Evidence map›Paper›PMID 39474192›Full record

ArticleJSES reviews, reports, and techniques2024

Glenohumeral capsular injury rate in patients with glenohumeral instability: a systematic review and meta-analysis.

Robert T Tisherman, Emily Luo, Damon Briggs, Clark Bulleit, Gabrielle Fatora, Brian Lau

Abstract read
In one paragraph

Article in JSES reviews, reports, and techniques, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Robert T TishermanDepartment of Orthopaedic Surgery, Duke University Hospital, Durham, NC, USA.
Emily LuoDepartment of Orthopaedic Surgery, Duke University Hospital, Durham, NC, USA.
Damon BriggsDepartment of Orthopaedic Surgery, Duke University Hospital, Durham, NC, USA.
Clark BulleitDepartment of Orthopaedic Surgery, Duke University Hospital, Durham, NC, USA.
Gabrielle FatoraDepartment of Orthopaedic Surgery, UPMC, Pittsburgh, PA, USA.
Brian LauDepartment of Orthopaedic Surgery, Duke University Hospital, Durham, NC, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Glenohumeral instability is a complex clinical problem with underlying pathology in the bony, labral, and capsular tissues. The rate of specific capsular injuries varies widely in the literature and the clinical importance of these specific injury patterns remains unclear. Methods: Following Preferred Reporting Items for Systematic Review and Meta-Analysis guidelines, a systematic review was performed of multiple databases for all primary research articles between 2008 and 2023 which included advanced imaging and included rates of capsular injury in patients with glenohumeral instability. Results: Twelve studies met inclusion criteria. The most prevalent capsular injury seen was in the inferior glenohumeral ligament (34.1%) across all studies, followed by anterior labroligamentous periosteal sleeve avulsions with 24.9% prevalence. Humeral avulsions of the glenohumeral ligaments lesions were the least common (6.2%) of subjects, followed closely by capsular tears (8.3%) of subjects. Conclusion: Capsular injury is commonly seen in magnetic resonance imaging of patients with anterior shoulder instability. Significant heterogeneity in language and imaging techniques was found in the existing literature. Further research is needed to explore these specific capsular lesions' clinical implications and rehabilitation strategies.

Indexed as

Capsular imagingGlenohumeral capsuleGlenohumeral instabilityMR arthrogramShoulder instabilitySystematic review

Identifiers

PMID39474192
PMCPMC11514087

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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.