构建和验证用于预测中风后性风险的诺莫格拉姆模型:一项回顾性研究
Qian Xie1, Jingling Zhu2, Xuanling Cheng1
1Department of Tuina, Dongguan Hospital of Traditional Chinese Medicine, Guangzhou University of Chinese Medicine, Dongguan, China.
Annals of medicine
|December 23, 2025
概括
一种新的诺莫格拉姆模型有效地利用常规临床数据预测了手术后肩部硬 (PSS) 的风险. 这种工具有助于临床医生做出决策,尽管需要外部验证.
科学领域:
- 临床医学 临床医学
- 整形外科 整形外科 整形外科
- 预测分析是一种预测分析.
背景情况:
- 手术后肩部硬 (PSS) 在骨科康复中构成了重大挑战.
- 准确预测PSS风险对于积极的临床管理和患者的结果至关重要.
研究的目的:
- 开发和验证术后肩部硬 (PSS) 风险的预测模型.
- 确定与PSS发展相关的关键临床预测因素.
- 为临床医生提供一个实际的决策工具.
主要方法:
- 用LASSO-逻辑回归分析来确定重要的预测因素.
- 通过使用常规临床数据构建了一个名录模型并进行内部验证.
- 用曲线下的面积 (AUC) 和校准曲线来评估模型性能.
- 决策曲线分析 (DCA) 和校准指数 (CIC) 用于模型评估.
主要成果:
- 确定了七个预测因素:C-反应蛋白,白蛋白,肌酸酶,禁食血糖,高脂血症,睡眠障碍和手动肌肉测试 (MMT) 得分.
- 诺米图表表现出强大的预测性能,AUC值为0.844 (训练) 和0.842 (验证).
- 观察到优秀的校准,在验证集中风险的高估是最小的.
结论:
- 基于常规的临床数据开发的诺米克图有效预测PSS风险.
- 该模型作为临床决策的实际工具.
- 建议进一步进行多中心外部验证,以确认其广泛适用性.
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