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Record W1517962512

In-hospital mortality following hip fracture care in southern Ontario.

2010· article· en· W1517962512 on OpenAlexaffabout
Khalid Alzahrani, Rajiv Gandhi, Aileen M. Davis, Nizar Mahomed

Bibliographic record

VenuePubMed · 2010
Typearticle
Languageen
FieldMedicine
TopicHip and Femur Fractures
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMedicineHip fractureIncidence (geometry)AmbulatoryPopulationHealth careResidenceEpidemiologyAmbulatory careEmergency medicineOsteoporosisDemographySurgeryEnvironmental healthInternal medicine
DOInot available

Abstract

fetched live from OpenAlex

BACKGROUND: The incidence of hip fractures is increasing within the aging population. We investigated the overall rate of in-hospital mortality following hip fracture and how this mortality rate compares across academic and community hospitals. METHODS: We reviewed prospectively collected data from 17 hospitals in southern Ontario as part of a project to evaluate a new streamlined clinical care pathway developed for acute care of elderly patients with hip fractures. We collected demographic data, prefracture living status, acute care mortality and time to surgery, and we compared these data between community and academic hospitals. RESULTS: Between March 2007 and February 2008, 2178 consecutive patients were admitted with a hip fracture to 13 community and 4 academic hospitals. The mean age was 79 years and 72% were women. The overall in-hospital mortality rate was 5.0%, with no difference between patients treated in academic versus community hospitals (p = 0.56). We found a greater rate of acute care in-hospital mortality for patients admitted from dependent-living facilities compared with those who were living independently (risk ratio 0.63, 95% confidence interval 0.42-0.96). CONCLUSION: Acute care in-hospital mortality following hip fractures remains high and is consistent across academic and community hospitals. With the rising incidence of hip fractures, we need to improve the models of care for these patients to reduce mortality and to maximize functional outcomes while maintaining efficient use of limited health care resources.

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)0.000
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 score0.295
Threshold uncertainty score0.971

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0000.001
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 head0.009
GPT teacher head0.243
Teacher spread0.234 · 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

Citations43
Published2010
Admission routes2
Has abstractyes

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