HIV Immunosuppression and Antimalarial Efficacy: Sulfadoxine‐Pyrimethamine for the Treatment of Uncomplicated Malaria in HIV‐Infected Adults in Siaya, Kenya
Bibliographic record
Abstract
BACKGROUND: The altered immune response of persons with human immunodeficiency virus (HIV) infection could result in increased rates of antimalarial treatment failure. We investigated the influence of HIV infection on the response to sulfadoxine-pyrimethamine treatment. METHODS: Febrile adults with Plasmodium falciparum parasitemia were treated with sulfadoxine-pyrimethamine and were monitored for 28 days. HIV status and CD4 cell count were determined at study enrollment. RESULTS: Of the adults enrolled in the study, 508 attended all follow-up visits, including 130 HIV-uninfected adults, 256 HIV-infected adults with a high CD4 cell count (> or =200 cells/ micro L), and 122 HIV-infected adults with a low CD4 cell count (<200 cells/ micro L). The hazard of treatment failure at day 28 of follow-up was significantly higher for HIV-infected adults with a low CD4 cell count (20.5%) than for HIV-uninfected adults (7.7%). Anemia (hemoglobin level, <110 g/L) modified the effect of HIV status on treatment failure. When we controlled for fever and parasite density, the hazard of treatment failure for HIV-infected adults with a low CD4 cell count and anemia was 3.4 times higher than that for HIV-uninfected adults (adjusted hazard ratio, 3.38; 95% confidence interval, 1.56-7.34). CONCLUSIONS: HIV-infected persons with a low CD4 cell count and anemia have an increased risk of antimalarial treatment failure. The response to malaria treatment in HIV-infected persons must be carefully monitored. Proven measures for the control and prevention of malaria must be incorporated into the basic package of services provided by HIV/acquired immunodeficiency syndrome care and treatment programs in malarious areas.
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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 | 0.000 | 0.000 |
| 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) | 0.001 | 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".