Antiretroviral Choice for HIV Impacts Antimalarial Exposure and Treatment Outcomes in Ugandan Children
Bibliographic record
Abstract
BACKGROUND: The optimal treatment of malaria in human immunodeficiency virus (HIV)-infected children requires consideration of critical drug-drug interactions in coinfected children, as these may significantly impact drug exposure and clinical outcomes. METHODS: We conducted an intensive and sparse pharmacokinetic/pharmacodynamic study in Uganda of the most widely adopted artemisinin-based combination therapy, artemether-lumefantrine. HIV-infected children on 3 different first-line antiretroviral therapy (ART) regimens were compared to HIV-uninfected children not on ART, all of whom required treatment for Plasmodium falciparum malaria. Pharmacokinetic sampling for artemether, dihydroartemisinin, and lumefantrine exposure was conducted through day 21, and associations between drug exposure and outcomes through day 42 were investigated. RESULTS: One hundred forty-five and 225 children were included in the intensive and sparse pharmacokinetic analyses, respectively. Compared with no ART, efavirenz (EFV) reduced exposure to all antimalarial components by 2.1- to 3.4-fold; lopinavir/ritonavir (LPV/r) increased lumefantrine exposure by 2.1-fold; and nevirapine reduced artemether exposure only. Day 7 concentrations of lumefantrine were 10-fold lower in children on EFV vs LPV/r-based ART, changes that were associated with an approximate 4-fold higher odds of recurrent malaria by day 28 in those on EFV vs LPV/r-based ART. CONCLUSIONS: The choice of ART in children living in a malaria-endemic region has highly significant impacts on the pharmacokinetics and pharmacodynamics of artemether-lumefantrine treatment. EFV-based ART reduces all antimalarial components and is associated with the highest risk of recurrent malaria following treatment. For those on EFV, close clinical follow-up for recurrent malaria following artemether-lumefantrine treatment, along with the study of modified dosing regimens that provide higher exposure, is warranted.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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".