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Is the Delay to Surgery for Isolated Hip Fracture Predictive of Outcome in Efficient Systems?

2006· article· en· W2090616770 on OpenAlexaff
Éric Bergeron, Lynne Moore, Jean‐Marie Bamvita, Sebastien Ratte, Charles Gravel, David Clas

Bibliographic record

VenueThe Journal of Trauma: Injury, Infection, and Critical Care · 2006
Typearticle
Languageen
FieldMedicine
TopicHip and Femur Fractures
Canadian institutionsHôpital Charles-Le Moyne
Fundersnot available
KeywordsMedicineComorbidityHip fractureMultivariate analysisAdverse effectSurgeryDemographicsUnivariate analysisCohortSingle CenterInternal medicineOsteoporosis

Abstract

fetched live from OpenAlex

BACKGROUND: Adverse outcomes for patients with isolated hip fracture have been documented when preoperative delay is longer than 48 hours. An efficient system will have the capacity to repair all hip fractures within 48 hours. We hypothesized that in an efficient system, there would be a medical justification for a delay greater than 48 hours. The purpose of this study was to identify the causes and outcome of delay for hip surgery in an efficient system. METHODS: All patients with isolated hip fracture admitted to a regional trauma center from April 1993 to March 2003 were reviewed. Demographics, presence of comorbidity, preoperative delay, complications, and mortality were collected. Univariate and multivariate analysis were carried out. RESULTS: The cohort included 977 patients. Overall mortality was 12.2%. Surgery was performed within 24 hours in 53% of cases and within 48 hours in 87% of cases. The presence of comorbidity partly explained longer (>48 hours) surgical delays. Multivariate analysis revealed that age greater than 65, male sex, and the presence of pulmonary and cardiac comorbid conditions or an active cancer but not surgical delay were associated with mortality and complications. However, surgical delay was associated with longer postsurgical hospital stay, independently of the presence of comorbidity or increasing age. CONCLUSIONS: Preoperative delay does not entail adverse outcomes when the surgery is delayed to allow for treatment of comorbid medical conditions. Preoperative delay is associated with a longer hospital stay. The presence of comorbidity only partly explains preoperative delay and adverse outcomes. A prospective study coding for the severity of comorbid conditions and the justification of the preoperative delay will be required to fully elucidate the link between delay and outcome.

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)0.000
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 score0.062
Threshold uncertainty score0.281

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.018
GPT teacher head0.321
Teacher spread0.302 · 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

Citations85
Published2006
Admission routes1
Has abstractyes

Explore more

Same venueThe Journal of Trauma: Injury, Infection, and Critical CareSame topicHip and Femur FracturesFrench-language works237,207