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Classification of Primary Angle Closure Spectrum With Hierarchical Cluster Analysis Publisher Pubmed



Moghimi S1, 3 ; Torkashvand A3 ; Mohammadi M3 ; Yaseri M4 ; Saunders LJ1 ; Lin SC5 ; Weinreb RN1
Authors
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Authors Affiliations
  1. 1. Hamilton Glaucoma Center, Department of Ophthalmology, Shiley Eye Institute, University of California, San Diego, CA, United States
  2. 2. Department of Ophthalmology, Shiley Eye Institute, University of California, San Diego, CA, United States
  3. 3. Tehran University Research Center, Tehran University of Medical Science, Tehran, Iran
  4. 4. Department of Epidemiology and Biostatistics, Tehran University of Medical Sciences, Tehran, Iran
  5. 5. Koret Vision Center, University of California, San Francisco Medical School, San Francisco, CA, United States

Source: PLoS ONE Published:2018


Abstract

Purpose To classify subjects with primary angle closure into clusters based on features from anterior segment optical coherence tomography (ASOCT) imaging and to explore how these clusters correspond to disease subtypes, including primary angle closure suspect (PACS), primary angle closure glaucoma(PACG), acute primary angle closure (APAC) and fellow eyes of APAC and reveal the factors that become more predominant in each subtype of angle closure. Method A cross-sectional study of 248 eyes of 198 subjects(88 PACS eyes, 53 PACG eyes, 54 APAC eyes and 53 fellow eyes of APAC) that underwent complete examination including gonioscopy, A-scan biometry, and ASOCT. An agglomerative hierarchical clustering method was used to classify eyes based on ASOCT parameters. Results Statistical clustering analysis produced three clusters among which the anterior segment parameters were significantly different. Cluster 1(43 eyes) had the smallest anterior chamber depth(ACD) and area, as well as the greatest lens vault (p<0.001 for all). Cluster 2(113 eyes) had the thickest iris at 2000 microns(p = 0.048), and largest iris area(p<0.001), and the deepest ACD (p<0.001). Cluster 3(92 eyes) was characterized by elements of both clusters 1 and 2 and a higher iris curvature(p<0.001). There was a statistically significant difference in the distribution of clusters among subtypes of angle closure eyes(p<0.001). Although the patterns of clusters were similar in PACS and PACG eyes, with the majority of the eyes classified into cluster 2(55%, and 62%, respectively), the highest proportion of APAC and fellow eyes were assigned to clusters 1(44%) and 3 (51%), respectively. Conclusion Hierarchical cluster analysis identified three clusters with different features. Predominant anatomical components are different among subtypes of primary angle closure. © 2018 Moghimi et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.