Heart failure with reduced ejection fraction and the intersection of cardio-renal-metabolic medicine #CaReMe
Bibliographic record
Abstract
Diabetes and chronic kidney disease (CKD) are important comorbidities in patients with heart failure (HF) that can complicate the clinical management and have major implications for morbidity and mortality. In addition, the presence of these comorbidities, particularly advanced CKD, is a limitation for the implementation of guideline-directed therapies in patients with HF with reduced ejection fraction (HFrEF). Though clinical trials in patients with HFrEF trials included varying percentages of patients with diabetes and/or CKD, patients with advanced CKD have been excluded in most HF studies. Thus, management recommendations for these patients often have to be extrapolated from subgroup analyses. This article summarizes pathophysiological aspects of the interaction of HFrEF, CKD, and diabetes and addresses clinical aspects for the screening of these comorbidities. Moreover, current treatment options for patients with HFrEF and CKD and/or diabetes are discussed and novel strategies such as the use of the selective mineralocorticoid receptor antagonist Finerenone are addressed.
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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 | 0.001 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 0.001 |
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".