Development and validation of nomograms to predict clinical outcomes of preeclampsia.

ABSTRACT:

Background

Preeclampsia (PE) is one of the most severe pregnancy-related diseases; however, there is still a lack of reliable biomarkers. In this study, we aimed to develop models for predicting early-onset PE, severe PE, and the gestation duration of patients with PE.

Methods

Eligible patients with PE were enrolled and divided into a training (n = 253) and a validation (n = 108) cohort. Multivariate logistic and Cox models were used to identify factors associated with early-onset PE, severe PE, and the gestation duration of patients with PE. Based on significant factors, nomograms were developed and evaluated using the area under the curve (AUC) and a calibration curve.

Results

In the training cohort, multiple gravidity experience (p = 0.005), lo

SUBMITTER: Xia Y 

PROVIDER: S-EPMC10972945 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature