MRI scan, 50 with subacromial impingement (SAI) (group B), and 50 with RCTs (group C). The CSA was measured electronically on true anteroposterior (AP) shoulder radiographs using a picture archiving and communication system (PACS). The presence of radiographic GT irregularities was also recorded according to the following classification: 0 = normal, 1 = sclerosis, and 2 = irregularity or a bony chip. A senior and one training surgeon took measurements. Mean CSAs were used for analysis, as confirmed by a high interobserver agreement, as determined by an interclass correlation coefficient (ICC) calculation. The p-value was set at 0.05. Results The mean CSA for groups A, B, and C was 32.4 (standard deviation (SD) ± 1.5), 34.8 (SD ± 3.2), and 39.3 (SD ± 3.4), respectively. Statistical analysis showed excellent discrimination between normal and cuff pathology, with an area under the curve (AUC) of 0.881 and an optimal CSA cutoff of 34.6° (sensitivity, 74%; specificity, 92%; accuracy, 80%). We then sought a cutoff between SAI and cuff tears and found 36.9 to be significant (AUC 0.848). CSA of ≥36.9° can differentiate between SAI and cuff tears (sensitivity, 78%; specificity, 76%; accuracy, 77%). Combining the CSA of ≥34.8° with GT of 2 can outstandingly discriminate a cuff tear (AUC 0.920, up from 0.848 with CSA alone). The addition of age can generate further improvement, with an AUC of 0.953 (sensitivity, 80%; specificity, 96%; accuracy, 88%). Conclusion This study shows that at age 40 years, RCT was predicted if CSA ≥ 44.9° (GT = 1) or ≥41.0° (GT = 2); at age 50 years, thresholds were CSA ≥ 42.0° (GT = 1) or ≥38.0° (GT = 2); and at age 60 years, CSA ≥ 39.1° (GT = 1) or ≥35.1° (GT = 2). Applying these age-banded thresholds yielded a sensitivity of 80%, a specificity of 96%, and an overall accuracy of 88%. Therefore, a simple radiograph-based model combining CSA, GT morphology, and age may allow clinicians to stratify patients at the first point of contact, streamlining diagnostic pathways, reducing unnecessary advanced imaging, and guiding early intervention strategies.

Indexed as

critical shoulder anglerotator cuff pathologyrotator cuff tearsshoulder girdlesubacromial impingement

Identifiers

PMID41393618
PMCPMC12699493

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