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Record W2981822539 · doi:10.1093/eurheartj/ehz745.0383

P3519Sex-based disparities in end of life care among patients with heart failure

2019· article· en· W2981822539 on OpenAlexaffabout
Harriette G.C. Van Spall, Andrea Hill, Longdi Fu, Heather J. Ross, Hannah Wunsch, John J. You, Robert Fowler

Bibliographic record

VenueEuropean Heart Journal · 2019
Typearticle
Languageen
FieldMedicine
TopicHeart Failure Treatment and Management
Canadian institutionsUniversity Health NetworkHealth Sciences CentreSunnybrook Health Science CentreMcMaster UniversityPopulation Health Research Institute
Fundersnot available
KeywordsMedicineRetrospective cohort studyIntensive care unitLogistic regressionHeart failureHealth carePopulationEmergency departmentCohortEnd-of-life careEmergency medicineCohort studyPediatricsInternal medicinePalliative care

Abstract

fetched live from OpenAlex

Abstract Background There are sex-based disparities in care and outcomes among patients with heart failure (HF), but the association between sex and health care services received at the end-of-life health is unknown. Purpose To assess for sex-based differences in location of death and the type and intensity of health care services received at the end of life among patients with HF. Methods We conducted a retrospective cohort study of adults (≥18 years) who died between April 1, 2004 and March 31, 2017 in Ontario, Canada. We included decedents who had a diagnosis of HF and a hospitalization for HF in the year preceding their death. We obtained demographic, clinical, health care utilization, and healthcare system cost data from population-based administrative databases, using unique encrypted identifiers to link records. We used descriptive statistics and a 2-level multivariable logistic regression model with patients (1st level) nested in regions (2nd level) to assess whether sex was independently associated with death in hospital. Results We identified 396,024 adults (51.5% women) who died of HF between April 1, 2004 and March 31, 2017. Mean (SD) age at death was 81.8 (10.7) years and a majority of deaths (53.4%) occurred in the hospital. During the last 6 months of life, a significantly lower proportion of women than men experienced emergency department visits (81.7% vs 86.5%; p<0.001); hospitalizations (75.6% vs 80.8%; p<0.001); intensive care unit (ICU) admissions (22.8% vs 30.1%; p<0.001); mechanical ventilation (15.5% vs 20.8%; p<0.001); cardiac catheterization (2.8% vs 4.6%; p<0.001); coronary revascularization (1.5% vs 2.6%; p<0.001); hemodialysis (4.8% vs 7.7%; p<0.001); or care from 10 or more different physicians (57.6% vs 67.1%; p<0.001). In the last 6 months of life, women spent fewer days than men in the hospital (mean 16.4 vs 18.3; mean difference [MD] 1.9 [95% confidence interval 1.7–2.0]; p<0.001), in an ICU (mean 2.1 vs 3.0; MD 0.9 [95% CI 0.8–0.9]; p<0.001), and on a ventilator (mean 1.4 vs 1.9; MD 0.5 [95% CI 0.5–0.5]; p<0.001). These differences persisted and remained significant in the last month of life. There was no difference in the proportion of women vs men receiving palliative care services (45.1% vs 45.0%; p=0.53) in the last 6 months of life. After adjusting for age, socioeconomic status, comorbidities, place of residence, and year of death, women had lower odds of dying in a hospital than men (adjusted odds ratio 0.88 [95% CI 0.87–0.89]). Conclusion In this large cohort study in Ontario, Canada, women with HF received disproportionately lower in-hospital and invasive care services than men in their last 6 months of life and were more likely than men to die at home. Acknowledgement/Funding Canadian Institutes of Health Research

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)0.000
metaresearch head score (Gemma)0.002
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 score0.429
Threshold uncertainty score0.853

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0080.000

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 head0.011
GPT teacher head0.228
Teacher spread0.218 · 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".

Quick stats

Citations0
Published2019
Admission routes2
Has abstractyes

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