针对日本免疫功能低下患者中常见的传染病,基于索赔的诊断的有效性
Ryota Hase1,2, Daisuke Suzuki3,4, Cynthia de Luise5
1Department of Infectious Diseases, Kameda Medical Center, 929 Higashi-cho, Kamogawa, 296-8602, Chiba, Japan.
日本的索赔数据算法在识别疹菌 (HZ) 和 Mycobacterium 结核病 (MTB) 感染方面显示中度至高精度. 验证研究证实了HZ和MTB的实用性,对于非结核性真菌菌感染 (NTM) 和Pneumocystis jirovecii肺炎 (PJP) 的性能较低.
科学领域:
- 医疗信息学 医疗信息学
- 流行病学 流行病学
- 传染性疾病 传染性疾病
背景情况:
- 索赔数据越来越多地用于疾病监测和研究.
- 验证从索赔数据中识别特定疾病的算法对于准确性至关重要.
- 这项研究的重点是日本的疹 (HZ),Mycobacterium结核病 (MTB),非结核菌感染 (NTM) 和Pneumocystis jirovecii肺炎 (PJP).
研究的目的:
- 验证基于日本索赔的疾病识别算法,用于HZ,MTB,NTM和PJP.
- 评估这些算法的积极预测值 (PPV) 对于流行和事件情况.
主要方法:
- 一项多中心,横截面,回顾性研究 (VALIDATE-J) 使用来自日本两家医院的索赔数据和医疗记录进行.
- 开发了算法来识别在2012-2016年期间处理的HZ,MTB,NTM和PJP病例.
- 诊断确认使用了三个黄金标准定义,并为流行病和事故病例计算了PPV.
主要成果:
- 对于疹病毒 (HZ) 的PPV在67.4-70.9%,对于Mycobacterium结核病 (MTB) 的PPV在67.0-90.0%之间,根据定义和病例类型.
- 非结核性真菌菌感染 (NTM) 的正预测值为18.3-63.4%,而Pneumocystis jirovecii肺炎 (PJP) 的正预测值为20.0-45.0%.
- 将治疗信息添加到算法中,改善了HZ的PPV,以及在较小程度上,对于流行的NTM病例.
结论:
- 基于索赔的算法证明了在日本识别疹 (HZ) 和Mycobacterium结核病 (MTB) 的中等到高的积极预测值.
- 这些算法在识别非结核性真菌菌感染 (NTM) 和Pneumocystis jirovecii肺炎 (PJP) 中表现较差.
- 算法改进,比如将处理数据纳入,可以在特定条件下提高准确性.
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