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Record W3217477982 · doi:10.1136/bjsports-2021-ioc.86

090 Joint hypermobility in athletes is associated with shoulder injury and shoulder pain: a systematic review and meta-analysis

2021· review· en· W3217477982 on OpenAlexaffabout
Behnam Liaghat, Julie Rønne Pedersen, Jonas Bloch Thorlund, Birgit Juul‐Kristensen, Carsten Bogh Juhl

Bibliographic record

VenuePoster presentations · 2021
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicConnective tissue disorders research
Canadian institutionsCanadian Memorial Chiropractic College
Fundersnot available
KeywordsJoint hypermobilityHypermobility (travel)MedicineAthletesPhysical therapyMeta-analysisOdds ratioPhysical medicine and rehabilitationInternal medicine

Abstract

fetched live from OpenAlex

Background Joint hypermobility in athletes is associated with increased risk of knee injuries, but currently it is unclear if joint hypermobility is associated with increased risk of shoulder injuries. Objective To assess the association between joint hypermobility and shoulder injuries in athletes. Design Systematic review and meta-analysis. Odds ratios (OR) for having shoulder injuries in exposed (joint hypermobility) athletes compared with non-exposed (without joint hypermobility) athletes were estimated using a random effects meta-analysis. We performed subgroup analyses to explore the effect of sex, type of sport, sports level, study type, risk of bias, and exposure definition (generalised joint hypermobility (GJH) or shoulder joint hypermobility). Risk of bias was assessed using Newcastle-Ottawa Scale, and overall quality of evidence using Grading of Recommendations Assessment, Development and Evaluation. Setting Recreational and elite sports settings or military settings. Patients (or Participants) Athletes (all sports) and military personnel above 16 years of age. Interventions (or Assessment of Risk Factors) Exposure: GJH or shoulder joint hypermobility. Main Outcome Measurements Acute shoulder injury or activity-related shoulder pain. Results In total, 2,496 participants (31.9% females, mean age 19.9 years) from seven studies were included. Athletes with joint hypermobility were more likely to have shoulder injuries (OR = 3.41, 95% CI 1.88, 6.21, I2 = 71.5%) than athletes without joint hypermobility. Exposure definition had large impact on estimates (GJH, OR = 1.97, 95% CI 1.32, 2.94; shoulder joint hypermobility, OR = 6.79, 95% CI 3.91, 11.80; p=0.002), while remaining subgroup analyses showed no differences. The overall quality of evidence was low. Conclusions We found 3-fold higher odds of shoulder injuries among athletes with joint hypermobility compared with non-exposed athletes. Due to low quality of evidence, future research may change the effect estimate. These findings highlight the need for prevention of shoulder injuries in athletes with joint hypermobility.

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)0.009
metaresearch head score (Gemma)0.026
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.013
Threshold uncertainty score0.046

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.026
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0130.031
Bibliometrics0.0050.005
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0020.001
Research integrity0.0020.002
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 head0.118
GPT teacher head0.400
Teacher spread0.282 · 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 designMeta-analysis
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

Citations0
Published2021
Admission routes2
Has abstractyes

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