Efficacy of Sacubitril/Valsartan vs. Enalapril at Lower than Target Doses in Heart Failure with Reduced Ejection Fraction: The PARADIGM-HF Trial
Bibliographic record
Abstract
AIMS: In this analysis, we utilized data from PARADIGM-HF to test the hypothesis that participants who exhibited any dose reduction during the trial would have similar benefits from lower doses of sacubitril/valsartan relative to lower doses of enalapril. METHODS AND RESULTS: In a post-hoc analysis from PARADIGM-HF, we characterized patients by whether they received the maximal dose (200 mg sacubitril/valsartan or 10 mg enalapril twice daily) throughout the trial or had any dose reduction to lower doses (100/50/0 mg sacubitril/valsartan or 5/2.5/0 mg enalapril twice daily). The treatment effect for the primary outcome was estimated, stratified by dose level using time-updated Cox regression models. In the two treatment arms, participants with a dose reduction (43% of those randomized to enalapril and 42% of those randomized to sacubitril/valsartan) had similar baseline characteristics and similar baseline predictors of the need for dose reduction. In a time-updated analysis, any dose reduction was associated with a higher subsequent risk of the primary event [hazard ratio (HR) 2.5, 95% confidence interval (CI) 2.2-2.7]. However, the treatment benefit of sacubitril/valsartan over enalapril following a dose reduction was similar (HR 0.80, 95% CI 0.70-0.93, P < 0.001) to that observed in patients who had not experienced any dose reduction (HR 0.79, 95% CI 0.71-0.88, P < 0.001). CONCLUSIONS: In PARADIGM-HF, study medication dose reduction identified patients at higher risk of a major cardiovascular event. The magnitude of benefit for patients on lower doses of sacubitril/valsartan relative to those on lower doses of enalapril was similar to that of patients who remained on target doses of both drugs.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".