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Evaluation of the Diagnostic Performance of Swept-Source Anterior Segment Optical Coherence Tomography in Primary Angle Closure Disease

To evaluate the diagnostic performance of swept-source anterior segment optical coherence tomography (SS-OCT) in differentiating eyes with primary angle closure disease (PACD) from eyes of control subjects, as well as eyes with PAC and PAC glaucoma (PACG) from eyes with PAC suspect (PACS) disease. M...

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Published in:American journal of ophthalmology 2022-01, Vol.233, p.68-77
Main Authors: Ma, Ping, Wu, Yanyan, Oatts, Julius, Patlidanon, Jutima, Yu, Yinxi, Ying, Gui-Shuang, Kline, Brad, Tun, Tin A., He, Mingguang, Aung, Tin, Li, Shuning, Yang, Yangfan, Han, Ying
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container_title American journal of ophthalmology
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creator Ma, Ping
Wu, Yanyan
Oatts, Julius
Patlidanon, Jutima
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He, Mingguang
Aung, Tin
Li, Shuning
Yang, Yangfan
Han, Ying
description To evaluate the diagnostic performance of swept-source anterior segment optical coherence tomography (SS-OCT) in differentiating eyes with primary angle closure disease (PACD) from eyes of control subjects, as well as eyes with PAC and PAC glaucoma (PACG) from eyes with PAC suspect (PACS) disease. Multicenter cross-sectional study. Chinese patients were classified into control, PACS, and PAC/PACG groups. The area under the receiving operating characteristic curve (AUC) from logistic regression models was used to evaluate discriminating ability. Sensitivity and specificity were calculated, and performance of the models was validated using an independent dataset. A total of 2928 SS-OCT images from 366 eyes of 260 patients were recruited to develop diagnostic models. The validation dataset included 1176 SS-OCT images from 147 eyes of 143 patients. For distinguishing PACD from control eyes, average anterior chamber depth had the highest AUC (0.94). With a cutoff of 2.2 mm for average anterior chamber depth, the sensitivity and specificity were 90.2% and 85.2% in the training set. For distinguishing PAC/PACG from PACS, a multivariate model had an AUC of 0.83, with sensitivity and specificity of 82.0% and 62.8% in the training set. The validation set confirmed the findings. SS-OCT of the anterior segment showed excellent diagnostic performance distinguishing PACD from normal eyes and moderate diagnostic ability distinguishing eyes with PAC/PACG from eyes with PACS. ACD alone may provide a simple and effective way to diagnose PACD from control subjects. As ACD can be obtained using other more available modalities, this has implications for the early diagnosis of PACD.
doi_str_mv 10.1016/j.ajo.2021.06.033
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Multicenter cross-sectional study. Chinese patients were classified into control, PACS, and PAC/PACG groups. The area under the receiving operating characteristic curve (AUC) from logistic regression models was used to evaluate discriminating ability. Sensitivity and specificity were calculated, and performance of the models was validated using an independent dataset. A total of 2928 SS-OCT images from 366 eyes of 260 patients were recruited to develop diagnostic models. The validation dataset included 1176 SS-OCT images from 147 eyes of 143 patients. For distinguishing PACD from control eyes, average anterior chamber depth had the highest AUC (0.94). With a cutoff of 2.2 mm for average anterior chamber depth, the sensitivity and specificity were 90.2% and 85.2% in the training set. For distinguishing PAC/PACG from PACS, a multivariate model had an AUC of 0.83, with sensitivity and specificity of 82.0% and 62.8% in the training set. The validation set confirmed the findings. 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subjects Anterior Eye Segment - diagnostic imaging
Cataracts
Cross-Sectional Studies
Datasets
Disease
Generalized linear models
Glaucoma
Glaucoma, Angle-Closure - diagnosis
Gonioscopy
Humans
Intraocular Pressure
Iris
Medical diagnosis
Optic nerve
Optics
Software
Tomography
Tomography, Optical Coherence
title Evaluation of the Diagnostic Performance of Swept-Source Anterior Segment Optical Coherence Tomography in Primary Angle Closure Disease
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