Use of Preventive Measures for Cardiovascular Disease in People With HIV
Bibliographic record
Abstract
Abstract Background Data on uptake of preventive measures for cardiovascular disease (CVD) in people with HIV are limited. Methods We determined the annual prevalence (2012–2021) of CVD preventive measures use for RESPOND participants with a very high (>10%) estimated D:A:D 10-year CVD risk who were eligible for each specific measure evaluated. We used binomial regression to assess factors associated with each preventative measure uptake. Results Between 2012 and 2021, the crude proportion of >10% estimated 10-year CVD risk individuals increased from 32.4% (n = 4272) to 52.1% (n = 5298). At the end of follow-up, among very high-risk individuals, 67.4% (1552/2303) with hypertension used antihypertensives, 55.9% (1562/2792) with dyslipidemia lipid-lowering drugs (LLDs), and 7.4% (159/2149) smokers ceased smoking, without significant changes over time. Conversely, a smaller proportion of individuals with diabetes received antidiabetics in later years (2012–2013: 60.3% [388/643] versus 2019–2020: 57.2% [459/803], global P = .0028). Use of angiotensin-converting enzyme inhibitors/angiotensin receptor blockers (ACEIs/ARBs) in those with hypertension or diabetes slightly declined before increasing again (42.1% [864/2052] versus 43.4% [1123/2585], global P = .0009). Individuals with ongoing viremia or intravenous drug use as HIV exposure group were less likely to cease smoking and use LLDs. Men ≥40 years and women ≥50 were more likely to use antihypertensives, ACEIs/ARBs, antidiabetics, and LLDs. The uptake of preventive measures was similar between sexes/genders. Conclusions The increasing proportion of individuals at very high estimated 10-year CVD risk without a corresponding increase in use of preventive measures calls for greater awareness of CVD risk management for people with HIV attending routine clinical care.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".