【摘要】 利用患者的重复测量数据提升预测模型的分类能力是当前临床预测模型开发中的关键方法问题。本研究拟探索两阶段模型的统计建模策略在基于重复测量数据开展非时变结局预测模型构建中的应用和价值，并以严重产后出血风险预测为例，从数据结构、基本原理、软件操作和模型评价等多个维度，介绍两阶段模型的实现过程，以期为临床研究者提供方法学指导。更多还原

【Abstract】 The use of repeated measurement data from patients to improve the classification ability of prediction models is a key methodological issue in the current development of clinical prediction models. This study aims to investigate the statistical modeling approach of the two-stage model in developing prediction models for non-time-varying outcomes using repeated measurement data. Using the prediction of the risk of severe postpartum hemorrhage as a case study, this study presents the implementation process of the two-stage model from various perspectives, including data structure, basic principles, software utilization, and model evaluation, to provide methodological support for clinical investigators.更多还原