Sex Differences in Long-Term Outcomes Following Acute Heart Failure Hospitalization: Findings from the Get with the Guidelines-Heart Failure Registry
Bibliographic record
Abstract
Abstract Aims Sex differences in long-term outcomes following hospitalization for heart failure (HF) across ejection fraction (EF) subtypes are not well described. In this study, we evaluated the risk of mortality and rehospitalization among males and females across the spectrum of EF over 5 years of follow-up following an index HF hospitalization event. Methods and results Patients hospitalized with HF between 1 January 2006 and 31 December 2014 from the American Heart Association's Get With The Guidelines-Heart Failure registry with available 5-year follow-up using Medicare Part A claims data were included. The association between sex and risk of mortality and readmission over a 5-year follow-up period for each HF subtype (HF with reduced EF [HFrEF, EF ≤40%], HF with mildly reduced EF [HFmrEF, EF 41–49%], and HF with preserved EF [HFpEF, EF >50%]) was assessed using adjusted Cox models. The effect modification by the HF subtype for the association between sex and outcomes was assessed by including multiplicative interaction terms in the models. A total of 155 670 patients (median age: 81 years, 53.4% female) were included. Over 5-year follow-up, males and females had comparably poor survival post-discharge; however, females (vs. males) had greater years of survival lost to HF compared with the median age- and sex-matched US population (HFpEF: 17.0 vs. 14.6 years; HFrEF: 17.3 vs. 15.1 years; HFmrEF: 17.7 vs. 14.6 years for age group 65-69 years). In adjusted analysis, females (vs. males) had a lower risk of 5-year mortality (adjusted hazard ratio [aHR] 0.89, 95% confidence interval [CI] 0.87–0.90, p < 0.0001), and the risk difference was most pronounced among patients with HFrEF (aHR 0.87, 95% CI 0.85–0.89; pinteraction[sex*HF subtype] = 0.04). Females (vs. males) had a higher adjusted risk of HF readmission over 5-year follow-up (aHR 1.06, 95% CI 1.04–1.08, p < 0.0001), with the risk difference most pronounced among patients with HFpEF (aHR 1.11, 95% CI 1.07–1.14; pinteraction[sex*HF subtype] = 0.001). Conclusions While females (vs. males) had lower adjusted mortality, females experienced a significantly greater loss in survival time than the median age- and sex-matched US population and had a greater risk of rehospitalization over 5 years following HF hospitalization.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".