five

Accuracy of self-reported history of autoimmune disease: A pilot study

收藏
NIAID Data Ecosystem2026-03-11 收录
下载链接:
https://figshare.com/articles/dataset/Accuracy_of_self-reported_history_of_autoimmune_disease_A_pilot_study/8199770
下载链接
链接失效反馈
官方服务:
资源简介:
Research associating the increased prevalence of familial autoimmunity with neuropsychiatric disorders is reliant upon the ascertainment of history of autoimmune diseases from relatives. To characterize the accuracy of self-report, we compared self-reported diagnoses of 18 autoimmune diseases using an online self-report questionnaire to the electronic medical record (EMR) diagnoses in 1,013 adult (age 18–70 years) patients of a primary care clinic. For the 11 diseases meeting our threshold observed prevalence, we estimated sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) for self-reported diagnoses under the assumption that EMR-based diagnoses were accurate. Six diseases out of 11 had either sensitivity or PPV below 50%, with the lowest PPV for dermatological and endocrinological diseases. Common errors included incorrectly self-reporting type 2 diabetes mellitus (DM), when type 1 DM was indicated by the EMR, and reporting rheumatoid arthritis when osteoarthritis was indicated by the EMR. Results suggest that ascertainment of familial autoimmunity through self-report contributes to inconsistencies and inaccuracies in studies of autoimmune disease history and that future studies would benefit from incorporating EMR review and biological measures.
创建时间:
2019-05-29
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作