Characterizing heart failure and its subtypes in people living with <scp>HIV</scp>
Bibliographic record
Abstract
OBJECTIVE: People living with HIV have an increased risk of heart failure (HF). There are different subtypes of HF. Knowledge about the factors differentiating HF subtypes in people with HIV is limited but necessary to guide preventive measures and treatment. METHODS: A retrospective review of medical records was undertaken in people with HIV aged ≥18 years who received care at the University of Miami/Jackson Memorial HIV Clinic between January 2017 and November 2019 (N = 1166). Patients with an echocardiogram available for review (n = 305) were included. HF was defined as a documented diagnosis of any HF subtype (n = 52). We stratified those with HF by their ejection fraction (EF) into HF with preserved EF (HFpEF), HF with borderline EF, or HF with reduced EF (HFrEF). RESULTS: The prevalence of HF was 4.5%. The cohort included 46.2% females and 75% self-identified African Americans. Those with HF had a higher prevalence of hypertension, prior myocardial infarction, angina, coronary artery disease, percutaneous coronary intervention, coronary artery bypass grafting, diastolic dysfunction, and left ventricle hypertrophy. People with HIV with HF with borderline EF exhibited more coronary artery disease than those with HFpEF. CONCLUSIONS: We characterize HF in people with HIV in South Florida and report the prevalence of HF and HF subtypes. Only a small percentage of patients had echocardiograms performed, suggesting an ongoing need for recognition of the increased risk of HF in people living with HIV, and raising the concern about lack of awareness contributing to underdiagnosis and missed treatment opportunities in this population.
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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 | 0.001 |
| 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".