试点一个自动查询和评分系统,以促进APDS患者从卫生系统的识别
Amy M FitzPatrick1, Aaron T Chin2, Sharon Nirenberg3
1Precision AQ, Bethesda, MD, United States.
Frontiers in immunology
|February 5, 2025
概括
识别患有激活PI3Kδ综合征 (APDS) 的患者是一项挑战. 使用风险评分的新电子健康记录查询方法成功识别了98%的已知APDS患者,改善了先天免疫错误的早期诊断.
科学领域:
- 免疫学 免疫学 免疫学
- 遗传学 遗传学 是一个
- 医疗信息学 医疗信息学
背景情况:
- 激活PI3Kδ综合征 (APDS) 是一种罕见的先天性免疫错误 (IEI),通常是晚期诊断的,延迟了关键的治疗.
- 早期识别APDS和其他IEI对于及时干预和改善患者结果至关重要.
- 目前用于APDS等罕见疾病的诊断方法可能是漫长而复杂的.
研究的目的:
- 开发和验证一种用于加快使用电子健康记录 (EHR) 数据识别APDS患者的新方法.
- 为了证明将不同的临床症状汇总成风险评分来识别患有罕见疾病的患者的可行性.
- 改善APDS和其他免疫系统的先天性错误的诊断时间表.
主要方法:
- 开发了一个结构化查询语言 (SQL) 脚本,结合了与APDS相关的文献验证的临床概念,并映射到ICD-10-CM代码.
- 在美国七个主要医疗中心的EHR系统中执行了SQL查询,覆盖了大约1700万个患者记录.
- 计算每个人的"APDS分数",分层他们的APDS风险,并与已知的APDS患者数据进行比较.
主要成果:
- 该查询成功识别了98% (45分之46) 的已知APDS患者,以及其他复杂疾病患者.
- 患有该综合征的患者的APDS评分中位数为9 (IQR = 5.75),范围为1-25.
- 灵敏度分析表明最佳的APDS分数截止值为7,达到0.70.70的灵敏度.
结论:
- 疾病特定的EHR查询提供了一种简单的方法,以提高整个罕见疾病谱的患者识别.
- 这种方法对像APDS这样的疾病特别有价值,因为有针对性,特定途径的治疗方法可用.
- 实施这些数据驱动的诊断工具可以显著减少罕见免疫缺陷的诊断延迟.
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