Evidence map›Paper›PMID 42718621›Full record

ArticleAsia-Pacific journal of sports medicine, arthroscopy, rehabilitation and technology2026

Prediction of massive rotator cuff tears classified as type B or C in the Collin classification using radiographic measurements.

Lee-Chia Liu, Hao-Chun Chuang, Kai-Lan Hsu, Fa-Chuan Kuan, Wei-Ren Su, Chih-Kai Hong

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Article in Asia-Pacific journal of sports medicine, arthroscopy, rehabilitation and technology, 2026. 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

6 authors.

Lee-Chia LiuDepartment of Orthopaedic Surgery, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan, Taiwan.
Hao-Chun ChuangDepartment of Orthopaedics, Tainan Municipal Hospital (managed by Show Chwan Medical Care Corporation), Tainan, Taiwan.
Kai-Lan HsuDepartment of Orthopaedic Surgery, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan, Taiwan.
Fa-Chuan KuanDepartment of Orthopaedic Surgery, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan, Taiwan.
Wei-Ren SuDepartment of Orthopaedic Surgery, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan, Taiwan.
Chih-Kai HongDepartment of Orthopaedic Surgery, National Taiwan University Hospital, College of Medicine, National Taiwan University, Taipei, Taiwan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Superior humeral head migration is a feature of advanced rotator cuff tears, but conventional radiographic measurements such as the acromiohumeral interval (AHI) have limitations. Evidence predicting massive tears like Collin type B or C remains scarce. This study aimed to develop and validate the acromion-humeral angle (AHA) as a novel parameter for assessing superior humeral head migration and compare its diagnostic value with the AHI. Methods: The study involved a retrospective review of 65 patients with confirmed rotator cuff tears, diagnosed between 2012 and 2016, after conservative treatment had failed. Patients underwent preoperative radiographic evaluations, and surgeries were performed by a senior surgeon. Three radiological parameters were measured: the AHI; acromion-humeral angle (AHA); and its subcomponents (A1, A2). Reliability was assessed using ICC, and statistical analyses, including logistic regression and ROC curve(Receiver operating characteristic curve) analysis, were conducted to evaluate diagnostic accuracy. Results: The study involved an analysis of 65 participants (32 men, 33 women; mean age, 59.2 years) with 68 shoulders diagnosed with rotator cuff tears. Collin type B/C tears were observed in 27 shoulders (49.3%). Interobserver reliability for A1, A2, and AHI measurements showed excellent agreement (ICC > 0.75). Radiological evaluations and simple logistic regression indicated that the A1-A2 ratio provided the highest accuracy for detecting Collin B/C tears (AUC = 0.80, likelihood ratio = 18.06, p < 0.001. An AHI < 7.9 mm (odds ratio = 9, p < 0.001) and A1-A2 ratio > 1.52 significantly increased the likelihood of Collin B/C tears (odds ratio = 6.28, p = 0.002). Conclusion: The A1-A2 ratio is a reliable radiographic parameter for predicting Collin type B or C massive rotator cuff tears, with diagnostic performance comparable to the AHI. It serves as a useful alternative or complementary measure for assessing superior humeral migration. An A1-A2 ratio greater than 1.52 is associated with an approximately 6.3-fold increased risk of Collin type B or C massive rotator cuff tears. Level of evidence: III, Cohort study.

Indexed as

Acromiohumeral intervalAcromion-humeral angleCollin classificationMassive rotator cuff tearRotator cuff tearShoulder

Identifiers

PMID42718621
PMCPMC13553585

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.