Classification Criteria For Multiple Evanescent White Dot Syndrome.
Classification Criteria For Multiple Evanescent White Dot Syndrome.
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DOI：
10.1016/j.ajo.2021.03.050
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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：
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作者：
Standardization of Uveitis Nomenclature (SUN) Working Group
确定多发性消失白点综合征 (MEWDS) 的分类标准。 MEWDS 和其他 8 种后葡萄膜炎病例的机器学习。后葡萄膜炎病例被收集在信息学设计的初步数据库中，并使用正式共识技术，由在诊断上达成绝大多数一致的病例构建最终数据库。案例被分为训练集和验证集。在训练集上使用多项逻辑回归的机器学习来确定一组简约的标准，以最大限度地减少传染性后部/全葡萄球菌之间的错误分类率。在验证集上评估所得标准。通过机器学习评估了 1,68 例后葡萄膜炎病例，其中包括 51 例 MEWDS。 MEWDS 的关键标准包括：1）多灶性灰白色脉络膜视网膜斑点，具有中心凹颗粒度； 2）荧光素血管造影（“花环样”高荧光病变）和/或光学相干断层扫描（从视网膜色素上皮穿过椭球区延伸到视网膜外核层的高反射病变）的特征成像； 3) 没有或轻微的前房和玻璃体炎症。后葡萄膜的总体准确度在训练集中为 93.9%，在验证集中为 98.0%（95% 置信区间 94.3、99.3）。 MEWDS 的错误分类率在训练集中为 7%，在验证集中为 0%。 MEWDS 的标准错误分类率较低，并且似乎在临床和转化研究中表现良好。使用正式的方法来制定分类标准，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，制定了多发性消失白点综合征的分类标准。关键标准包括具有中心凹颗粒度的多灶性脉络膜视网膜灰斑、无轻度前房和玻璃体炎症，以及特征性荧光素血管造影（“花环样”超荧光）和/或光学相干断层扫描（病变从视网膜色素上皮延伸到视网膜）。由此产生的分类标准具有较低的错误分类率。
To determine classification criteria for multiple evanescent white dot syndrome (MEWDS). Machine learning of cases with MEWDS and 8 other posterior uveitides. Cases of posterior uveitides were collected in an informatics-designed preliminary database, and a final database was constructed of cases achieving supermajority agreement on 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 infectious posterior/panuveitides. The resulting criteria were evaluated on the validation set. One thousand sixty-eight cases of posterior uveitides, including 51 cases of MEWDS, were evaluated by machine learning. Key criteria for MEWDS included: 1) multifocal gray white chorioretinal spots with foveal granularity; 2) characteristic imaging on fluorescein angiography (“wreath-like” hyperfluorescent lesions) and/or optical coherence tomography (hyper-reflective lesions extending from retinal pigment epithelium through ellipsoid zone into the retinal outer nuclear layer); and 3) absent to mild anterior chamber and vitreous inflammation. Overall accuracy for posterior uveitides was 93.9% in the training set and 98.0% (95% confidence interval 94.3, 99.3) in the validation set. The misclassification rates for MEWDS were 7% in the training set and 0% in the validation set. The criteria for MEWDS 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 multiple evanescent white dot syndrome were developed. Key criteria included multifocal chorioretinal gray spots with foveal granularity, absent to mild anterior chamber and vitreous inflammation, and either a characteristic fluorescein angiogram (“wreath-like” hyperfluorescence) and/or optical coherence tomogram (lesions extending from retinal pigment epithelium into retina). The resulting classification criteria had a low misclassification rate.
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影响因子：
--
作者：
dell'Omo, Roberto;Pavesio, Carlos E
通讯作者：
Pavesio, Carlos E
影响因子：
1
作者：
Joseph, Anthony;Rahimy, Ehsan;Sarraf, David
通讯作者：
Sarraf, David
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
影响因子：
4.2
作者：
AABERG, TM;CAMPO, RV;JOFFE, L
通讯作者：
JOFFE, L
影响因子：
3.3
作者：
Pellegrini, Marco;Veronese, Chiara;Ciardella, Antonio P.
通讯作者：
Ciardella, Antonio P.