Effect of cardio-metabolic risk factors on all-cause mortality among HIV patients on antiretroviral therapy in Malawi: A prospective cohort study
Bibliographic record
Abstract
Cardiovascular disease (CVD) risk among people living with HIV is elevated due to persistent inflammation, hypertension and diabetes comorbidity, lifestyle factors and exposure to antiretroviral therapy (ART). Data from Africa on how CVD risk affects morbidity and mortality among ART patients are lacking. We explored the effect of CVD risk factors and the Framingham Risk Score (FRS) on medium-term ART outcomes.A prospective cohort study of standardized ART outcomes (Dead, Alive on ART, stopped ART, Defaulted and Transferred out) was conducted from July 2014-December 2016 among patients on ART at a rural and an urban HIV clinic in Zomba district, Malawi. The primary outcome was Dead. Active defaulter tracing was not done and patients who transferred out and defaulted were excluded from the analysis. At enrolment, hypertension, diabetes and dyslipidemia were diagnosed, lifestyle data collected and the FRS was determined. Cox-regression analysis was used to determine independent risk factors for the outcome Dead.Of 933 patients enrolled, median age was 42 years (IQR: 35-50), 72% were female, 24% had hypertension, 4% had diabetes and 15.8% had elevated total cholesterol. The median follow up time was 2.4 years. Twenty (2.1%) patients died, 50 (5.4%) defaulted, 63 (6.8%) transferred out and 800 (85.7%) were alive on ART care (81.7% urban vs. 89.9% rural). In multivariable survival analysis, male gender (aHR = 3.28; 95%CI: 1.33-8.07, p = 0.01) and total/HDL cholesterol ratio (aHR = 5.77, 95%CI: 1.21-27.32; p = 0.03) were significantly associated with mortality. There was no significant association between mortality and hypertension, body mass index, central obesity, diabetes, FRS, physical inactivity, smoking at enrolment, ART regimen and WHO disease stage.Medium-term all-cause mortality among ART patients was associated with male gender and elevated total/HDL cholesterol ratio.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".