Abstract 901: Effects of Bucindolol on Cardiovascular Mortality and Morbidity are Determined by the Beta-1 389 Arg/Gly Receptor Polymorphism
Bibliographic record
Abstract
Introduction: Bucindolol is a nonselective beta-adrenergic blocker with potent sympatholytic properties. The Beta-blocker Evaluation of Survival Trial (BEST) reported that the administration of bucindolol resulted in a nonsignificant decrease in total mortality (HR = 0.89 (0.78, 1.02), unadjusted p=0.10) in patients with advanced, NYHA Class III-IV heart failure (HF). Recent observations from that trial also reported that the amino acid arginine (Arg/Arg) or glycine (any Gly) in position 389 of the beta-1 receptor plays a significant role on the clinical response to bucindolol. The impact of bucindolol on cardiovascular mortality and morbidity (cardiovascular hospitalizations) has been incompletely investigated, because hospitalizations had been evaluated from case report forms (CRFs) only, and never adjudicated by the endpoints committee (EPC). Methods: The BEST data base consists of 2708 patients with a mean follow-up of 2.0 years. Cardiovascular (CV) mortality and hospitalizations have now been evaluated by EPC, which further subclassified total hospitalizations into cardiovascular (CV) and those due to worsening heart failure (HF). The impacts of Arg or Gly encoded at amino acid position 389 on endpoints were further investigated in the 1040 patient substudy. Results: Time to event results for adjudicated CV endpoints are presented below. Conclusions: Chronic administration of bucindolol results in a significant reduction in cardiovascular hospitalizations and mortality. Effects on either are strikingly beta-1 389 Arg/Gly specific, with the higher functioning, Arg/Arg version of the receptor associated with large treatment effects and Gly carriers exhibiting little or no evidence of efficacy. Genetic targeting of the β 1 -ΑR 389 polymorphism may improve the clinical responses to bucindolol for CV mortality and morbidity.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".