Keck School of Medicine of the University of California, Los Angeles, CA, USA.
Department of Population and Public Health Science, Keck School of Medicine at the University of Southern California, Los Angeles, CA, USA.
Transl Vis Sci Technol. 2023 Sep 1;12(9):4. doi: 10.1167/tvst.12.9.4.
The purpose of this study was to investigate the classification of angle closure eyes based on hierarchical cluster analysis of ocular biometrics measured in the dark and light using anterior segment optical coherence tomography (AS-OCT).
Participants of the Chinese American Eye Study received complete eye examinations to identify primary angle closure suspects (PACS) and primary angle closure without/with glaucoma (PAC/G). AS-OCT was performed in the dark and light. Biometric parameters describing the angle, iris, lens, and anterior chamber were analyzed. Hierarchical clustering was performed using Ward's method. Post hoc logistic regression models were developed to identify biometric predictors of angle closure staging.
Analysis of 159 eyes with PACS (N = 120) or PAC/G (N = 39) produced 2 clusters in the dark and light. In both analyses, cluster 1 (N = 132 in the dark and N = 126 in the light) was characterized by smaller angle opening distance (AOD)750 and trabecular iris space area (TISA)750, greater iris curvature (IC), and greater lens vault (LV; P < 0.001) than cluster 2. The proportion of PAC/PACG to PACS eyes was significantly higher in cluster 1 than 2 in the light (36:90 and 3:30, respectively; P = 0.02), but not the dark (36:96 and 3:24, respectively; P = 0.08). On multivariable regression analyses, smaller TISA750 (odds ratio [OR] = 0.84 per 0.01 mm2) and AOD750 (OR = 0.93 per 0.01 mm) in the light and smaller TISA750 (OR = 0.86 per 0.01 mm2) in the dark conferred higher risk of PAC/G (P ≤ 0.02).
Unsupervised cluster analysis of ocular biometrics can classify angle closure eyes by severity. Static biometrics measured in the light and dark are both predictive of PAC/G.
Clustering of biometrics measured in the light could provide an alternative source of information to risk-stratify angle closure eyes for more severe disease.
本研究旨在通过眼前节光学相干断层扫描（AS-OCT）在暗光和亮光下测量的眼部生物测量指标进行层次聚类分析，对闭角型青光眼（angle closure glaucoma，ACG）眼进行分类。
中美眼研究（Chinese American Eye Study）的参与者接受了全面的眼科检查，以确定原发性闭角型青光眼疑似患者（primary angle closure suspect，PACS）和原发性闭角型青光眼伴/不伴青光眼（primary angle closure with/without glaucoma，PAC/G）。在暗光和亮光下进行 AS-OCT 检查。分析描述角度、虹膜、晶状体和前房的生物测量参数。采用 Ward 法进行层次聚类。建立事后逻辑回归模型，以确定预测闭角型青光眼分期的生物测量指标。
对 159 只 PACS 眼（N=120）或 PAC/G 眼（N=39）进行分析，在暗光和亮光下均产生 2 个聚类。在这两种分析中，聚类 1（暗光下 N=132，亮光下 N=126）的特征是暗光下的小角度开口距离（angle opening distance，AOD）750 和小梁虹膜空间面积（trabecular iris space area，TISA）750 较小，虹膜曲率（iris curvature，IC）较大，晶状体拱顶（lens vault，LV）较大（P＜0.001）。与聚类 2 相比，在亮光下 PAC/PACG 眼与 PACS 眼的比例显著更高（分别为 36:90 和 3:30，P=0.02），但在暗光下差异无统计学意义（分别为 36:96 和 3:24，P=0.08）。多变量回归分析显示，在亮光下 TISA750 较小（每 0.01mm2 比值比[odds ratio，OR]为 0.84）和 AOD750 较小（每 0.01mm 比值比[OR]为 0.93），以及在暗光下 TISA750 较小（每 0.01mm2 比值比[OR]为 0.86），均与 PAC/G 风险较高相关（P≤0.02）。
眼部生物测量的无监督聚类分析可以根据严重程度对闭角型青光眼眼进行分类。在暗光和亮光下测量的静态生物测量值均可预测 PAC/G。
Zhiyuan Wu, MD, PhD
