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Record W2137587081 · doi:10.1302/0301-620x.87b3.15300

The effect of hospital type and surgical delay on mortality after surgery for hip fracture

2005· article· en· W2137587081 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueJournal of Bone and Joint Surgery - British Volume · 2005
Typearticle
Languageen
FieldMedicine
TopicHip and Femur Fractures
Canadian institutionsSunnybrook Health Science CentreInstitute for Clinical Evaluative SciencesYork University
Fundersnot available
KeywordsMedicineOdds ratioHip fractureConfidence intervalSurgeryInternal medicineOsteoporosis

Abstract

fetched live from OpenAlex

Death during the first year after hip fracture may be influenced by the type of hospital in which patients are treated as well as the time spent awaiting surgery. We studied 57,315 hip fracture patients who were admitted to hospital in Ontario, Canada. Patients treated in teaching hospitals had a decreased risk of in-hospital mortality (odds ratio (OR) 0.89; 95% confidence interval (CI) 0.83 to 0.97) compared with those treated in urban community institutions. There was a trend toward increased mortality in rural rather than urban community hospitals. In-hospital mortality increased as the surgical delay increased (OR 1.13; 95% CI 1.10 to 1.16) for a one-day delay and higher (OR 1.60; 95% CI 1.42 to 1.80) for delays of more than two days. This relationship was strongest for patients younger than 70 years of age and with no comorbidities but was independent of hospital status. Similar relationships were seen at three months and one year after surgery. This suggests that any delay to surgery for non-medical reasons is detrimental to a patient's 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.

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)0.002
metaresearch head score (Gemma)0.001
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 score0.104
Threshold uncertainty score0.457

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.010
GPT teacher head0.249
Teacher spread0.240 · 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