Association Between HIV Infection, Antiretroviral Therapy, and Risk of Acute Myocardial Infarction: A Cohort and Nested Case–Control Study Using Québec's Public Health Insurance Database
Bibliographic record
Abstract
BACKGROUND: Morbidity associated with cardiovascular disease is increasing in the HIV-infected population. We aimed to study the impact of HIV and of antiretrovirals on acute myocardial infarction (AMI). METHODS: We performed a cohort and a nested case-control study using the dataset of the Régie de l'Assurance Maladie du Québec. HIV-positive patients were identified using ICD-9 diagnostic codes and matched to HIV-negative patients. Within the HIV-positive cohort, cases of AMI were identified and matched to HIV-positive patients without AMI. The coprimary outcomes were the risk of AMI associated with HIV exposure in the cohort study and that associated with exposure to antiretrovirals in the case-control study. Data were analysed using Poisson and conditional logistic regression. RESULTS: About 7053 HIV-positive patients were matched to 27,681 HIV-negative patients. Incidence rates of AMI in the HIV+ cohort was 3.88 95% confidence interval (CI) (3.26 to 4.58) per 1000 patient-years, compared to 2.21 95% CI (1.93 to 2.52) per 1000 patient-years in the HIV cohort. The adjusted incidence ratio of AMI for HIV-infected patients was 2.11 95%CI (1.69 to 2.63). Among HIV+ patients, 125 AMI cases were matched with 1084 HIV+ patients. We found increased odds ratio (95% CI) of AMI associated with any exposure to abacavir 1.79 (1.16 to 2.76), P = 0.02, efavirenz 1.83 (1.21 to 2.76) P = 0.004, lopinavir 1.98 (1.24 to 3.16) P = 0.004, and ritonavir 2.29 (1.48 to 3.54) P < 0.001. CONCLUSIONS: HIV+ individuals were at higher risk of AMI than the general population, and several antiretrovirals were associated with an increased risk of AMI. Results should be interpreted with caution in absence of data on smoking and HIV clinical status.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".