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Record W4391441069 · doi:10.1177/03635465231187039

Return to Sport After Pediatric Anterior Cruciate Ligament Reconstruction: A Systematic Review of the Criteria

2024· review· en· W4391441069 on OpenAlexaff
Justin-Pierre Lorange, Laurianne Senécal, Philippe Moisan, Marie‐Lyne Nault

Bibliographic record

VenueThe American Journal of Sports Medicine · 2024
Typereview
Languageen
FieldMedicine
TopicKnee injuries and reconstruction techniques
Canadian institutionsCentre Hospitalier Universitaire Sainte-JustineCentre Intégré Universitaire de Santé et de Services Sociaux du Centre-Sud-de-l'Île-de-MontréalHôpital du Sacré-Cœur de MontréalUniversité de MontréalMcGill University Health Centre
Fundersnot available
KeywordsMedicineAnterior cruciate ligament reconstructionMilestoneInclusion and exclusion criteriaPhysical therapyRehabilitationAnterior cruciate ligamentPopulationSports medicineEvidence-based medicineMEDLINEProspective cohort studySurgeryAlternative medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Postoperative rehabilitation is an important component of recovery after anterior cruciate ligament (ACL) reconstruction (ACLR), facilitating successful return to sport (RTS) by reducing risk factors for repeat injury. PURPOSE: This systematic review aimed to determine the best protocol for RTS after ACLR in children. STUDY DESIGN: Systematic review; Level of evidence, 4. METHODS: PubMed, Embase, PEDro, SPORTDiscus, and Web of Science databases were searched from October 3, 2014, to November 3, 2022. The inclusion criteria were the pediatric population (<18 years old) after ACLR with clear RTS criteria and/or mean/median time to RTS. Multiligament knee injuries were excluded from this study. The methodologic quality of the included articles was assessed using the methodological index for non-randomized studies (MINORS). The highest possible score was 24 points for comparative studies (ie, a study comparing 2 protocols or more). Noncomparative studies or studies with a single protocol could score a maximum of 16 points as assessed by the MINORS score. RESULTS: The search yielded 1816 titles, and 24 were retained based on the inclusion and exclusion criteria. Every study was published between 2015 and 2022. Among the 24 studies included, 13 were retrospective and 11 were prospective. The mean MINORS score for the noncomparative studies was 13 of 16 (n = 23) and 23 of 24 for the comparative study (n = 1). The studies were categorized into unspecified clearance (n = 10), milestone based (n = 13), and combined time and milestone (n = 1). A total of 1978 patients (57% female) were included in the review. The mean age at ACLR was 14.7 years. The most common endpoint used was graft rupture (0% to 35%). In the unspecified group, the quickest RTS was 5.8 months and the longest was 9.6 months. Statistically significant risk factors for ACL reinjury included younger age and earlier RTS. The latter was a significant contributor to graft failure for combined time-based and milestone-based RTS. In the milestone-based group, the most common criteria were ≥90% limb symmetry measured using hamstring strength, quadriceps strength, and/or hop tests. The mean RTS time was 6.8 to 13.5 months. CONCLUSION: RTS should be delayed, when possible, especially in the younger population. A combination of quantitative tests and qualitative tests is also recommended. However, optimal RTS criteria have yet to be determined. Future prospective studies should focus on comparing the different times and milestones currently available.

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)0.022
metaresearch head score (Gemma)0.083
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 score0.022
Threshold uncertainty score0.118

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0220.083
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0130.009
Bibliometrics0.0220.021
Science and technology studies0.0020.002
Scholarly communication0.0040.004
Open science0.0040.003
Research integrity0.0030.001
Insufficient payload (model declined to judge)0.0060.001

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 head0.013
GPT teacher head0.336
Teacher spread0.323 · 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

Citations16
Published2024
Admission routes1
Has abstractyes

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