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Reproductive and Urinary Physiology Commons™
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Full-Text Articles in Reproductive and Urinary Physiology
Routinely Collected Antenatal Data For Longitudinal Prediction Of Preeclampsia In Nulliparous Women: A Population‑Based Study, Anna Sandstrom, Jonathan Snowden, Matteo Bottai, Olof Stephansson, Anna-Karin Wikström
Routinely Collected Antenatal Data For Longitudinal Prediction Of Preeclampsia In Nulliparous Women: A Population‑Based Study, Anna Sandstrom, Jonathan Snowden, Matteo Bottai, Olof Stephansson, Anna-Karin Wikström
OHSU-PSU School of Public Health Faculty Publications and Presentations
The objective was to evaluate the sequentially updated predictive capacity for preeclampsia during pregnancy, using multivariable longitudinal models including data from antenatal care. This population-based cohort study in the Stockholm-Gotland Counties, Sweden, included 58,899 pregnancies of nulliparous women 2008–2013. Prospectively collected data from each antenatal care visit was used, including maternal characteristics, reproductive and medical history, and repeated measurements of blood pressure, weight, symphysis-fundal height, proteinuria, hemoglobin and blood glucose levels. We used a shared-effects joint longitudinal model including all available information up until a given gestational length (week 24, 28, 32, 34 and 36), to update preeclampsia prediction sequentially. …
Predicting Vaginal Birth After Previous Cesareavn: Using Machine-Learning Models And A Population-Based Cohort In Sweden, Charlotte Wollmann, Kyle D. Hart, Can Liu, Aaron B. Caughey, Olof Stephansson, Jonathan M. Snowden
Predicting Vaginal Birth After Previous Cesareavn: Using Machine-Learning Models And A Population-Based Cohort In Sweden, Charlotte Wollmann, Kyle D. Hart, Can Liu, Aaron B. Caughey, Olof Stephansson, Jonathan M. Snowden
OHSU-PSU School of Public Health Faculty Publications and Presentations
Introduction: Predicting a woman’s probability of vaginal birth after cesarean could facilitate the antenatal decision-making process. Having a previous vaginal birth strongly predicts vaginal birth after cesarean. Delivery outcome in women with only a cesarean delivery is more unpredictable. Therefore, to better predict vaginal birth in women with only one prior cesarean delivery and no vaginal deliveries would greatly benefit clinical practice and fill a key evidence gap in research. Our aim was to predict vaginal birth in women with one prior cesarean and no vaginal deliveries using machine-learning methods, and compare with a US prediction model and its further …