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Record W2599024705 · doi:10.1503/cjs.008616

The burden of second hip fractures: provincial surgical hospitalizations over 15 years

2017· article· en· W2599024705 on OpenAlexafffundvenue
Pierre Guy, Boris Sobolev, Katie Jane Sheehan, Lisa Kuramoto, Kelly A. Lefaivre

Bibliographic record

VenueCanadian Journal of Surgery · 2017
Typearticle
Languageen
FieldMedicine
TopicHip and Femur Fractures
Canadian institutionsVancouver Coastal Health Research InstituteUniversity of British ColumbiaVancouver Coastal Health
FundersCanadian Institutes of Health ResearchCentre for Hip Health and MobilityUniversity of British Columbia
KeywordsMedicineHip fracturePhysical therapySurgeryOsteoporosisInternal medicine

Abstract

fetched live from OpenAlex

<h3>Background:</h3> Second hip fractures account for up to 15% of all hip fractures. We sought to determine if the proportion of hip fracture surgeries for second hip fracture changed over time in terms of patient and fracture characteristics. <h3>Methods:</h3> We reviewed the records of patients older than 60 years hospitalized for hip fracture surgery between 1990 and 2005 in British Columbia. We studied the proportion of surgeries for second hip fracture among all hip fracture surgeries. Linear regression tested for trends across fiscal years for women and men. <h3>Results:</h3> We obtained 46 341 patient records. Second hip fracture accounted for 8.3% of hip fracture surgeries. For women the proportion of second hip fracture surgeries increased linearly from 4% to 13% with each age decade (<i>p</i> = 0.001) and across fiscal years (<i>p</i> = 0.002). In men the proportion of second hip fracture surgeries was 5% for each age decade between the ages of 60 and 90 years across fiscal years, increasing to 8% for men older than 90 years across fiscal years (<i>p</i> = 0.20). These sex-specific trends were similar for both pertrochanteric and transcervical fracture types. <h3>Conclusion:</h3> Second hip fracture surgeries account for an increasing proportion of hip fracture surgeries and may require more health care resources to minimize poorer reported outcomes. Future research should determine whether more health care resources are required to manage these patients and optimize their outcomes.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.060
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0010.000

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 head0.017
GPT teacher head0.270
Teacher spread0.253 · 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.

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

Citations15
Published2017
Admission routes3
Has abstractyes

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