Objective To develop an evidence-based and simple screening tool to estimate calcium intake in pregnant women, suitable for use in daily clinical practice. Design Cross-sectional analysis within a cohort study Population and setting We extracted all data from the Rotterdam Periconceptional cohort (PREDICT study) conducted at the Erasmus MC, University Medical Centre in Rotterdam, the Netherlands, between November 2014 and December 2020. Methods Data was extracted from food frequency questionnaires. The estimated average requirement of 750 m/day was defined as the lower limit for an adequate calcium intake. We created a prediction model, using multivariable binary logistic regression with backward stepwise selection. We developed a simple screening tool based on the prediction model. Main outcome measures Probability of adequate calcium intake Results 694 participants are included, of which 201 (29%) had an adequate calcium intake. Total daily or weekly intakes of cheese, milk, and yogurt or curd were selected as predictors for the prediction model. The model had excellent discrimination (AUC 0.858), a good fit (Brier score 0.136, HL statistic p=0.499) and satisfactory calibration. The test accuracy measures were: sensitivity 80.9%, specificity 77.1%, PPV 89.7%, NPV 62.2%. A color coded digital screening tool was developed for use in clinical practice. Conclusions This evidence-based and simple screening tool is a reliable and efficient instrument to predict inadequate calcium intakes in pregnancy, which can easily be incorporated in daily clinical practice and existing pregnancy coaching platforms.

Objective: Prediction of preterm birth is currently not feasible, resulting in maternal and fetal overexposure to prenatal corticosteroids and unnecessary hospital admittance. Novel biomarkers seem to hold potential for predictive applicability, including non-invasive volatile organic compounds. In this study, we aimed to assess the potential of urinary volatile organic compound profiles (VOCs) in the identification of pregnant women at risk for preterm birth. Design, setting, population: We prospectively collected urine of women admitted for imminent preterm birth (≧ 24+0 weeks until 36+6 weeks), collected data on maternal characteristics, including urine cultures, time between admission and delivery and mode of delivery. Methods and main outcome measures: Urine samples were analyzed using gas chromatography coupled to an ion mobility spectrometer (GC-IMS). VOCs of women delivering preterm and term were compared. Results: Urinary VOCs differed between women delivering between 28+0 until 36+6 weeks compared to women admitted for imminent preterm birth but delivering at term (area under the curve: 0.70). We identified women with either chorioamnionitis (area under the curve: 0.72) and positive bacterial cultures (area under the curve: 0.97) based on their urinary VOCs. Conclusions: Urinary VOCs hold potential for non-invasive prediction of preterm birth. Furthermore, they may allow for detection of chorioamnionitis and urinary tract infections in the investigated population. These observations need to be validated in a larger population prior to clinical implementation. Funding: This study was funded by the Department of Obstetrics and Prenatal diagnosis. Keywords: preterm birth, premature delivery, volatile organic compounds, chorioamnionitis, urinary tract infection, infection