Vitamin A and Zinc Supplementation Among Pregnant Women to Prevent Placental Malaria: A Randomized, Double-Blind, Placebo-Controlled Trial in Tanzania
Bibliographic record
Abstract
Vitamin A and zinc are important for immune function and may improve host defense against malaria and reduce the risk of adverse pregnancy outcomes. Our objective was to determine whether daily oral supplementation with either or both nutrients starting in the first trimester reduces the risk of placental malaria and adverse pregnancy outcomes. We undertook a randomized, double-blind placebo-controlled trial with a factorial design among 2,500 human immunodeficiency virus–negative primigravid or secundigravid pregnant women in their first trimester of pregnancy in Dar es Salaam, Tanzania. We randomly allocated equal numbers of participants to 2,500 IU of vitamin A, 25 mg of zinc, both 2,500 IU of vitamin A and 25 mg of zinc, or a placebo until delivery. A total of 625 participants were allocated to each treatment group. Our primary outcome, placental malaria infection (past or current), was assessed in all randomized participants for whom placental samples were obtained at delivery (N = 1,404), which represents 56% of total participants and 62% of all pregnancies lasting 28 weeks or longer (N = 2,266). Birth outcomes were obtained for 2,434 of the 2,500 randomized participants. Secondary outcomes included small for gestational age (SGA) births and prematurity. All analyses were intent to treat. Those who received zinc had a lower risk of histopathology-positive placental malaria compared with those who did not receive zinc (risk ratio = 0.64, 95% confidence interval = 0.44, 0.91), but neither nutrient had an effect on polymerase chain reaction–positive malaria, SGA, or prematurity. No safety concerns were identified. We recommend additional studies in other geographic locations to confirm these findings.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".