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Classification of primary angle closure spectrum with hierarchical cluster analysis

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Listed:
  • Sasan Moghimi
  • Ali Torkashvand
  • Massood Mohammadi
  • Mehdi Yaseri
  • Luke J Saunders
  • Shan C Lin
  • Robert N Weinreb

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

Suggested Citation

  • Sasan Moghimi & Ali Torkashvand & Massood Mohammadi & Mehdi Yaseri & Luke J Saunders & Shan C Lin & Robert N Weinreb, 2018. "Classification of primary angle closure spectrum with hierarchical cluster analysis," PLOS ONE, Public Library of Science, vol. 13(7), pages 1-14, July.
  • Handle: RePEc:plo:pone00:0199157
    DOI: 10.1371/journal.pone.0199157
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