Singapore Eye Research Institute and Singapore National Eye Center, Singapore; Duke-NUS Graduate Medical School, Singapore.
Bioinformatics Institute, A*STAR (Agency for Science, Technology and Research), Singapore.
Ophthalmology. 2013 Dec;120(12):2525-2531. doi: 10.1016/j.ophtha.2013.05.028. Epub 2013 Aug 2.
To identify subgroups of primary angle-closure suspects (PACS) based on anterior segment optical coherence tomography (AS-OCT) and biometric parameters.
Cross-sectional study.
We evaluated 243 PACS subjects in the primary group and 165 subjects in the validation group.
Participants underwent gonioscopy and AS-OCT (Carl Zeiss Meditec, Dublin, CA). Customized software (Zhongshan Angle Assessment Program, Guangzhou, China) was used to measure AS-OCT parameters. An agglomerative hierarchical clustering method was first used to determine the optimum number of parameters to be included in the determination of subgroups. The best number of subgroups was then determined using Akaike Information Criterion (AIC) and Gaussian Mixture Model (GMM) methods.
Subgroups of PACS.
The mean age of the subjects was 64.8 years, and 65.02% were female. After hierarchical clustering, 1 or 2 parameters from each cluster were chosen to ensure representativeness of the parameters and yet keep a minimum of redundancy. The parameters included were iris area, anterior chamber depth (ACD), anterior chamber width (ACW), and lens vault (LV). With the use of GMM, the optimal number of subgroups as given by AIC was 3. Subgroup 1 was characterized by a large iris area, subgroup 2 was characterized by a large LV and a shallow ACD, and subgroup 3 was characterized by elements of both subgroups 1 and 2. The results were replicated in a second independent group of 165 PACS subjects.
Clustering analysis identified 3 distinct subgroups of PACS subjects based on AS-OCT and biometric parameters. These findings may be relevant for understanding angle-closure pathogenesis and management.
基于眼前节光学相干断层扫描(AS-OCT)和生物测量参数,确定原发性闭角型青光眼疑似患者(PACS)的亚组。
横断面研究。
我们评估了原发性组的 243 名 PACS 受试者和验证组的 165 名受试者。
参与者接受房角镜检查和 AS-OCT(德国卡尔蔡司公司,都柏林,加利福尼亚州)检查。使用定制软件(中山角度评估程序,广州,中国)测量 AS-OCT 参数。首先使用凝聚层次聚类方法确定要包含在亚组确定中的最佳参数数量。然后使用 Akaike 信息准则(AIC)和高斯混合模型(GMM)方法确定最佳亚组数量。
PACS 的亚组。
受试者的平均年龄为 64.8 岁,65.02%为女性。经过层次聚类,每个聚类中选择 1 或 2 个参数,以确保参数的代表性,同时保持最小的冗余。所包括的参数包括虹膜面积、前房深度(ACD)、前房宽度(ACW)和晶状体拱顶(LV)。使用 GMM,根据 AIC 给出的最佳亚组数量为 3。亚组 1 的特征是虹膜面积大,亚组 2 的特征是 LV 大且 ACD 浅,亚组 3 的特征是亚组 1 和 2 的特征都有。在第二个独立的 165 名 PACS 受试者组中复制了这些结果。
聚类分析根据 AS-OCT 和生物测量参数确定了 3 个不同的 PACS 亚组。这些发现可能与理解闭角型青光眼发病机制和管理有关。