Statistical analysis.
peripheral blood malaria parasitemia, parasitemia
MALARIA, PARASITEMIA, REGRESSIONS, SECONDARY, REGRESSION, PRETERM DELIVERY
The sample size of 440 pregnant women per group was planned to give 80% power at a 5% level of significance to detect a 40% reduction in the rate of preterm delivery, which was the trial’s main hypothesis.Treatment allocation for the study was broken for the analysis of the trial’s main hypothesis. The statistician for this secondary analysis was different from the one doing the analyses for the main hypothesis. For this analysis the statistician (L.H.) merged the treatment allocation codes with maternal malaria parasitemia and fetal ultrasound data only after data were cleaned, the analysis plan was written, and the syntax for the analysis was done with a mock code. The analysis was based on the principle of intention-to-treat. We conducted statistical analyses with Stata 16.1 (StataCorp, College Station, TX).For maternal malaria parasitemia during pregnancy, we calculated the proportion of positive malaria parasitemia DBS samples by intervention group during the entire follow-up period and for the second trimester (from 14 weeks + 0 days to 26 weeks + 6 days of gestation) and third trimester (from 27 weeks + 0 days of gestation to the end) of pregnancy. We estimated the odds ratios (ORs) between the three groups with mixed-effects logistic regressions with random intercepts by participant. Because of different timing of enrollment in terms of gestational weeks, the timing and number of the 4-weekly assessments per pregnancy varied. There were also missed visits during the follow-up. We used a mixed effects model that allows uneven timing and in which the random effect captures individual intercepts despite the variation in number of observations per participant. We estimated two different models: one for the entire follow-up period and one estimating the OR for the second and third trimesters separately. The model estimating the OR for the second and third trimesters separately allowed the estimates of treatment effect to differ between trimesters. Based on the OR, we estimated marginal risk ratios between the intervention groups from the model for the entire follow-up period.We modeled biparietal diameter (mm) and femur length (mm) in relation to gestational weeks and intervention groups during the second and third trimesters of pregnancy by mixed-effects linear regression. Because fetal growth was not linear throughout pregnancy, we used two separate models to estimate the slopes for the second and third trimesters. The duration of pregnancy was centered to 14 weeks, which was the shortest duration of pregnancy at enrollment in the data. The model included random intercepts and random slopes by participants and allowed variation in the timing and number of ultrasound measurements per pregnancy. The random effects were allowed to be correlated. We estimated the change in biparietal diameter and femur length in relation to gestational weeks, with an interaction term between intervention groups and weeks of gestation, and the slope was multiplied by 4 to obtain the change per 4 gestational weeks. We calculated the differences in the rates of change between the three groups.The proportion of women with none or one previous pregnancy and with microscopic peripheral blood malaria parasitemia at enrollment was higher in the control group than in the intervention groups.The null hypothesis of no difference between groups was rejected if As an exploratory analysis, we performed tests for interaction between interventions and number of previous pregnancies (as a continuous variable), maternal HIV status, and bed net use at enrollment by using the likelihood ratio test and considered 