Progress and Prospects of Clinical Prediction Models for Risk of Stroke Recurrence in Ischemic Stroke

doi:10.3969/j.issn.1673-5765.2023.07.001

Abstract

Abstract: In the era of big data and precision medicine, clinical prediction models are increasingly important in precise risk stratification, personalized diagnosis, and management. However, existing ischemic stroke recurrence risk prediction models vary significantly in terms of the population used for development, predictive factors, predicted outcomes, development methods, and predictive performance. Additionally, limitations in development methods, reporting, external validation, and model impact research have limited their clinical applicability. Therefore, future research on clinical prediction models should prioritize the validation and evaluation of existing models, while also adhering to methodological standards when developing new prediction models. This includes selecting predictive factors, model fitting, presentation methods, and reporting results, with the aim of enhancing predictive performance.

Key words: Ischemic stroke; Stroke recurrence; Clinical prediction model; Risk score

摘要： 临床预测模型在大数据与精准医学时代对精准风险分层、个性化诊疗和管理愈发重要。现有的缺血性卒中复发风险预测模型在开发队列人群、预测因子、预测结局、开发方法以及预测性能上存在较大差异。此外，开发方法上的缺陷、报告内容上的不完整以及外部验证和模型影响研究的缺失，使其临床应用效果受限。因此，后续的临床预测模型研究，一方面，应重视现有模型的验证和评价；另一方面，在开发新预测模型时，在预测因子的选取、模型的选用和拟合、展示方式及结果报告上，应遵循相应的方法学规范，以提高预测性能。

关键词: 缺血性卒中; 卒中复发; 临床预测模型; 风险评分

GU Hongqiu, YANG Kaixuan, JIANG Yingyu, DU Kejin, RAO Zhenzhen, YANG Xin, WANG Chunjuan, XIONG Yunyun, JING Jing, LI Zixiao. Progress and Prospects of Clinical Prediction Models for Risk of Stroke Recurrence in Ischemic Stroke [J]. Chinese Journal of Stroke, 2023, 18(07): 731-739.

谷鸿秋, 杨凯璇, 姜英玉, 杜柯瑾, 饶蓁蓁, 杨昕, 王春娟, 熊云云, 荆京, 李子孝. 缺血性卒中患者卒中复发风险预测模型研究进展及展望 [J]. 中国卒中杂志, 2023, 18(07): 731-739.

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