使用重复测量来预测2型糖尿病患者心血管风险
Krishna M Gokhale1, Joht Singh Chandan1, Chris Sainsbury1
1Institute of Applied Health Research, University of Birmingham, Birmingham, United Kingdom.
The American journal of cardiology
|April 29, 2024
概括
这项研究发现,使用重复患者数据仅略有改善了2型糖尿病 (T2DM) 患者心血管疾病 (CVD) 风险预测. 需要进一步的研究来增强T2DM个体的CVD风险模型.
科学领域:
- 心脏病学 心脏病学
- 内分泌学 在内分泌学.
- 医疗信息学 医疗信息学
背景情况:
- QRISK心血管疾病 (CVD) 风险评估模型需要对2型糖尿病患者 (T2DM) 进行优化.
- 对T2DM患者的重复测量数据可能会提高心血管疾病风险预测的准确性.
研究的目的:
- 评估是否结合时间变化,重复测量数据可以提高QRISK模型对T2DM患者心血管疾病的预测能力.
- 支持对T2DM个体进行心血管疾病预防策略的决策.
主要方法:
- 利用IQVIA医学研究数据英国初级保健数据库来识别T2DM患者 (25-85岁) 没有先前使用心血管疾病或他类药物.
- 采用Cox的比例危险模型与时间依赖的共变量来估计心血管疾病风险,分析传统和非传统因素.
- 为男性和女性单独验证模型,评估歧视 (哈雷尔的C指数) 和校准.
主要成果:
- 包括198,835名T2DM患者 (90,466名女性,180,143名男性).
- 模型显示出良好的歧视 (C指数:女性0.71,男性0.69) 和校准.
- 与标准QRISK模型相比,包括时间变化的重复测量仅在心血管疾病风险预测方面取得了轻微的改善.
结论:
- 目前对T2DM患者的QRISK模型性能仅通过结合时间变化的数据而略有改善.
- 建议对时间变化的模型中的额外共变量进行进一步的研究,以提高T2DM中CVD风险预测的准确性.
- 优化心血管疾病风险预测模型对于T2DM群体的有效预防策略至关重要.
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