Gender differences in antiretroviral treatment outcomes of HIV patients in rural Uganda
Bibliographic record
Abstract
Gender differences in treatment outcomes of 305 persons living with HIV receiving antiretroviral treatment (ART) in Kabarole district, western Uganda, were evaluated. The primary treatment outcome was virological suppression defined as HIV-1 RNA viral load (VL) <400 copies/ml and the secondary outcome measure was the increase in the CD4 cell count after six months on ART. Statistical analysis included descriptive, univariate, and multivariate methods. Proportionally, more females chose to seek treatment compared to males. After six months of treatment, females were more likely to have viral suppression (VL > 400 copies/ml) as compared to males (odds ratio 2.14, 95% confidence interval 0.99-4.63, p=0.05). While females had a significantly higher baseline CD4 cell count at initiation of treatment compared to males, the increase in CD4 cell count after six months on ART was similar in males and females. The reasons for better ART outcomes for females should be further investigated. Ideally, ART programs should work toward equitable treatment outcomes for men and women, if the cause of the gender differential lies in patient behavior and the way ART services are delivered.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".