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Record W2266567687 · doi:10.1177/0363546515624467

Is There a Genetic Predisposition to Anterior Cruciate Ligament Tear? A Systematic Review

2016· review· en· W2266567687 on OpenAlexaffabout
Rakesh John, Mandeep Singh Dhillon, Siddhartha Sharma, Sharad Prabhakar, Mohit Bhandari

Bibliographic record

VenueThe American Journal of Sports Medicine · 2016
Typereview
Languageen
FieldMedicine
TopicKnee injuries and reconstruction techniques
Canadian institutionsMcMaster University
Fundersnot available
KeywordsMedicineAnterior cruciate ligamentACL injuryTearsGenetic predispositionCandidate geneSurgeryInternal medicineGeneGeneticsDisease

Abstract

fetched live from OpenAlex

BACKGROUND: Injuries to the anterior cruciate ligament (ACL) are among the most common knee ligament injuries and frequently warrant reconstruction. The etiopathogenesis of these injuries has focused mainly on mechanism of trauma, patient sex, and anatomic factors as predisposing causes. Several genetic factors that could predispose to an ACL tear have recently been reported. PURPOSE: This systematic review summarizes the current evidence for a genetic predisposition to ACL tears. The principal research question was to identify genetic factors, based on the available literature, that could predispose an individual to an ACL tear. STUDY DESIGN: Systematic review. METHODS: The PubMed, EMBASE, Cochrane, and HuGE databases were searched; the search was run from the period of inception until June 21, 2015. A secondary search was performed by screening the references of full-text articles obtained and by manually searching selected journals. Articles were screened with prespecified inclusion criteria. The quality of studies included in the review was assessed for risk of bias by 2 reviewers using the Newcastle-Ottawa Scale. RESULTS: A total of 994 records were identified by the search, out of which 17 studies (16 case-control studies and 1 cross-sectional study) were included in the final review. Two studies observed a familial predisposition to an ACL tear. Fourteen studies looked at specific gene polymorphisms in 20 genes, from which different polymorphisms in 10 genes were positively associated with an ACL tear. In addition to these polymorphisms, 8 haplotypes were associated with ACL tear. One study looked at gene expression analysis. CONCLUSION: Although specific gene polymorphisms and haplotypes have been identified, it is difficult to come to a conclusion on the basis of the existing literature. Several sources of bias have been identified in these studies, and the results cannot be extrapolated to the general population. More studies are needed in larger populations of different ethnicities. Gene-gene interactions and gene expression studies in the future may delineate the exact role of these gene polymorphisms in ACL tears.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.712
Threshold uncertainty score0.722

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0080.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.015
GPT teacher head0.339
Teacher spread0.325 · 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 teacher head, 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

Citations53
Published2016
Admission routes2
Has abstractyes

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