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Record W3011599327 · doi:10.1097/jom.0000000000001841

Association of Disability Benefits and/or Litigation With Time to Return to Work After Tibia Shaft Fracture Fixation

2020· article· en· W3011599327 on OpenAlexafffund
Yasir Rehman, Aaron Jones, Kim Madden, Diane Heels‐Ansdell, Jason W. Busse

Bibliographic record

VenueJournal of Occupational and Environmental Medicine · 2020
Typearticle
Languageen
FieldMedicine
TopicBone fractures and treatments
Canadian institutionsMcMaster University
FundersCanadian Institutes of Health Research
KeywordsMedicinePhysical therapyPolytraumaHazard ratioTibiaConfidence intervalSurgeryInternal medicine

Abstract

fetched live from OpenAlex

OBJECTIVES: We explored the association of compensation status with return to work (RTW) after tibial fracture. METHODS: Eligible patients were adults with tibial shaft fractures enrolled in the Trial to Re-evaluate Ultrasound in the Treatment of Tibial Fractures. We explored the association between disability benefits and/or litigation and RTW using multivariable discrete interval hazard analysis, adjusting for sex, age, country of residence, smoking status, body mass index, polytrauma, fracture severity, fracture gap, pain severity, and physical functioning. RESULTS: Of 330 eligible patients, 111 (34%) had not returned to full-time work 1-year after surgery. In our adjusted model, receipt of disability benefits and/or involvement in litigation was associated with delayed RTW (HR = 0.71, 95% CI 0.52-0.96). DISCUSSION: Tibial shaft fracture patients receiving disability benefits and/or involved in litigation are less likely to RTW.

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)0.002
metaresearch head score (Gemma)0.015
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.015
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.012
GPT teacher head0.248
Teacher spread0.236 · 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 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

Citations3
Published2020
Admission routes2
Has abstractyes

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