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Mid‐trimester β‐hCG levels incorporated in a multifactorial model for the prediction of severe pre‐eclampsia
Author(s) -
Lee LongChien,
Sheu BorChing,
Shau WenYi,
Liu DouMin,
Lai TaiJung,
Lee YuHsiang,
Huang SuCheng
Publication year - 2000
Publication title -
prenatal diagnosis
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.956
H-Index - 97
eISSN - 1097-0223
pISSN - 0197-3851
DOI - 10.1002/1097-0223(200009)20:9<738::aid-pd917>3.0.co;2-r
Subject(s) - eclampsia , medicine , obstetrics , pregnancy , preeclampsia , second trimester , gynecology , gestation , biology , genetics
Pre‐eclampsia remains a major cause of perinatal morbidity and mortality worldwide. Proposed predicting tests for early detection of pregnant women destined to develop pre‐eclampsia remain unsatisfactory. The aim of this study was to investigate the clinical utility of combining mid‐trimester maternal serum β‐human chorionic gonadotrophin (MShCG) levels with selected clinical determining factors as a multifactorial predictive test for pre‐eclampsia. Thirty‐nine cases with mild pre‐eclampsia and 56 with severe pre‐eclampsia were recruited as the study groups. Normotensive women (957) were enrolled as controls. Potential determining risk factors for severe pre‐eclampsia were selected using a multiple logistic regression to build various combined prediction models. A receiver–operator characteristic curve was employed to assess the performance of each prediction test for pre‐eclampsia. The prediction efficacy of each test was examined by the area under the curve (AUC). Our data show that mid‐trimester MShCG levels significantly correlated with severity of pre‐eclampsia (Spearman rank correlation coefficient=0.195, p <0.001). Women with mild pre‐eclampsia had a 2.61‐times greater chance, while women with severe pre‐eclampsia had a 6.13‐times greater chance of having MShCG exceeding 2.0 multiples of the median than did women with a normal pregnancy. A combined prediction model composed of MShCG levels, body mass index (BMI), parity, and age as a predictive test for severe pre‐eclampsia was superior to MShCG levels alone (AUC 0.765 versus 0.648). The integrated multifactorial model could identify women at risk early on for developing severe pre‐eclampsia, with a sensitivity of 70% and a specificity of 71%. Thus, we demonstrate a potentially effective and convenient method by which women at risk for developing severe pre‐eclampsia can be identified early, based on a multifactorial predictive model composed of midtrimester MShCG levels, BMI, parity, and age. Copyright © 2000 John Wiley & Sons, Ltd.