Heart failure with preserved ejection fraction
Bibliographic record
Abstract
PURPOSE OF REVIEW: Heart failure is a major health problem with significant morbidity and mortality. Although impressive advances in treatment and reduction in mortality have marked heart failure with reduced ejection fraction (HFrEF), the mortality in patients with heart failure with preserved ejection fraction (HFpEF), which accounts for nearly half of heart failure cases, has remained unchanged. This may be because of the lack of consistent diagnostic criteria and limited understanding of the pathophysiology of HFpEF, and thus appropriate treatment options. RECENT FINDINGS: Recent data suggest that HFpEF consists of multiple abnormalities rather than a distinct entity. Advances in testing have improved diagnosis, but further validation is required. The discoveries of new pathological abnormalities have identified potential new drug therapy targets. Traditional agents with strong evidence in HFrEF have proved unsuccessful in HFpEF. Newer agents such as angiotensin receptor neprilysin inhibitor, sildenafil, and ivabradine have demonstrated benefits without improving mortality. Lastly, as HFpEF patients are older with more comorbidities, alternate endpoints to survival benefit should be considered. SUMMARY: Although enormous strides have been made in understanding the pathophysiology and refining the diagnostic criteria of HFpEF, there is currently no pharmacological therapy with mortality benefits. Further characterization and the recruitment of more homogeneous patient populations will be essential to identify effective treatments.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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".