在电子健康记录和基因组数据查后,家族高胆固醇血症遗传和表型诊断的收益率
Samuel S Gidding1, H Lester Kirchner2, Andrew Brangan1
1Department of Genomic Health Geisinger Danville PA USA.
Journal of the American Heart Association
|June 29, 2023
概括
两种查算法在70%的患者中确定了家族性高胆固醇血症 (FH) 遗传变异. 然而,由于缺少电子健康记录数据,确认表型FH很困难.
科学领域:
- 遗传学 遗传学 是一个
- 心脏病学 心脏病学
- 医疗信息学 医疗信息学
背景情况:
- 针对家族性高胆固醇血症 (FH) 的电子健康记录 (EHR) 的数据挖掘是具有挑战性的,因为表型和基因组数据碎片化.
- 之前的研究缺乏用于验证FH查工具的全面数据集.
研究的目的:
- 评估两个FH查算法 (Mayo Clinic和FIND FH) 在一个大型社区卫生倡议队列中的诊断产量.
- 评估使用EHR数据识别FH患者的可行性.
主要方法:
- 使用了盖辛格MyCode社区卫生倡议队列 (n=130,257).
- 应用梅奥诊所和FIND FH查算法来识别潜在的FH病例.
- 用荷兰脂质临床网络得分来确定表型FH的变异阴性参与者的审查图表.
主要成果:
- 在排除后,分析了59729名参与者的最终队列.
- 结合的算法确定了197个具有致病性或可能致病性FH变体的个体 (70%的净收益率).
- 现型诊断确认受到身体发现和家族病史的不完整EHR数据的限制.
结论:
- 两种已建立的FH查算法有效地确定了具有FH遗传变异的大量个体.
- 在电子健康记录中缺乏详细的表型数据,这阻碍了FH的完整诊断.
- 未来的努力应集中在将全面的临床数据整合到电子健康记录中,以改善FH检测.
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