Constructing a logistic regression-based prediction model for subsequent early pregnancy loss in women with pregnancy loss.

ABSTRACT:

Objectives

The aim of this study is to construct a nomogram for predicting subsequent early pregnancy loss in women with a history of pregnancy loss, which may increase well-being and the capacity for managing reproductive options.

Materials and methods

We conducted a retrospective analysis of medical records from women with a history of pregnancy loss at the Reproductive Medicine Center of Lanzhou University Second Hospital between January 2019 and December 2022. A cohort of 718 patients was selected for the study. We structured our data into a training set of 575 cases (80% of the cohort) and a test set of 143 cases (20%). To identify significant predictors, we applied a stepwise forward algorithm guided by the Akaike Information Criterion (AIC) to the training set. Model

SUBMITTER: Ding N 

PROVIDER: S-EPMC11823067 | biostudies-literature | 2025 Feb

REPOSITORIES: biostudies-literature