Baseline ECG and Cardiovascular Outcomes in People With HIV: Insights From REPRIEVE
Bibliographic record
Abstract
BACKGROUND: With antiretroviral therapy, people with HIV (PWH) have an increased burden of cardiovascular disease. The REPRIEVE (Randomized Trial to Prevent Vascular Events in HIV) trial demonstrated that pitavastatin reduces major adverse cardiovascular events (MACEs) among PWH at low to moderate traditional atherosclerotic risk. Electrocardiographic abnormalities are common in PWH, but little is known about their association with MACEs. We sought to examine whether baseline electrocardiographic abnormalities are associated with increased MACE risk among a global primary cardiovascular disease prevention cohort of PWH in REPRIEVE. METHODS: In this observational analysis, entry electrocardiographic abnormalities were adjudicated and classified as major or minor abnormalities. Multivariable cause-specific Cox proportional hazards models assessed the association of electrocardiographic abnormalities with MACEs while stratifying for treatment effect. The model improvement with the addition of the ECG to a model with the pooled cohort equations risk score was examined. RESULTS: Among 7719 participants (median age, 50 years; 69% men), 49% had ≥1 electrocardiographic abnormality, with 3% classified as major. Over a median of 5.6 years, a major electrocardiographic abnormality was associated with a 2.42-fold (95% CI, 1.49-3.91) higher hazard of incident MACEs, whereas minor abnormalities were not. Specific abnormalities associated with MACEs were chamber enlargement and infarct/ischemia pattern. No significant subgroup- or treatment-related interaction was observed. Adding electrocardiographic findings to traditional risk factors increased the C-statistic modestly (+0.01). CONCLUSIONS: Among PWH in REPRIEVE, electrocardiographic abnormalities were common, but major electrocardiographic abnormalities were rare. Though major abnormalities were associated with increased hazard of MACEs, routine electrocardiographic screening is unlikely to improve the prediction of future cardiovascular events in this primary prevention population with low to moderate cardiovascular risk.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".