开发和验证一个多机构的电子青少年异常性关节炎现型
Alysha Taxter1, Edward Oberle1, Amy Lynn Rakestraw2
1Department of Pediatrics, Nationwide Children's Hospital, Columbus, OH, USA.
Seminars in arthritis and rheumatism
|February 21, 2026
概括
开发一个可计算的表型算法,在大型数据集中准确地识别青少年形性关节炎 (JIA) 患者. 这种经过验证的方法提高了JIA在多个机构的研究准确性.
科学领域:
- 类风湿病学 类风湿病学
- 数据科学数据科学数据科学
- 临床信息学 临床信息学
背景情况:
- 在电子健康记录 (EHR) 和索赔数据中识别青少年异常性关节炎 (JIA) 患者是复杂的.
- 由于临床异质性,现有的方法缺乏精度.
- 为了准确的队列鉴定,需要一个强大的,可计算的表型.
研究的目的:
- 开发和验证可计算的表型算法,用于识别JIA患者.
- 确保算法的可移植性和在多个机构之间一致的性能.
- 在大规模的回顾性研究中提高JIA患者识别的准确性.
主要方法:
- 利用了来自三个地点的多机构数据.
- 包括年龄在20岁以下的患有与JIA相关的ICD代码的受试者,但不包括特定的自身免疫疾病.
- 通过手动图表审查和计算的正预测值 (PPV) 验证了诊断.
主要成果:
- 确定了8093个潜在的JIA主题.
- 获得了0.95的PPV,表型需要≥4个JIA代码,年龄≤20岁,排除标准,确定了5377名受试者.
- 证明PPV增加,具有更高的JIA代码计数要求.
结论:
- 成功开发并验证了一个可计算的,便携式的JIA表型算法.
- 该算法在多个机构中显示出一致的性能.
- 这种方法在协作研究中促进了准确的JIA患者鉴定,提高了研究可靠性.
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