A Model for Predicting Polycystic Ovary Syndrome Using Serum AMH, Menstrual Cycle Length, Body Mass Index and Serum Androstenedione in Chinese Reproductive Aged Population: A Retrospective Cohort Study.

ABSTRACT:

Background

A clinical diagnosis of polycystic ovary syndrome (PCOS) can be tedious with many different required tests and examinations. Furthermore, women with PCOS have increased risks for several metabolic complications, which need long-term health management. Therefore, we attempted to establish an easily applicable model to identify such women at an early stage.

Objective

To develop an easy-to-use tool for screening PCOS based on medical records from a large assisted reproductive technology (ART) center in China.

Materials and methods

A retrospective observational cohort from Peking University Third Hospital was used in the study. Least Absolute Shrinkage and Selection Operator (LASSO) logistic regression with 10-fold cross-validation was applied to construct the

SUBMITTER: Xu H 

PROVIDER: S-EPMC8970043 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature