Rapid Fire - Basic Science 1
Bibliographic record
Abstract
Abstract Aims To examine associations of below-target and target dose of enalapril, an angiotensin-converting enzyme (ACE) inhibitor, with outcomes in patients with heart failure and reduced ejection fraction (HFrEF) in the Studies of Left Ventricular Dysfunction (SOLVD) Treatment trial. Methods and results Two thousand five hundred and sixty-nine patients with HFrEF (ejection fraction ≤35%) were randomized to below-target (5–10 mg/day) dose placebo (n = 1284) or enalapril (n = 1285). One month post-randomization, blind up-titration to target (20 mg/day) dose was attempted for both study drugs in 2458 patients. Among the 1444 patients who achieved dose up-titration (placebo, n = 748; enalapril, n = 696; mean dose for both groups, 20.0 mg/day), target dose enalapril (vs. target dose placebo) was associated with a 9% absolute lower risk of the combined endpoint of heart failure hospitalization or all-cause mortality [adjusted hazard ratio (HR) 0.70; 95% confidence interval (CI) 0.60–0.81; P < 0.001] during 4 years of follow-up. Among the 1014 patients who could not achieve target dose (placebo, n = 486; enalapril, n = 528; mean dose for both groups, 8.8 mg/day), below-target dose enalapril (vs. below-target dose placebo) was associated with a 12% absolute lower risk of the combined endpoint of heart failure hospitalization or all-cause mortality (adjusted HR 0.68; 95% CI 0.57–0.81; P < 0.001). Among the 1224 patients receiving enalapril, target (vs. below-target) dose had no association with the combined endpoint of heart failure hospitalization or all-cause mortality (adjusted HR 1.04; 95% CI 0.87–1.23; P = 0.695). Conclusion In patients with HFrEF, the clinical benefits of ACE inhibitors appear to be similar at both below-target and target doses.
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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 | 0.005 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.619 | 0.480 |
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".