Late Results of the Warm Heart Trial : The Influence of Nonfatal Cardiac Events on Late Survival
Bibliographic record
Abstract
BACKGROUND: The Warm Heart Trial randomized 1732 CABG patients to receive warm or cold blood cardioplegia. In the warm cardioplegia patients, nonfatal perioperative cardiac events were significantly decreased and the mortality rate was nonsignificantly decreased (1. 4% versus 2.5%, P:=0.12). The purpose of the present study was to evaluate the late results of these trial patients. METHODS AND RESULTS: Randomization was stratified according to surgeon and urgency of the operation. Seven hundred sixty-two patients recruited from 1 of the centers were followed through the hospital clinic for late events. Late survival (including perioperative deaths) at 72 months was nonsignificantly greater in the warm cardioplegia patients (94.5+/-1.7%, mean+/-SEM) than in the cold cardioplegia patients (90.9+/-2.6%). Independent predictors of mortality by Cox proportional hazards model were redo CABG, diabetes mellitus, renal insufficiency, and increasing age. The influence of nonfatal perioperative events (perioperative myocardial infarction according to computerized ECG readings or low output syndrome as determined by an outcome committee) on late survival was also analyzed. Late survival at 84 months was significantly reduced in the group who experienced nonfatal perioperative outcomes (94.5+/-1.7% versus 84. 9+/-4.5%, P:<0.001) and remained a significant predictor after adjustment for other important variables (risk ratio 6.4, 95% CI 1. 87 to 8.73, P:<0.0001). CONCLUSIONS: Effective myocardial protection through either cold or warm blood cardioplegia is essential, because late survival is significantly reduced in patients with nonfatal perioperative cardiac outcomes.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| 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".