Protective effect of pyridoxal-5-phosphate (MC-1) on perioperative myocardial infarction is independent of aortic cross clamp time: results from the MEND-CABG trial.
Bibliographic record
Abstract
AIM: Aortic cross-clamp time remains a significant marker of mortality and morbidity after coronary artery bypass graft (CABG) surgery. Pyridoxal-5-phosphate (MC-1), blocking purinergic receptors and intracellular influx of calcium, was shown to decrease the incidence of perioperative myocardial infarction in the prospective, randomized, double-blinded MC-1 to Eliminate Necrosis and Damage in CABG (MEND-CABG) clinical trial. METHODS: We studied the relationship between treatment with MC-1 and aortic cross-clamping relative to the incidence of cardiovascular (CV) death and myocardial infarction (MI) in the trial that enrolled 901 high-risk patients undergoing CABG with cardiopulmonary bypass. Patients were randomized to receive either placebo, MC-1 250 mg/day or MC-1 750 mg/day starting 3-10 h before CABG and continued for 30 days after surgery. Serial creatine kinase-myocardial band (CK-MB) determinations, ECGs and clinical evaluations were performed. RESULTS: Cross-clamping time increased the event rate of death and MI with an odds ratio (95% confidence interval) of 1.67 (1.17-2.37, P=0.0044). Treatment with MC-1 decreased the rate of events (P=0.0073) with odds ratios of 0.52 (0.31-0.88 for MC-1 250 mg/day versus placebo) and 0.48 (0.29-0.82 for MC-1 750 mg/day versus placebo). There was no interaction between cross-clamp time and treatment (P=0.61) on the occurrence of the combined endpoint. CONCLUSION: MC-1 decreased the incidence of CV death and MI (CK-MB >or=100 ng/mL) during the first 90 days after CABG in the MEND-CABG trial. Although longer aortic clamping time increased the risk of cardiovascular events, the protective effect of MC-1 was independent of ischemic time during CABG.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.002 | 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".