慢性阻塞性肺病中主要心血管和呼吸系统事件预测模型的开发和内部验证:全国初级保健电子医疗记录队列研究
Chris P Gale1,2,3, Mohit Bhutani4, Jeffrey Shi Kai Chan5
1Department of Cardiology, Leeds Teaching Hospitals NHS Trust, Leeds, UK.
Pragmatic and observational research
|March 16, 2026
概括
一个新的模型预测慢性阻塞性肺病 (COPD) 患者的主要心血管和呼吸系统不良事件 (MACRE). 该工具使用电子健康记录来准确评估COPD护理中的10年风险.
科学领域:
- 心脏病学 心脏病学
- 肺部病理学 肺部病理学
- 数据科学在医学中的数据科学
背景情况:
- 心血管疾病在慢性阻塞性肺病 (COPD) 患者中很常见.
- 现有的心血管风险模型没有针对COPD患者进行优化.
- 需要改进对这一群体的风险评估.
研究的目的:
- 开发一种预测模型,用于COPD患者10年内发生重大心血管和呼吸系统不良事件 (MACRE) 的风险.
- 创建一个工具,以改善COPD患者的风险分层.
主要方法:
- 在全国范围内使用英国初级保健电子健康记录,用于40岁以上的COPD患者.
- 开发了一种具有最小绝对收缩的多变量考克斯回归模型和用于变量选择的选择运算符.
- 使用单独的数据集验证了模型,评估了5年和10年预测时间的性能.
主要成果:
- 该模型来自122,077名患者,包括61个预测变量.
- 它表现出良好的至优秀的差别 (AUROC 0.78在5年,0.82在10年) 和令人满意的校准.
- MACRE发生在50.2%的验证组中,平均随访时间为10.5年.
结论:
- 一个电子健康记录衍生的模型准确地预测了COPD患者的MACRE.
- 该模型显示了高分辨率和对中长期预测的令人满意的校准.
- 需要进一步的研究来评估其临床实用性,用于试验招生和患者管理.
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