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Record W2921215081 · doi:10.1136/jisakos-2018-000255

Critical shoulder angle is an effective radiographic parameter that is associated with rotator cuff tears and osteoarthritis: a systematic review

2019· review· en· W2921215081 on OpenAlexaff
Gabriel M. Kuper, Ajaykumar Shanmugaraj, Nolan S. Horner, Seper Ekhtiari, Nicole Simunovic, Edwin R. Cadet, Olufemi R. Ayeni

Bibliographic record

VenueJournal of ISAKOS Joint Disorders & Orthopaedic Sports Medicine · 2019
Typereview
Languageen
FieldMedicine
TopicShoulder Injury and Treatment
Canadian institutionsMcMaster University
Fundersnot available
KeywordsMedicineRotator cuffIntraclass correlationOsteoarthritisTearsRadiographyPhysical therapyReliability (semiconductor)SurgeryPathologyPsychometrics

Abstract

fetched live from OpenAlex

Importance The critical shoulder angle (CSA) is a relatively new radiographic parameter correlated with pathologies such as rotator cuff tears and osteoarthritis. Objective The purpose of this systematic review was to: (1) determine the degree of correlation between the CSA and shoulder pathologies, (2) determine the reliability of measuring CSA between (inter-rater reliability) and within (intrarater reliability) clinicians, (3) assess the accuracy of different imaging modalities used for measuring the CSA and (4) determine the association of CSA with patient outcomes after surgery. Evidence review The electronic databases MEDLINE, EMBASE and PubMed were searched in March 2018 for relevant studies. The results are presented in a narrative summary. Findings A total of 26 studies and 4563 patients satisfied the inclusion criteria. The majority of CSAs were measured using radiographs (98.2%) in neutral rotation (72.9%). Significant associations (p<0.05) were found between lower CSAs (<30°) and osteoarthritis, and higher CSAs (>35°) with primary rotator cuff tears and the risk of re-tear following a repair. The CSA has excellent intrarater (intraclass correlation coefficient (ICC) 0.903 to 0.996) and inter-rater reliability (ICC 0.869 to 0.980) when measured with radiographs. High variability in measurements was found when using MRI. The CSA, however, is not a clear, significant independent predictor (p>0.05) of outcomes after the surgical management of shoulder pathologies. Conclusions and relevance The CSA is an effective radiographic parameter that is associated with rotator cuff tears and osteoarthritis. Lower CSAs (<30°) are associated with osteoarthritis, whereas higher CSAs (>35°) are associated with primary rotator cuff tears and re-tear after arthroscopic repair. Currently, there is a limited predictive value of the CSA in patient-reported outcomes after rotator cuff repair. The CSA is measured with high intrarater and inter-rater reliability for both radiographs and CT scans. Measuring the CSA using radiographs with the arm in the neutral rotation is currently recommended. Future studies are required to further investigate how best use the CSA to guide patient management and its predictive value. Level of evidence IV.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.015
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.007
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.015
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0050.004
Bibliometrics0.0070.006
Science and technology studies0.0000.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.032
GPT teacher head0.332
Teacher spread0.301 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations4
Published2019
Admission routes1
Has abstractyes

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