Abstract 12580: Does Sex Influence the Effect of Surgical Revascularization in Patients in Ischemic Left Ventricular Dysfunction? Results From the STICH Trial
Bibliographic record
Abstract
Introduction: Studies have shown sex-specific differences regarding CAD and heart failure with left ventricular (LV) dysfunction. Whether these differences impact the benefit of CABG in patients with ischemic LV dysfunction has not been studied prospectively. Female sex is conventionally considered a risk factor for open-heart surgery, and has been included as a poor prognostic factor in multiple cardiac operative risk evaluation scores. We investigated the impact of sex on the long-term benefit of CABG in patients enrolled in the prospective Surgical Treatment for Ischemic Heart Failure Study (STICH) trial. Method: The STICH trial randomized 1212 patients [148 (12%) women and 1064 (88%) men] with CAD and EF≤ 35% to medical therapy alone (MED) versus MED plus CABG. Long-term (10-year) outcomes with each treatment were compared according to sex. Results: At baseline, women were older with higher BMI and more CAD risk factors (e.g. diabetes) except for smoking, and had lower rates of prior CABG than men (all p<0.05). Moreover, women had higher NYHA class, lower 6-min walk capacity and lower Kansas City Cardiomyopathy Questionnaire scores (all p<0.05). At 10-year follow up, the all-cause mortality rate (HR 0.70, CI 0.55-0.89, adjusted p=0.002) and CV mortality rate (HR 0.64, CI 0.48-0.86, adjusted p=0.006) were significantly lower in women than men. Furthermore, with randomization to CABG vs. MED treatment, there was no significant interaction between sex and treatment group in all-cause mortality, CV mortality, mortality or CV hospitalization (all p>0.05, Figure 1). In addition, surgical deaths were similar for both sexes among patients randomized to CABG. Conclusion: Sex does not impact the effect of CABG on all-cause mortality, CV mortality, CV hospitalization or surgical deaths in patients with ischemic LV dysfunction. Thus, sex should not influence treatment decisions regarding CABG in these patients.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.000 | 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".