Abstract 1798: B-type Natriuretic Peptide and the Effect of Ranolazine in Patients with Non-ST Elevation Acute Coronary Syndromes in the MERLIN-TIMI 36 Trial
Bibliographic record
Abstract
Ranolazine is believed to exert anti-ischemic effects by reducing myocardial cellular Na + & Ca 2+ overload and consequently LV wall stress. B-type natriuretic peptide (BNP) rises in response to increased wall stress and is a potent indicator of risk in ACS. Thus, we designed a prospective evaluation of the interaction between BNP and the effect of ranolazine as part of a randomized, blinded, placebo-controlled trial. METHODS : We measured plasma BNP (ADVIA BNP) at baseline (N = 4543) in pts with non-ST elevation ACS randomized to ranolazine or placebo in the MERLIN-TIMI 36 trial. Pts were stratified using BNP >80 pg/ml based on prior work. The 1 o endpoint was a composite of cardiovascular death, myocardial infarction, or recurrent ischemia (CVD/MI/RI). RESULTS : Pts with an elevated BNP (N = 1935) were at significantly higher risk of CVD/MI/RI (26.4% vs. 20.4%, p < 0.0001), CVD/MI (16.2% vs. 7.5%, p<0.0001) and CVD alone (9.0% vs. 2.4%, p<0.0001). In pts with BNP>80 pg/ml, ranolazine reduced the primary endpoint (HR 0.79; 95%CI 0.66 – 0.94, p=0.009) contrasting with the lack of detectable effect in those with a negative BNP result ( Figure , p-interaction = 0.05). The apparent effect of ranolazine in pts with BNP>80 pg/ml was directionally similar when considering both recurrent ischemia (HR 0.78; 0.62–0.98; p = 0.04) and CVD/MI (HR 0.83; 0.66–1.05, p= 0.12, p-interaction 0.07). CONCLUSIONS : Elevated BNP is associated with worse outcomes in ACS. The results of this planned exploratory analysis suggest that ranolazine may have enhanced efficacy in pts with elevated BNP. The potential interaction of biomarkers of hemodynamic stress and the effects of ranolazine warrants additional study.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".