Sex Differences in Clinical Characteristics and Outcomes in Elderly Patients With Heart Failure and Preserved Ejection Fraction
Bibliographic record
Abstract
BACKGROUND: There are few sex-specific outcome data in heart failure with preserved ejection fraction. METHODS AND RESULTS: We assessed sex differences in baseline characteristics and outcomes among 4128 patients with heart failure with preserved ejection fraction in the Irbesartan in Heart Failure with Preserved Ejection Fraction (I-PRESERVE) trial. Women (n=2491) with heart failure with preserved ejection fraction were ≈1 year older (72±7 years versus 71±7 years) and more likely to be obese (46% versus 35%) and have chronic kidney disease (34% versus 26%) and hypertension (91% versus 85%) than men but less likely to have an ischemic cause (19% versus 34%), atrial fibrillation (27% versus 33%), or chronic obstructive pulmonary disease (8% versus 13%) (all P<0.001). During a mean of 49.5 months, there were 881 deaths (447 in women, 434 in men; risk ratio, 0.64; 95% CI, 0.56-0.74) and 5776 hospitalizations (3239 in women, 2537 in men; risk ratio, 0.80; 95% CI, 0.76-0.84). Women had lower risk of all-cause events (deaths and hospitalizations), even after adjusting for baseline characteristics (adjusted hazards ratio, 0.81; 95% CI, 0.73-0.89). However, the sex-related difference in risk of all-cause events was modified in the presence or absence of atrial fibrillation, renal dysfunction, stable angina pectoris, or advanced New York Heart Association class symptoms. CONCLUSIONS: In patients with typical heart failure with preserved ejection fraction, there were prominent sex differences in baseline characteristics and outcomes. Women had better overall prognosis, although the presence of 4 common baseline characteristics seemed to moderate this finding.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".