Classification Criteria for Cytomegalovirus Anterior Uveitis.
Classification Criteria for Cytomegalovirus Anterior Uveitis.
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DOI：
10.1016/j.ajo.2021.03.060
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发表时间：
2021-08
影响因子：
4.2
通讯作者：
Standardization of Uveitis Nomenclature (SUN) Working Group
中科院分区：
文献类型：
--
作者：
Standardization of Uveitis Nomenclature (SUN) Working Group
确定巨细胞病毒（CMV）前葡萄膜炎的分类标准机器学习CMV前葡萄膜炎和其他8种前葡萄膜炎病例。前葡萄膜炎的病例收集在信息学设计的初步数据库中，并使用正式的共识技术，构建了一个最终的病例库，其中的病例在诊断上达到了绝大多数的一致。将病例分为训练集和验证集。在训练集上使用使用多项逻辑回归的机器学习来确定一组最小化前葡萄膜错误分类率的简约标准。在验证集上评价所得标准。1083例前葡萄膜炎，包括89例CMV前葡萄膜炎，通过机器学习进行了评估。前葡萄膜炎的总体准确度在训练集中为97.5%，在验证集中为96.7%（95%置信区间92.4，98.6）。CMV前葡萄膜炎的关键标准包括眼房水CMV聚合酶链反应检测阳性的单侧前葡萄膜炎。无临床特征可靠诊断CMV前葡萄膜炎。CMV前葡萄膜炎的错误分类率在训练集中为1.3%，在验证集中为0%。巨细胞病毒前葡萄膜炎的标准有一个低的错误分类率，并表现出足够好的临床和转化研究中使用。使用正式的方法来开发分类标准，包括基于信息学的病例收集，基于共识技术的病例选择和机器学习，开发了巨细胞病毒（CMV）前葡萄膜炎的分类标准。关键标准包括单侧前葡萄膜炎伴眼房水CMV聚合酶链反应检测阳性。由此产生的标准有一个低的错误分类率。
To determine classification criteria for cytomegalovirus (CMV) anterior uveitis Machine learning of cases with CMV anterior uveitis and 8 other anterior uveitides. Cases of anterior uveitides were collected in an informatics-designed preliminary database, and a final datafubase was constructed of cases achieving supermajority agreement on the diagnosis, using formal consensus techniques. Cases were split into a training set and a validation set. Machine learning using multinomial logistic regression was used on the training set to determine a parsimonious set of criteria that minimized the misclassification rate among the anterior uveitides. The resulting criteria were evaluated on the validation set. One thousand eighty-three of cases of anterior uveitides, including 89 cases of CMV anterior uveitis, were evaluated by machine learning. The overall accuracy for anterior uveitides was 97.5% in the training set and 96.7% in the validation set (95% confidence interval 92.4, 98.6). Key criteria for CMV anterior uveitis included unilateral anterior uveitis with a positive aqueous humor polymerase chain reaction assay for CMV. No clinical features reliably diagnosed CMV anterior uveitis. The misclassification rates for CMV anterior uveitis were 1.3 % in the training set and 0% in the validation set, respectively. The criteria for CMV anterior uveitis had a low misclassification rate and appeared to perform sufficiently well for use in clinical and translational research. Using a formalized approach to developing classification criteria, including informatics-based case collection, consensus-technique-based case selection, and machine learning, classification criteria for cytomegalovirus (CMV) anterior uveitis were developed. Key criteria included unilateral anterior uveitis with positive aqueous humor polymerase chain reaction assay for CMV. The resulting criteria had a low misclassification rate.
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影响因子：
4.2
作者：
Standardization of Uveitis Nomenclature (SUN) Working Group
通讯作者：
Standardization of Uveitis Nomenclature (SUN) Working Group
影响因子：
1.7
作者：
Trusko B;Thorne J;Jabs D;Belfort R;Dick A;Gangaputra S;Nussenblatt R;Okada A;Rosenbaum J;Standardization of Uveitis Nomenclature (SUN) Project
通讯作者：
Standardization of Uveitis Nomenclature (SUN) Project
DOI：
10.1007/s00417-009-1239-7
发表时间：
2010-04-01
影响因子：
2.7
作者：
Ruokonen, Peter C.;Metzner, Sylvia;Pleyer, Uwe
通讯作者：
Pleyer, Uwe
影响因子：
4.1
作者：
Chee, S-P;Jap, A.
通讯作者：
Jap, A.
影响因子：
8.1
作者：
Gonzales, John A.;Hinterwirth, Armin;Thuy Doan
通讯作者：
Thuy Doan