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Record W4388596038 · doi:10.1093/eurheartj/ehad655.871

Sex differences in long-term outcomes among hospitalized heart failure patients across the spectrum of ejection fraction: findings from the Get with the guidelines - heart failure registry

2023· article· en· W4388596038 on OpenAlexaff
Neil Keshvani, Sonia Shah, Iyanuoluwa Ayodele, Karen Chiswell, Brooke Alhanti, Larry A. Allen, Kavita Sharma, Stephen J. Greene, Clyde W. Yancy, Harriette G.C. Van Spall, Gregg C. Fonarow, Paul A. Heidenreich, Ambarish Pandey

Bibliographic record

VenueEuropean Heart Journal · 2023
Typearticle
Languageen
FieldMedicine
TopicHeart Failure Treatment and Management
Canadian institutionsPopulation Health Research Institute
Fundersnot available
KeywordsMedicineHeart failureEjection fractionInternal medicineCardiologyMyocardial infarctionProportional hazards modelHazard ratioIncidence (geometry)Confidence interval

Abstract

fetched live from OpenAlex

Abstract Background Sex differences in 5-year outcomes across heart failure (HF) ejection fraction (EF) subtypes are not well known. Purpose To assess the interaction between sex and EF for risk of long-term adverse outcomes after hospitalization with HF. Methods Patients from American Heart Association’s Get With The Guidelines – Heart Failure registry enrolled between 1/1/2006 – 12/31/2014 with age ≥ 65 years with available 5-year follow-up data, ascertained through linkage with Medicare fee-for-service Part A administrative claims, were included. HF subtypes included HF with reduced EF (HFrEF) with EF ≤ 40%, HF with mildly reduced EF (HFmrEF) with EF 41-49%, and HF with preserved EF (HFpEF) with EF ≥ 50%. Sex differences in 5-year all-cause mortality and readmission for each HF subtype were assessed using unadjusted cumulative incidence methods and adjusted Cox models. Median survival across HF subtypes was compared to median survival of U.S. adults. Results 155,670 patients (mean age 81 years, 53.4% females) were included. Male patients were younger and had a higher prevalence of prior myocardial infarction or coronary artery bypass graft surgery and were more likely to have HFrEF, while women were more likely to have history of hypertension and HFpEF. The median post-hospitalization survival of patients with HF was substantially lower than the age- and sex-specific U.S. life expectancy across each HF subtype (Figure 1).Patients with HF had high 5-year mortality rates (HFrEF male: 81.3%, female: 78.4%; HFpEF male: 80.5% vs female 79.5%). In adjusted analysis, female (vs. male) patients had a significantly lower 5-year mortality risk (HR [95%CI]: 0.89 [0.87 – 0.90], p<0.01) and a higher 5-year readmission risk (all-cause: 1.03 [1.02 – 1.04]), CV: 1.05 [1.04 – 1.07]), HF: 1.06 [1.04 – 1.08], p<0.01 for each). HF subtype modified the association between sex and 5-year outcomes (pinteraction <0.05 for mortality and CV and HF readmission), with the greatest risk reduction of mortality for female vs. male patients with HFrEF and the greatest risk increase of readmission (CV and HF) among female vs. male patients with HFmrEF and HFpEF (Figure 2). Conclusion Among patients with HF, the overall survival post-HF hospitalization is very low for each HF subtype. Female patients have a lower 5-year mortality risk but a higher risk of HF or CV readmission regardless of EF.Figure 1Figure 2

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)0.005
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 score0.006
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
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 head0.036
GPT teacher head0.310
Teacher spread0.274 · 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

Citations1
Published2023
Admission routes1
Has abstractyes

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