Heart Failure with Reduced Ejection Fraction: Comparison of Patient Characteristics and Clinical Outcomes Within Asia and between Asia, Europe and the Americas
Bibliographic record
Abstract
AIMS: Nearly 60% of the world's population lives in Asia but little is known about the characteristics and outcomes of Asian patients with heart failure with reduced ejection fraction (HFrEF) compared to other areas of the world. METHODS AND RESULTS: We pooled two, large, global trials, with similar design, in 13 174 patients with HFrEF (patient distribution: China 833, India 1390, Japan 209, Korea 223, Philippines 223, Taiwan 199 and Thailand 95, Western Europe 3521, Eastern Europe 4758, North America 613, and Latin America 1110). Asian patients were younger (55.0-63.9 years) than in Western Europe (67.9 years) and North America (66.6 years). Diuretics and devices were used less, and digoxin used more, in Asia. Mineralocorticoid receptor antagonist use was higher in China (66.3%), the Philippines (64.1%) and Latin America (62.8%) compared to Europe and North America (range 32.8% to 49.6%). The rate of cardiovascular death/heart failure hospitalization was higher in Asia (e.g. Taiwan 17.2, China 14.9 per 100 patient-years) than in Western Europe (10.4) and North America (12.8). However, the adjusted risk of cardiovascular death was higher in many Asian countries than in Western Europe (except Japan) and the risk of heart failure hospitalization was lower in India and in the Philippines than in Western Europe, but significantly higher in China, Japan, and Taiwan. CONCLUSION: Patient characteristics and outcomes vary between Asia and other regions and between Asian countries. These variations may reflect several factors, including geography, climate and environment, diet and lifestyle, health care systems, genetics and socioeconomic influences.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".