Building a machine learning-based risk prediction model for second-trimester miscarriage.

Background: Second-trimester miscarriage is a common adverse pregnancy outcome that imposes substantial economic and psychological pressures on both the physical and mental well-being of patients and their families. Currently, there is a scarcity of research on predictive models for the risk of second-trimester miscarriage.

Methods: Clinical data were retrospectively collected from patients who were in the second trimester of pregnancy (between 14+0 and 27+6 weeks gestation), whose main diagnosis was "threatened abortion" and who were hospitalized at the Women and Children's Hospital of Ningbo University from January 2020 to October 2023.

Establishment of a predictive model for postpartum hemorrhage in twins: a retrospective study.

Objective: To explore the risk factors and develop a predictive model for postpartum hemorrhage in twin pregnancies.

Methods: All patients who gave birth at Ningbo Women and Children's Hospital from January 2018 to August 2022 were recruited. Patients were randomly allocated to a training cohort (n[Formula: see text]1395) validation cohort (n[Formula: see text]650) at a 7:3 ratio.