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Record W2604871989 · doi:10.1136/ebmed-2017-110683

Close contact casting may result in similar outcomes compared with plate fixation for unstable ankle fractures in patients over 60 years old

2017· letter· en· W2604871989 on OpenAlexaff
Alastair Younger

Bibliographic record

VenueEvidence-Based Medicine · 2017
Typeletter
Languageen
FieldMedicine
TopicFoot and Ankle Surgery
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsMedicineAnkleInternal fixationSurgeryRandomized controlled trial

Abstract

fetched live from OpenAlex

Commentary on: Willett K , Keene DJ , Mistry D , et al . Close contact casting vs surgery for initial treatment of unstable ankle fractures in older adults: a randomized clinical trial. JAMA 2016;316:1455–63.[OpenUrl][1] Surgery has been considered the mainstay of treatment for unstable ankle fractures. Early mobilisation and weight bearing is possible with stable anatomic fracture fixation (open reduction internal fixation (ORIF)). Surgery also increases the risk of wound problems. This study compared outcomes among older adults with ankle fractures who received ORIF versus close contact casting. This study was prospective, powered and randomised to determine the outcomes at 6 months of adults aged 60 years or older using the Olerund-Molander Ankle Score (OMAS). Patients were randomised to casting or surgery (ORIF) in a 1:1 ratio. The surgeons were trained in the casting technique before the study. If casting failed and the patient underwent ORIF, … [1]: {openurl}?query=rft.jtitle%253DJAMA%26rft.volume%253D316%26rft.spage%253D1455%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmano category
Domain: not available · Genre: Editorial
About the Canadian research system: no · About a Canadian topic: no
Non-randomized triallow
gptno category
Domain: not available · Genre: Commentary
About the Canadian research system: no · About a Canadian topic: no
Not applicablemedium
models splitAgreement compares identical category sets and study designs across arms.

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)0.004
metaresearch head score (Gemma)0.068
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.021
Threshold uncertainty score0.070

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.068
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.003
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0060.004
Insufficient payload (model declined to judge)0.0210.003

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 head0.062
GPT teacher head0.332
Teacher spread0.270 · 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

Labeled directly by 2 models reading the full record.

The models applied no category: nothing in the taxonomy fit this work.

The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.

Study designNon-randomized trial · Not applicable
Domainnot available
GenreEditorial · Commentary

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

Citations2
Published2017
Admission routes1
Has abstractyes

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