Pharmacometric Evaluation of Sulfadoxine-Pyrimethamine-Amodiaquine and Dihydroartemisinin-Piperaquine Seasonal Malaria Chemoprevention in Northern Uganda
Bibliographic record
Abstract
BACKGROUND: Seasonal malaria chemoprevention (SMC) using monthly sulfadoxine-pyrimethamine-amodiaquine (SPAQ) is being deployed East Africa, where antimalarial drug resistance levels are high. Dihydroartemisinin-piperaquine (DP) is a potential alternative. METHODS: A prospective 28 day pharmacometric assessment of SMC was conducted in Karamoja, Northern Uganda. In two villages children received SPAQ and in a third were randomized to DP vs. no SMC The primary outcome was malaria infection defined by capillary blood sample qPCR positivity on day 28, or presentation with fever and slide or rapid test positivity after day 2. RESULTS: Baseline qPCR malaria parasitemia prevalence among 1250 enrolled children was 46% (575/1250); P. falciparum 85%, other malarias (mainly P. ovale) 25%. Breakthrough parasitemias occurred in 7% (33/496) of DP, 31% (158/504) of SPAQ, and 39% (98/250) of no drug recipients. Clinical malaria (all P. falciparum) developed in 17% of no drug (42/250; 1 severe), 8% of SPAQ (38/504; 2 severe) and 2% of DP (13/496) recipients. Adjusted protective efficacies against all malaria parasitemia, P. falciparum parasitemia, and clinical malaria were SPAQ; 56% (95%CI 35-70%), 46% (11-68%), and 60% (27-78%)and for DP; 84% (77-89%), 86% (75-92%) and 86% (74-92%) respectively. Some asymptomatic P. falciparum infections were not cleared by SPAQ. All 260 P. falciparum isolates genotyped were Pfcrt K76 (haplotype CVMNK, a marker of 4-aminoquinoline susceptibility) and most were quintuple Pfdhfr/dhps mutants (i.e. relatively SP resistant). The chemoprevention drug exposure-response relationship was strong for desethylamodiaquine, but weak for sulfadoxine. CONCLUSIONS: SPAQ SMC had low clinical and parasitological chemopreventive efficacy in Northern Uganda whereas dihydroartemisinin-piperaquine was effective.
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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".