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Record W2922316566 · doi:10.1161/circ.139.suppl_1.p402

Abstract P402: Association Between Post-stroke Disability and 5-year Hip-fracture Risk: the Women’s Health Initiative

2019· article· en· W2922316566 on OpenAlexaff
Carin Northuis, Carolyn Crandall, Karen L. Margolis, Susan J. Diem, Kristine E. Ensrud, Jean Wactawski‐Wende, Kamakshi Lakshminarayan

Bibliographic record

VenueCirculation · 2019
Typearticle
Languageen
FieldMedicine
TopicHip and Femur Fractures
Canadian institutionsCrandall University
Fundersnot available
KeywordsMedicineHip fractureStroke (engine)Physical therapyIncidence (geometry)Observational studySurgeryInternal medicineOsteoporosis

Abstract

fetched live from OpenAlex

Background: Hip fractures are a significant post-stroke complication. While studies have shown an increased incidence of hip fractures post-stroke, the relationship between stroke-related disability and hip fracture rates are not well characterized. Herein, we examine factors associated with hip fracture risk after stroke using the Women’s Health Initiative (WHI) data. Methods: The WHI is a prospective study of 161,808 postmenopausal women aged 50-79 years. In the WHI, stroke cases were initially self-reported and then confirmed by a neurologist adjudication using medical records and a manual. Hip fracture cases were self-reported and then radiologically confirmed by physician adjudication. We included stroke survivors from the observational and clinical trial arms who had a Glasgow Outcome Score (GOS) of 1-3 (good recovery, moderately disabled, severely disabled) and survived at least one week after stroke (n=4,640). Survival free from any radiologically-confirmed hip fracture post-stroke was estimated and compared by GOS status. Secondary analysis examined the post-stroke hip fracture risk while accounting for the competing risk of death. Results: There were 124 hip fractures. Average age of stroke was 74.6 ± 7.2 years. Mean follow-up time was 3.1±1.8 years. Hip fractures by GOS status represented 2.4% (45/1872), 2.5% (34/1366), and 3.5% (45/1278) among good recovery, moderately disabled, and severely disabled. In the competing risk model, 23.3% (1079/4640) of the participants died before the end of follow-up or the occurrence of a hip fracture. Severely disabled (HR: 2.1 (95% CI: 1.3, 3.2), p=0.001) status, but not moderately disabled (HR: 1.1 (95% CI: 0.7, 1.7) p=0.8), was significantly associated with an increase in risk of hip fracture compared to good recovery status. This association was attenuated and not significant for moderately disabled (HR: 1.1 (95%CI: 0.7, 1.7), p=0.8) and severely disabled (HR 1.5 (95%CI: 1.0, 2.3), p=0.06) status when accounting for mortality after stroke. High Hip Fracture Risk Assessment Tool (FRAX) risk (without bone density information), being Caucasian, and increasing age were associated with an increased post stroke hip fracture risk. When accounting for mortality after stroke, higher FRAX-predicted hip fracture risk and race/ethnicity remained significant. The association between age and hip fracture was attenuated and not significant after accounting for post-stroke mortality. Conclusion: Among stroke survivors, severely disabled status and FRAX-predicted hip fracture risk were associated with a higher risk of subsequent radiologically confirmed hip fracture, but only the FRAX-predicted hip fracture risk association remained significant when considering the competing risk of mortality after stroke. Interventions to reduce fracture risk after stroke should be evaluated in clinical trials.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.014
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.013
GPT teacher head0.275
Teacher spread0.262 · 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 source (direct Gemma or distilled Codex), 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".

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Citations0
Published2019
Admission routes1
Has abstractyes

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