Prediction model for severe maternal morbidity in pregnant women with hypertensive disorders of pregnancy.

Objectives: To investigate risk factors for severe maternal morbidity (SMM) in pregnant women with hypertensive disorders of pregnancy (HDP) and to develop a risk prediction model.

Methods: A prospective observational cohort study was conducted among pregnant women who were hospitalized for hypertensive disorders of pregnancy (HDP) between January 2016 and December 2020 in Fujian College of Clinical Medicine for Obstetrics & Gynecology and Pediatrics, Fujian Province, China (a training set), and a risk predictive model was constructed. Pregnant women with HDP who were hospitalized between January 2021 and December 2021 were selected as a validation set. Concordance index (C-index) and calibration curves were used to test predictive model discrimination and calibration.

Results: We included 970 pregnant women (790 in the training set and 180 in the validation set). Least absolute shrinkage and selection operator regression was used to screen for nine related variables such as intra-uterine growth retardation (IUGR), diastolic blood pressure (DBP) and systolic blood pressure (SBP) at suspected diagnosis, total bilirubin, albumin (ALB), uric acid, total cholesterol, serum magnesium, and suspected gestational age. SBP at suspected diagnosis (OR =1.22, 95%CI:1.08-1.42) and total cholesterol (OR = 1.78, 95%CI:1.17-2.80) were independent risk factors of severe maternal morbidity in pregnant women with HDP. A nomogram was constructed, and internal validation of the nomogram model was done using the bootstrap self-sampling method. C-index in the training and the validation set was 0.798 and 0.909, respectively.

Conclusion: Our prediction model can be used to determine gestational hypertension severity in pregnant women.