Brief Report: Insomnia and Risk of Myocardial Infarction Among People With HIV
Bibliographic record
Abstract
BACKGROUND: Insomnia is common among people with HIV (PWH) and may be associated with increased risk of myocardial infarction (MI). This study examines the association between insomnia and MI by MI type among PWH. SETTING: Longitudinal cohort study of PWH at 5 Centers for AIDS Research Network of Integrated Clinical Systems sites. METHODS: Clinical data and patient-reported measures and outcomes from PWH in care between 2005 and 2018 were used in this study. Insomnia, measured at baseline, was defined as having difficulty falling or staying asleep with bothersome symptoms. The Centers for AIDS Research Network of Integrated Clinical Systems centrally adjudicates MIs using expert reviewers, with distinction between type 1 MI (T1MI) and type 2 MI (T2MI). Associations between insomnia and first incident MI by MI type were measured using separate Cox proportional hazard models adjusted for age, sex, race/ethnicity, traditional cardiovascular disease risk factors (hypertension, dyslipidemia, poor kidney function, diabetes, and smoking), HIV markers (antiretroviral therapy, viral suppression, and CD4 cell count), and stimulant use (cocaine/crack and methamphetamine). RESULTS: Among 12,448 PWH, 48% reported insomnia. Over a median of 4.4 years of follow-up, 158 T1MIs and 109 T2MIs were identified; approximately half of T2MIs were attributed to sepsis or stimulant use. After adjustment for potential confounders, we found no association between insomnia and T1MI (hazard ratio = 1.05, 95% confidence interval: 0.76 to 1.45) and a 65% increased risk of T2MI among PWH reporting insomnia compared with PWH without insomnia (hazard ratio = 1.65, 95% confidence interval: 1.11 to 2.45). CONCLUSIONS: PWH reporting insomnia are at an increased risk of T2MI, but not T1MI, compared with PWH without insomnia, highlighting the importance of distinguishing MI types among PWH.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".