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Record W2622588708 · doi:10.2106/jbjs.16.00788

Outcomes of After-Hours Hip Fracture Surgery

2017· article· en· W2622588708 on OpenAlexaff
Daniel Pincus, Sagar Desai, David Wasserstein, Bheeshma Ravi, Michael J. Paterson, Patrick Henry, Hans J. Kreder, Richard Jenkinson

Bibliographic record

VenueJournal of Bone and Joint Surgery · 2017
Typearticle
Languageen
FieldMedicine
TopicHip and Femur Fractures
Canadian institutionsHealth Sciences CentreSunnybrook Health Science CentreInstitute for Clinical Evaluative SciencesUniversity of Toronto
Fundersnot available
KeywordsMedicineHip fractureSurgeryFemoral neckOdds ratioLogistic regressionOsteoporosisInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Given single-institution studies showing trends between after-hours hip fracture surgical procedures and adverse outcomes, as well as fixation time targets that may increasingly compel after-hours operations, we investigated the relationship between after-hours hip fracture surgical procedures and adverse outcomes in a large, population-based cohort. METHODS: All Ontarians who were ≥60 years of age and underwent a hip fracture surgical procedure between April 2002 and March 2014 were eligible for study inclusion. Data were obtained from linked health administrative databases. The primary exposure was after-hours provision of surgical procedures, occurring weekday evenings between the hours of 5 P.M. and 12 A.M. or over the weekend, but not overnight (after 12 A.M. to 7 A.M.). Surgical complications up to 6 months following a hip fracture surgical procedure comprised the primary outcome. Medical complications, including mortality, up to 90 days postoperatively were also assessed. Odds ratios (ORs) were calculated using a logistic regression model that accounted for clustering at the hospital level and adjusted for patient, provider, and fracture characteristics previously shown to explain the majority of variance in hip fracture outcomes. RESULTS: During the study period, 87,647 patients underwent an isolated hip fracture surgical procedure; 51.2% of these patients had femoral neck fractures, 44.1% had intertrochanteric fractures, and 4.7% had subtrochanteric fractures. The surgical procedure occurred after hours in 59,562 patients (68.0%), and 27,240 patients (31.1%) underwent a surgical procedure during normal hours (7 A.M. to 5 P.M.). Only 845 patients (1%) underwent a surgical procedure overnight. We observed no significant relationships between timing of the surgical procedure and adverse outcomes, except for patients who had undergone an after-hours surgical procedure and had fewer inpatient surgical complications (OR, 0.90 [95% confidence interval, 0.83 to 0.99]; p = 0.01). CONCLUSIONS: Adverse outcomes following a hip fracture surgical procedure were similar whether a surgical procedure occurred during normal hours or after hours. Concerns regarding the quality of after-hours surgical procedures should not influence hip fracture prioritization policy. However, given that the great majority of hip fracture surgical procedures occurred after hours, future research should examine other potential consequences of this practice, such as financial impact and surgeon burnout. LEVEL OF EVIDENCE: Therapeutic Level III. See Instructions for Authors for a complete description of levels of evidence.

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)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation 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 score0.024
Threshold uncertainty score0.422

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
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 head0.033
GPT teacher head0.284
Teacher spread0.251 · 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.

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

Citations39
Published2017
Admission routes1
Has abstractyes

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