Abstract P009: The Association of Liver Enzymes with Subclinical Myocardial Damage
Bibliographic record
Abstract
Background: Nonalcoholic fatty liver disease (NAFLD) is present in up to 30% of the US population and is strongly associated with obesity and diabetes. While a number of studies support an association between NAFLD and cardiovascular disease, limited evidence exists for the association with subclinical myocardial injury. Objective: To test the hypothesis that elevated liver enzymes (Alanine aminotrasferase [ALT], Aspartate aminotranferase [AST] and Gamma-glutamyl transpeptidase [GGT]) in the absence of significant alcohol consumption are independently associated with subclinical myocardial injury, defined by elevated cardiac troponin-T measured using a highly-sensitive assay (hs-cTnT). Methods: We conducted a cross-sectional analysis of 9351 participants from the Atherosclerosis Risk in the Communities (ARIC) Study with information on ALT, AST and GGT , hs-cTnT, and no evidence of coronary heart disease or elevated alcohol consumption (>14 and >21 drinks/week for women and men, respectively). We used logistic regression models to examine the association between liver enzymes and elevated hs-TnT (hs-TnT >0.014 μ g/L ) defined in a healthy reference population. Our secondary outcome was detectable hs-TnT (>0.003 μ g/L ). Results: In this community-based population (mean age 63 years, 60% women, 78% white), 7.2% and 66.1% had elevated and detectable hs-TnT, respectively. Medians [range] of ALT, AST and GGT were 13 [1-381], 18 [5-358] and 21 [2-1277], respectively. Higher levels of ALT, AST and GGT, even within the normal range, were independently associated with elevated hs-TnT (Figure). ALT and AST were also independently associated with detectable hs-TnT. After excluding participants with heart failure, the results remained consistent. Conclusions: In this sample, elevated livers enzymes were independently associated with subclinical myocardial damage suggesting that NAFLD may contribute to myocardial injury beyond its effects on development of clinical atherosclerotic coronary disease.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.015 | 0.002 |
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".