Evidence map›Paper›PMID 37672252›Full record

ArticleTranslational vision science & technology2023

Classification of Angle Closure Severity by Hierarchical Cluster Analysis of Ocular Biometrics in the Dark and Light.

Austin Cho, Juan Pablo Lewinger, Anmol A Pardeshi, Galo Apolo Aroca, Mina Torres, Monisha Nongpiur, Xuejuan Jiang, Roberta McKean-Cowdin, Rohit Varma, Benjamin Y Xu

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In one paragraph

Article in Translational vision science & technology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Austin ChoKeck School of Medicine of the University of California, Los Angeles, CA, USA.
Juan Pablo LewingerKeck School of Medicine of the University of California, Los Angeles, CA, USA.
Anmol A PardeshiRoski Eye Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.
Galo Apolo ArocaRoski Eye Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.
Mina TorresSouthern California Eye Institute, CHA Hollywood Presbyterian Medical Center, Los Angeles, CA, USA.
Monisha NongpiurSingapore Eye Research Institute and Singapore National Eye Center, Singapore, Republic of Singapore.
Xuejuan JiangRoski Eye Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.
Roberta McKean-CowdinKeck School of Medicine of the University of California, Los Angeles, CA, USA.
Rohit VarmaSouthern California Eye Institute, CHA Hollywood Presbyterian Medical Center, Los Angeles, CA, USA.
Benjamin Y XuRoski Eye Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.

Funding

Chinese American Eye StudyU10EY017337 · NEI · UNIVERSITY OF SOUTHERN CALIFORNIA · PI VARMA, ROHIT · 2009 to 2013
$10.2M
Development and Validation of Quantitative Anterior Segment OCT-based Methods to Evaluate Patients with Primary Angle Closure DiseaseK23EY029763 · NEI · UNIVERSITY OF SOUTHERN CALIFORNIA · PI XU, BENJAMIN Y. · 2019 to 2023
$1.1M
NEI NIH HHS K23 EY029763NEI NIH HHS U10 EY017337
6 · The paper itself

Abstract

Purpose: 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). Methods: 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. Results: 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). Conclusions: 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. Translational Relevance: Clustering of biometrics measured in the light could provide an alternative source of information to risk-stratify angle closure eyes for more severe disease.

Indexed as

Anterior ChamberGlaucomaBiometryCluster AnalysisHumansTomography, Optical Coherence

Identifiers

PMID37672252
PMCPMC10484011

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.