Pattern of liver enzyme elevations in acute ST-elevation myocardial infarction
Bibliographic record
Abstract
OBJECTIVES: Liver enzyme elevations occur with ST-segment elevation myocardial infarction (STEMI); however, their significance in the modern era is not well-defined. The incidence of liver enzyme elevations in STEMI, temporal trends, correlations with creatine kinase-MB (CK-MB), and associations with clinical outcomes were evaluated. METHODS: The Complement Inhibition in Myocardial Infarction Treated with Angioplasty and Complement Inhibition in Myocardial Infarction Treated with Thrombolytics trials evaluated 1903 patients with STEMI. A core lab analyzed liver enzymes at baseline, days 1, 6, and 14, and CK-MB measured sequentially over 72 h. The GUSTO model for 30-day mortality was used to predict clinical endpoints. RESULTS: A total of 1783 patients were included in the analysis. Aspartate transaminase (AST) was elevated above the upper limit of normal in 85.6% and alanine transaminase (ALT) was elevated in 48.2% of patients at baseline or day 1. CK-MB area under the curve correlated with maximum AST (r=0.727) and maximum ALT (r=0.456). Both AST and ALT elevations were independent predictors of worse outcomes in multivariable adjusted analysis, even after adjustment for CK-MB. Hazard ratios and 95% confidence intervals of AST elevation were 1.12 (1.05-1.19) for all-cause mortality, and 1.08 (1.02-1.13) for the composite endpoint of death, congestive heart failure, shock, or stroke. Hazard ratios and 95% confidence intervals of ALT elevation were 1.15 (1.04-1.27) for mortality and 1.47 (1.10-1.98) for the composite endpoint. CONCLUSION: AST and ALT elevations are common in STEMI. Both markers are correlated with CK-MB area under the curve, but independently associated with worse mortality and clinical 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".