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Record W4291895619 · doi:10.1016/j.asmr.2022.07.001

Wide Variability in Return‐to‐Sport Criteria used by Team Physicians After Anterior Cruciate Ligament Reconstruction in Elite Athletes—A Qualitative Study

2022· article· en· W4291895619 on OpenAlexaff
Marcel Betsch, Ali Darwich, Justin Chang, Daniel B. Whelan, Darrell Ogilvie‐Harris, Jaskarndip Chahal, John Theodoropoulos

Bibliographic record

VenueArthroscopy Sports Medicine and Rehabilitation · 2022
Typearticle
Languageen
FieldMedicine
TopicKnee injuries and reconstruction techniques
Canadian institutionsWomen's College HospitalUniversity of Toronto
Fundersnot available
KeywordsRehabilitationPsychologyQualitative researchFeelingAnterior cruciate ligament reconstructionApplied psychologyAthletesPhysical therapyMedicineAnterior cruciate ligamentSocial psychologySurgery

Abstract

fetched live from OpenAlex

Purpose: The purpose of this study is to explore currently used readiness to return to sport (RTS) criteria after anterior cruciate ligament reconstruction (ACLR) used in elite athletes to gain novel insights into the RTS decision-making process of professional team physicians. Methods: Eighteen qualitative semistructured interviews with professional team physicians were conducted by a single trained interviewer. The interviews were used to identify team physician concepts and themes regarding the criteria used to determine RTS after ACLR. General inductive analysis and a coding process were used to identify themes and subthemes arising from the data. A hierarchical approach in coding helped to link themes. Results: The most important RTS criteria included muscle strength, followed by satisfactory functional testing including hop tests, a satisfactory clinical examination, joint stability, psychological readiness, time since the ACLR surgery, absence of joint effusion, subjective feeling of knee stability, pain-free return to sporting movements, completion of a sport-specific rehabilitation, and at last allied team support. Conclusions: This study identified 4 main themes, including (1) objective findings, (2) informative feedback of the team members, (3) subjective findings, and (4) type of sport and time to surgery as having the most influence on RTS decision after ACLR. However, interviews showed that even among professional team physicians, the main criteria to RTS in these categories were inconsistent. A definitive set of conclusive guidelines could not be established and would be a fruitful and useful area for future research through further quantitative studies and international consensus meetings along the foundation of the presenting study. Level of Evidence: V, evidence-based practices, qualitative study.

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)0.004
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.143
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.007
GPT teacher head0.322
Teacher spread0.315 · 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.

Study designObservational
Domainnot available
GenreEmpirical

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

Citations13
Published2022
Admission routes1
Has abstractyes

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