Association Between ALT Level and the Rate of Cardio/Cerebrovascular Events in HIV-Positive Individuals
Bibliographic record
Abstract
BACKGROUND: An inverse association between serum alanine aminotransferase (ALT) levels and the risk of myocardial infarction (MI) has been reported in the general population. We investigated associations between ALT levels and the risk of various cardiovascular and cerebrovascular outcomes in a large cohort study of HIV-positive individuals. METHODS: Using Poisson regression, we investigated associations between the latest ALT level and MI, coronary heart disease (CHD), and stroke, after adjusting for known confounders and cumulative/recent exposure to antiretroviral drugs. Analyses were also performed for the end points of all-cause/liver-related mortality and new-onset diabetes mellitus. RESULTS: By February 2011, participants had experienced 541 MIs, 804 CHD, and 258 stroke events. The MI rate decreased from 3.1/1000 person-years among those with ALT ≤18 U/L to 2.1/1000 person-years among those with ALT >60 U/L. After adjustment for confounders, each 2-fold increment in ALT was associated with a 19% drop in the MI rate {relative rate, 0.81 [95% confidence interval (CI): 0.74 to 0.89], P = 0.0001}. A weaker inverse association was seen for CHD with no indication of a linear association between ALT levels and stroke (P = 0.72). Adjusted relative rates were 0.88 (95% CI: 0.81 to 0.97) and 0.70 (95% CI: 0.54 to 0.92) in those who were hepatitis C virus negative and hepatitis C virus positive, respectively, and 0.72 (95% CI: 0.58 to 0.89) and 0.84 (0.77 to 0.93) in injection drug users and non-injection drug users, respectively. Liver-related mortality and diabetes both demonstrated a positive association with ALT levels, whereas all-cause mortality showed a U-shaped relationship. CONCLUSIONS: Higher ALT levels are associated with lower MI risk in HIV-positive individuals, but with higher risks of liver-related mortality and diabetes mellitus.
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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 | 0.003 |
| 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 | 0.001 |
| 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".