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信息内容作为卫生系统对罕见疾病的查工具
Tudor Groza1,2,3,4,5, Peter N Robinson6, Weng Khong Lim7,8,9,10
1Genetics service, KK Women's and Children's Hospital, Singapore, Singapore. tudorg@bii.a-star.edu.sg.
NPJ digital medicine
|November 25, 2025
概括
本研究介绍了信息内容 (IC) 作为一种使用电子健康记录的罕见疾病 (RD) 新型查工具. 该方法实现了早期 RD 识别的高灵敏度,减少了诊断延迟.
科学领域:
- 医疗信息学 医疗信息学
- 临床数据科学 临床数据科学
- 罕见疾病研究 罕见疾病研究
背景情况:
- 罕见疾病影响全球数百万人,但由于复杂性和稀有性,诊断往往会延迟 (5-6年).
- 电子健康记录 (EHR) 包含大量的临床数据,但有效识别罕见疾病仍然是一个挑战.
- SNOMED CT是新加坡EHR系统中标准的临床术语,提供了一个结构化数据源.
研究的目的:
- 调查来自SNOMED CT术语在EHR中的信息内容 (IC) 的有效性,作为罕见疾病候选者的查工具.
- 评估诊断旅程,并在大量患者队伍中识别潜在的诊断不足的罕见疾病.
- 评估基于IC的罕见疾病查方法的灵敏度和精度.
主要方法:
- 对1,274,199名患者的纵向EHR数据集 (2018-2022) 的分析,其中包括35,898个独特的SNOMED CT术语.
- 使用SNOMED-Orphanet映射识别罕见疾病患者 (n=17,575) 的情况.
- 将信息内容 (IC) 度量和结果驱动的值应用于用于查罕见疾病概况的电子健康记录数据.
主要成果:
- 信息内容 (IC) 有效地区分了罕见疾病患者的个人资料和最初的临床接触.
- 提出的基于IC的选方法实现了大约95%的灵敏度.
- 保持了20%的精度,CI值为8.17,从3次患者接触开始.
- 这项研究确定了71种诊断不足的罕见疾病,其中57种是遗传性疾病.
结论:
- 在EHR中SNOMED CT术语的信息内容 (IC) 分析是罕见疾病的可行和新的查工具.
- 这种方法提供了高灵敏度和可控的精度,可能缩短了诊断旅程.
- 该方法在医院和卫生系统层面对罕见疾病查具有实用性,有助于识别被诊断不足的疾病.
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