Health Status Across Major Subgroups of Patients with Heart Failure and Preserved Ejection Fraction
Bibliographic record
Abstract
AIMS: There are limited data on health status and changes in it over time across major subgroups of patients with heart failure and preserved ejection fraction (HFpEF), including ejection fraction spectrum, age, sex, region, body mass index (BMI), and comorbidities including diabetes, chronic kidney disease (CKD), anaemia, and atrial fibrillation/flutter. METHODS AND RESULTS: In the EMPEROR-Preserved trial, the Kansas City Cardiomyopathy Questionnaire (KCCQ) was assessed at baseline, 12, 32 and 52 weeks. Determinants of baseline KCCQ score and change over time, and the impact of empagliflozin on KCCQ scores were studied in specified subgroups. A Cox model was used to assess the association between 5- and 10-point increase and 5-point decrease in KCCQ score from baseline to week 12 and later outcomes. Among 2979 participants in the placebo arm, mean KCCQ clinical summary score (CSS) was 70.7 (20.8). Older age, female sex, BMI, anaemia, and a history of diabetes, and CKD were associated with worse scores. KCCQ-CSS score improved during follow-up; patients with atrial fibrillation/flutter at enrollment (p trend = 0.014) and CKD (p trend < 0.001) had less improvement. A 5-point increase in KCCQ-CSS at week 12 was associated with lower risk of cardiovascular death or heart failure hospitalization (5%), cardiovascular death (8%), and first heart failure hospitalization (4%) subsequently. A similar trend was seen with KCCQ total symptom score (TSS) and overall summary score (OSS). Empagliflozin improved KCCQ-CSS, -TSS and -OSS scores similarly across subgroups studied except for greater improvement in patients with the highest BMI (p trend = 0.153, 0.08 and 0.078, respectively). CONCLUSION: Health status in patients with HFpEF is impaired, especially in elderly, women, and those with obesity and comorbidities. Empagliflozin improved health status among all key subgroups studied with a greater effect in obese patients.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".