Recent Abacavir Use Increases Risk of Type 1 and Type 2 Myocardial Infarctions Among Adults With HIV
Bibliographic record
Abstract
BACKGROUND: There is persistent confusion as to whether abacavir (ABC) increases the risk of myocardial infarction (MI), and whether such risk differs by type 1 (T1MI) or 2 (T2MI) MI in adults with HIV. METHODS: Incident MIs in North American Cohort Collaboration on Research and Design participants were identified from 2001 to 2013. Discrete time marginal structural models addressed channeling biases and time-dependent confounding to estimate crude hazard ratio (HR) and adjusted hazard ratio (aHR) and 95% confidence intervals; analyses were performed for T1MI and T2MI separately. A sensitivity analysis evaluated whether Framingham risk score (FRS) modified the effect of ABC on MI occurrence. RESULTS: Eight thousand two hundred sixty-five adults who initiated antiretroviral therapy contributed 29,077 person-years and 123 MI events (65 T1MI and 58 T2MI). Median follow-up time was 2.9 (interquartile range 1.4-5.1) years. ABC initiators were more likely to have a history of injection drug use, hepatitis C virus infection, hypertension, diabetes, impaired kidney function, hyperlipidemia, low (<200 cells/mm) CD4 counts, and a history of AIDS. The risk of the combined MI outcome was greater for persons who used ABC in the previous 6 months [aHR = 1.84 (1.17-2.91)]; and persisted for T1MI (aHR = 1.62 [1.01]) and T2MI [aHR = 2.11 (1.08-4.29)]. FRS did not modify the effect of ABC on MI (P = 0.14) and inclusion of FRS in the MSM did not diminish the effect of recent ABC use on the combined outcome. CONCLUSIONS: Recent ABC use was associated with MI after adjustment for known risk factors and for FRS. However, screening for T1MI risks may not identify all or even most persons at risk of ABC use-associated MIs.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 teacher head, 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".