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Record W2901816716 · doi:10.22374/cjgim.v13i4.272

Emerging Barrier to Timely Care of Hip Fracture Patients: A Prospective Study of Direct Oral Anticoagulation and Time to Surgery

2018· article· en· W2901816716 on OpenAlexaffvenue
Marlis T. Sabo, Fatima Mahdi

Bibliographic record

VenueCanadian Journal of General Internal Medicine · 2018
Typearticle
Languageen
FieldMedicine
TopicAtrial Fibrillation Management and Outcomes
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsMedicineHip fractureAtrial fibrillationIncidence (geometry)Prospective cohort studyWarfarinSurgeryInternal medicineOsteoporosis

Abstract

fetched live from OpenAlex

Rapid surgical management of hip fracture patients is critical to reduce morbidity and mortality. These patients may be anticoagulated and the new direct oral anticoagulants (DOAC) may introduce delays to treatment. Our purpose was to examine the impact of these DOAC on time to surgical management for hip fracture patients. Methods A prospective audit of 55 consecutive operative hip fracture patients examined time from diagnosis to surgery. Indications for anticoagulation were recorded. Results Time to surgery for the DOAC group was 66±16 hours, versus 38±21 and 25±19 hours for warfarin and control groups, respectively (P<0.05). Anticoagulation was for atrial fibrillation in 93%. Conclusion Patients on DOAC faced significant delays to surgery. Given that both DOAC use and incidence of hip fracture are expected to rise, this presents a barrier to optimized care in this vulnerable group.

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)0.001
metaresearch head score (Gemma)0.009
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 score0.018
Threshold uncertainty score0.035

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.027
GPT teacher head0.312
Teacher spread0.285 · 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

Citations9
Published2018
Admission routes2
Has abstractyes

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