Baseline Characteristics of Patients With HF With Mildly Reduced and Preserved Ejection Fraction
Bibliographic record
Abstract
OBJECTIVES: This report describes the baseline clinical profiles and management of DELIVER (Dapagliflozin Evaluation to Improve the Lives of Patients With Preserved Ejection Fraction Heart Failure) trial participants and how these compare with those in other contemporary heart failure with preserved ejection fraction trials. BACKGROUND: The DELIVER trial was designed to evaluate the effects of the sodium-glucose cotransporter-2 inhibitor dapagliflozin on cardiovascular death, heart failure (HF) hospitalization, or urgent HF visits in patients with HF with mildly reduced and preserved left ventricular ejection fraction (LVEF). METHODS: Adults with symptomatic HF and LVEF >40%, with or without type 2 diabetes mellitus, elevated N-terminal pro-B-type natriuretic peptide (NT-proBNP) levels, and evidence of structural heart disease were randomized to dapagliflozin 10 mg once daily or matching placebo. RESULTS: ; and 57% with history of atrial fibrillation or flutter). Most participants had New York Heart Association functional class II symptoms (75%). Baseline mean LVEF was 54.2 ± 8.8% and median NT-proBNP of 1,399 pg/mL (IQR: 962 to 2,210 pg/mL) for patients in atrial fibrillation/flutter compared with 716 pg/mL (IQR: 469 to 1,281 pg/mL) in those who were not. Patients in both hospitalized and ambulatory settings were enrolled, including 10% enrolled in-hospital or within 30 days of a hospitalization for HF. Eighteen percent of participants had HF with improved LVEF. CONCLUSIONS: DELIVER is the largest and broadest clinical trial of this population to date and enrolled high-risk, well-treated patients with HF with mildly reduced and preserved LVEF. (Dapagliflozin Evaluation to Improve the Lives of Patients With Preserved Ejection Fraction Heart Failure [NCT03619213]).
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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) | 0.001 | 0.000 |
| 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) | 0.003 | 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".