Anti-Retroviral Treatment Outcomes among Older Adults in Zomba District, Malawi
Bibliographic record
Abstract
There are approximately 3 million people aged 50 and older in sub-Saharan Africa who are HIV-positive. Despite this, little is known about the characteristics of older adults who are on treatment and their treatment outcomes.A retrospective cohort analysis was performed using routinely collected data with Malawi Ministry of Health monitoring tools from facilities providing antiretroviral therapy services in Zomba district. Patients aged 25 years and older initiated on treatment from July 2005 to June 2010 were included. Differences in survival, by age group, were determined using Kaplan-Meier survival plots and Cox proportional hazards regression models.There were 10,888 patients aged 25 and older. Patients aged 50 and older (N = 1419) were more likely to be male (P<0.0001) and located in rural areas (P = 0.003) than those aged 25-49. Crude survival estimates among those aged 50-59 were not statistically different from those aged 25-49 (P = 0.925). However, survival among those aged 60 and older (N = 345) was worse (P = 0.019) than among those 25-59. In the proportional hazards model, after controlling for sex and stage at initiation, survival in those aged 50-59 did not differ significantly from those aged 25-49 (hazard ratio 1.00 (95% CI: 0.79 to 1.27; P = 0.998) but the hazard ratio was 1.46 (95% CI: 1.03 to 2.06; P = 0.032) for those aged 60 and older compared to those aged 25-49.Treatment outcomes of those aged 50-59 are similar to those aged 25-49. A better understanding of how older adults present for and respond to treatment is critical to improving HIV services.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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".