ArticleBMC musculoskeletal disorders2022
The combined utilization of predictors seems more suitable to diagnose and predict rotator cuff tears.
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.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
6 citing papers in PubMed.
- Advances in Shoulder Pain Imaging: A Narrative Review of Current Practice and Emerging Trends.Current medical imaging · 2025Article
- Comparison of ultrasound and MRI shows equivalent accuracy and reliability in acromial index measurement.Scientific reports · 2025Article
- Association Between Rotator Cuff Tears and Shoulder MRI Parameters: Importance of Arthroscopic Validation in Coronal Acromiohumeral Interval Measurement.Orthopaedic journal of sports medicine · 2025Article
- The Modified Ultrasound-Assisted Method: A Study of the Correlation between Magnetic Resonance Imaging and the Ultrasound-Assisted Evaluation of the Critical Shoulder Angle.Diagnostics (Basel, Switzerland) · 2024Article
- Possibility of diagnosing rotator cuff tears in areas with scarce medical resources: can non-standard anteroposterior radiographs accurately predict rotator cuff tears?Frontiers in medicine · 2024Article
- Anatomic characteristics of shoulder based on MRI accurately predict incomplete rotator cuff injuries in patients: relevance for predictive, preventive, and personalized healthcare strategies.The EPMA journal · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundMorphological markers presenting the lateral extension of acromion and the greater tuberosity of humerus were proposed to diagnose and predict rotator cuff tears (RCTs) in recent years, but few studies have addressed the combined performance when using two predictors together. As a presence of a RCT may be associated with the impingement caused by both acromion and the greater tuberosity, we believe a combined utilization of predictors could result in a better diagnostic and predictive performance than using a single predictor. The aim of this study is to (i) explore whether the combination is more efficient to predict and diagnose RCTs; (ii) find out which combination is the most superior screening approach for RCTs.
methodsThis was a retrospective study and patients who visited our hospital and were diagnosed with or without partial-thickness or full-thickness RCTs via magnetic resonance imaging from January 2018 to April 2022 were enrolled and classified into two groups respectively. Four predictors, the critical shoulder angle (CSA), the acromion index (AI), the greater tuberosity angle (GTA) and the double-circle radius ratio (DRR) were picked to participate in the present study. Quantitative variables were compared by independent samples t tests and qualitative variables were compared by chi-square tests. Binary logistic regression analysis was used to construct discriminating combined models to further diagnose and predict RCTs. Receiver operating characteristic (ROC) curves were pictured to determine the overall diagnostic performance of the involved predictors and the combined models.
resultsOne hundred and thirty-nine shoulders with RCTs and 57 shoulders without RCTs were included. The mean values of CSA (35.36 ± 4.57 versus 31.41 ± 4.09°, P < 0.001), AI (0.69 ± 0.08 versus 0.63 ± 0.08, P < 0.001), DRR (1.43 ± 0.10 versus 1.31 ± 0.08, P < 0.001) and GTA (70.15 ± 7.38 versus 64.75 ± 7.91°, P < 0.001) were significantly higher in the RCT group than for controls. Via ROC curves, we found the combined model always showed a better diagnostic performance than either of its contributors. Via logistic regression analysis, we found the values of both predictors over their cutoff values resulted in an increasement (20.169-161.214 folds) in the risk of having a RCT, which is more than that by using a single predictor only (2.815 -11.191 folds).
conclusionThe combined utilization of predictors is a better approach to diagnose and predict RCTs than using a single predictor, and CSA together with DRR present the strongest detectability for a presence of RCTs.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.