Statistical Analysis
The Pre-E cohort was evaluated as a single group, as well as divided into 2 groups, non-severe Pre-E and severe Pre-E, using the American College of Obstetrics and Gynecology criteria for Pre-E with severe features [18]. Basic clinical and demographic comparisons were performed using Chi-Square tests for categorical variables and Students t-tests and Wilcoxon rank-sum tests for continuous variables, depending on the linearity of the data. Pairwise comparisons were made using a Bonferroni correction. To analyze wheezing outcomes, a participant level variable of ever/never wheezed was created for participants who had at least one survey response in the the first six months of surveys, as well as after 6 months. We then analyzed all the survey data from infants meeting this criterion. For each of the main outcomes, simple bivariate analyses were first performed and those variables with significance of P≤0.10 were included in a multivariable model. In addition to these variables, we included clinically relevant ones, e.g. sex, race, etc. For the outcome of wheezing, using the dichotomous wheezing outcome as described above, logistic regression analysis was performed using multivariable model including Pre-E group, sex, GA, mother’s smoking history, family history of asthma, and antenatal steroid use. IPFT outcomes were analyzed with raw data adjusting for race, sex, and body length at testing in multivariable models. Simple t-tests were used for the bivariate analyses and ANCOVA models were performed for the adjusted models, with the covariates sex, race, length, and GA. Fetal growth restriction, antenatal steroid use, and family history of asthma were also included as covariates based on the results of the bivariate analysis. All analytic assumptions were verified, collinearity was assessed for multivariable models, and analyses were performed using SAS v9.4 (SAS Institute, Cary, NC).