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Detection of primary angleclosure suspect with different mechanisms of angle closure using multivariate prediction models
Author(s) -
Zhang Ye,
Dong Zhe,
Zhang Qing,
Li Lei,
Thomas Ravi,
Li Si Zhen,
He Ming Guang,
Wang Ning Li
Publication year - 2021
Publication title -
acta ophthalmologica
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.534
H-Index - 87
eISSN - 1755-3768
pISSN - 1755-375X
DOI - 10.1111/aos.14634
Subject(s) - gonioscopy , receiver operating characteristic , multivariate statistics , logistic regression , closure (psychology) , statistics , iris (biosensor) , artificial intelligence , ophthalmology , medicine , computer science , optometry , mathematics , glaucoma , economics , biometrics , market economy
Purpose We had found that a multivariate prediction model used for the detection of primary angle‐closure suspects (PACS) by combining multiple static and dynamic anterior segment optical coherence tomography (ASOCT) parameters had an area under the receiver operating characteristic curve (AUC) of 0.844. We undertook this study to evaluate this method in screening of PACS with different dominant mechanisms of angle closure (AC). Methods The right eyes of subjects aged ≥40 years who participated in the 5‐year follow‐up of the Handan Eye Study and had undergone gonioscopy and ASOCT examinations under light and dark conditions were included. All ASOCT images were analysed by the Zhongshan Angle Assessment Program. The dominant AC mechanism in each eye was determined to be pupillary block (PB), plateau iris configuration (PIC) or thick peripheral iris roll (TPIR). Backward logistic regression (LR) was used for inclusion of variables in the prediction models. LR, Naïve Bayes’ classification (NBC) and neural network (NN) were evaluated and compared using the AUC. Results Data from 796 subjects (413 PACS and 383 normal eyes) were analysed. The AUCs of LR, NBC and NN in the PB group were 0.920, 0.918 and 0.917. The AUCs of LR, NBC and NN in the PIC group were 0.715, 0.708 and 0.707. The AUCs of LR, NBC and NN in TPIR group were 0.867, 0.833 and 0.886. Conclusions Prediction models showed the best performance for detection of PACS with PB mechanism for AC and have potential for screening of PACS.