遗传性心脏病的自动表型化,用于动态患者聚合和结果报告
Shuhei Toba1,2,3, Taylor M Smith1,2, Francesca Sperotto1,2
1Department of Cardiology, Boston Children's Hospital, Boston, MA 02115, United States.
JAMIA open
|October 3, 2025
概括
这项研究开发了一种准确而有效的方法,使用诊断和手术代码来确定先天性心脏缺陷表型. 这种方法有助于研究,质量改善和对先天性心脏病患者的临床决策.
科学领域:
- 心脏病学 心脏病学
- 医疗信息学 医疗信息学
- 计算生物学 计算生物学
背景情况:
- 准确的患者表征对于先天性心脏病 (CHD) 研究和临床护理至关重要.
- 现有的CHD患者表型化方法可能是劳动密集型的,可能缺乏全面的数据集成.
研究的目的:
- 开发和验证一种自动化方法,从现有的诊断和手术代码中计算详细的CHD表型.
- 在大量患者群体中评估这种计算方法的准确性和效率.
主要方法:
- 从1981年至2020年期间,提取了超过161,000名患者的诊断和程序代码.
- 开发了一个计算管道来映射代码,计算父解剖学,并识别子类和共同变异的发现.
- 对500名患者的临床文档验证了算法的准确性.
主要成果:
- 成功地为52%的患有心脏病的患者分配了表型.
- 在算法分配和临床专家判断之间达到了很高的一致性 (96.4%).
- 确定定义上的差异是分歧的主要来源.
结论:
- 从代码中自动计算详细的CHD表型,可实现高精度和高效率.
- 该框架可以支持开发交互结果报告和在心血管疾病护理中的临床决策支持工具.
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