使用行政数据库识别患有外周动脉疾病的患者的挑战
Pishoy Gouda1, Douglas C Dover2, Elinor Mengxiao Wang2
1Mazankowski Alberta Heart Institute, University of Alberta, Division of Cardiology, Edmonton, Alberta, Canada.
CJC open
|September 25, 2023
概括
鉴定患有外周动脉疾病 (PAD) 和冠状动脉疾病 (CAD) 的患者是困难的. 目前的模型在CAD患者中难以准确检测PAD,这凸显了对改进诊断工具的需求.
科学领域:
- 心血管医学 心血管医学
- 公共卫生 公共卫生
- 医疗信息学 医疗信息学
背景情况:
- 周围动脉疾病 (PAD) 在冠状动脉疾病 (CAD) 患者中显著增加了发病率.
- 准确识别患有CAD和PAD的个体是一个持续的临床挑战.
- 同时出现的PAD和CAD需要因心血管风险增加而量身定制的管理策略.
研究的目的:
- 评估预测模型在识别患有并发冠状动脉疾病和外周动脉疾病的患者中的有效性.
- 评估设计用于检测基线PAD并预测未来PAD发展的大型CAD队列中的模型的性能.
主要方法:
- 利用链接的行政数据库,包括207,026名被诊断患有CAD的个人.
- 数据涵盖2002年至2019年,平均随访期为4.7年.
- 应用预测模型以确定基线时的流行PAD和随访期间的事件PAD.
主要成果:
- 为确定基线PAD和预测未来PAD而开发的模型表现出不良的校准和歧视.
- 基线PAD模型的c统计值为0.618,对于未来的PAD模型,它是0.583.
- 这些结果表明模型在可靠识别同时患有CAD和PAD的患者方面不足.
结论:
- 由于缺乏其他变量,目前的预测模型不足以准确识别患有并发性冠状动脉疾病和外周动脉疾病的患者.
- 需要进一步的研究来开发更强大的模型,包括额外的临床和人口统计数据.
- 改进的识别策略对于优化患者护理和降低高风险人群的发病率至关重要.
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