Prediction of progression to severe disease in women with late preterm hypertensive disorders of pregnancy

Abstract

In women with non-severe hypertension in pregnancy near term, progression to severe disease can be predicted. This model requires external validation before it can be applied in practice.

Prediction of adverse maternal and perinatal outcomes in preeclampsia based on B-type natriuretic peptide: a retrospective study

“…The degree of proteinuria cannot be used as a single indication for termination of pregnancy, but it can still reflect renal damage, and large amounts of proteinuria can lead to hypoalbuminemia, thereby affecting the outcome of PE. Increasing age was a risk factor for adverse perinatal outcomes in our study (OR: 1.072, 95% CI: 1.015-1.132), which was the same as other studies (6,7). Study had shown that in women ≥35 years old, the risk of adverse outcomes such as stillbirth, preterm birth and low birth weight was higher than that in the control group (20-34 years old) (42).…”

“…Other factors in the prediction model of maternal outcomes are SBP, AST, CR, and ALB. The results of our model are consistent with those of some established models (4)(5)(6)(7)(8)(32)(33)(34), indicating that elevated SBP, AST, and CR levels as well as reduced ALB levels predict the increase of adverse maternal outcomes, so changes in these indicators need to be closely monitored during clinical treatment. Other factors in the prediction model of perinatal outcomes were maternal age, HB, BMI, and proteinuria.…”

“…There is controversy regarding the predictive role of proteinuria on adverse outcomes in PE. Some studies have suggested that proteinuria is a good indicator for predicting adverse outcomes (6,32,38), but others have shown otherwise (39). In PE, the women with proteinuria >3 g/24 h had a lower birth weight, while the women with proteinuria >5 g/24 h had a significantly higher incidence of fetal growth restriction or stillbirth (40).…”

“…Therefore, early prediction of adverse outcomes of PE is essential to improve the prognosis of mothers and infants. In recent years, researchers from various countries have devoted themselves to exploring the prediction of adverse outcomes of PE, and established some prediction models (4)(5)(6)(7)(8). These predictive models have their own advantages and disadvantages.…”

Comparison of Multivariable Logistic Regression and Other Machine Learning Algorithms for Prognostic Prediction Studies in Pregnancy Care: Systematic Review and Meta-Analysis

“…The characteristics of study populations showed that pregnant women and fetuses or newborns were the populations of most studies developed using LR and non-LR models, respectively. Among pregnant women, the LR algorithm was mostly applied to develop predictions for outcome categories of obstetric labor (13/77, 17%) [36,46,47,54,57,62,64,70,83,86,91,97,103], pregnancy-induced hypertension (12/77, 16%) [30,31,43,48,55,65,66,68,76,81,93,105], and gestational diabetes (7/77, 9%) [33,45,49,84,94,100,104]. Among fetus or newborn populations, non-LR algorithms were mostly applied to develop predictions for outcome categories of premature birth (12/50, 24%) [111,112,115,116,118,119,121,122,125,130,141,143] and fetal distress (9/50, 18%) [113,…”