Genetic Variants Are Not Associated with Outcome in Patients with Coronary Artery Disease and Left Ventricular Dysfunction: Results of the Genetic Substudy of the Surgical Treatment for Ischemic Heart Failure (STICH) Trials
Bibliographic record
Abstract
OBJECTIVES AND BACKGROUND: We evaluated the ability of 23 genetic variants to provide prognostic information in patients enrolled in the Genetic Substudy of the Surgical Treatment for Ischemic Heart Failure (STICH) trials. METHODS: Patients assigned to STICH Hypothesis 1 were randomized to medical therapy with or without coronary artery bypass grafting (CABG). Those assigned to STICH Hypothesis 2 were randomized to CABG or CABG with left ventricular reconstruction. RESULTS: In patients assigned to STICH Hypothesis 2 (n = 714), no genetic variant met the prespecified Bonferroni-adjusted threshold for statistical significance (p < 0.002); however, several variants met nominal prognostic significance: variants in the β2-adrenergic receptor gene (β2-AR Gln27Glu) and in the A1-adenosine receptor gene (A1-717 T/G) were associated with an increased risk of a subject dying or being hospitalized for a cardiac problem (p = 0.027 and 0.031, respectively). These relationships remained nominally significant even after multivariable adjustment for prognostic clinical variables. However, none of the 23 genetic variants influenced all-cause mortality or the combination of death or cardiovascular hospitalization in the STICH Hypothesis 1 population (n = 532) by either univariate or multivariable analysis. CONCLUSION: We were unable to identify the predictive genotypes in optimally treated patients in these two ischemic heart failure populations.
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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 | 0.008 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".