Title

Algorithm of suboptimal health status, serum magnesium and calcium levels as a novel approach for prediction and identification of pregnant women likely to develop preeclampsia and adverse perinatal complications in a Ghanaian population

Document Type

Conference Proceeding

School

School of Medical and Health Sciences

Comments

Anto, E.O., Roberts,, P., Turpin, C. A. , Coall, D., Wang, Y., & Wang, W. ( August 7, 2019). Algorithm of Suboptimal Health Status, Serum Magnesium and Calcium Levels as a Novel Approach for Prediction and Identification of Pregnant Women Likely to Develop Preeclampsia and Adverse Perinatal Complications in a Ghanaian Population. Abstract presented at the 71st AACC Annual Scientific Meeting and Clinical lab Expo, Session 17, B-155

Abstract

Preeclampsia (PE) is among the leading cause of maternal and foetal morbidity and mortality associated with adverse perinatal complications. The most devastating are pregnant women who are yet to be diagnosed but complain of poor health-suboptimal health status (SHS). For the first time, we explored the usefulness of a SHS questionnaire-25 (SHSQ-25) along with serum magnesium and calcium levels for prediction and early identification of normotensive pregnant women who later develop PE and adverse perinatal outcome.

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