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J Res Health Sci. 2022;22(2): e00547.
doi: 10.34172/jrhs.2022.82
PMID: 36511259
PMCID: PMC9818039
Scopus ID: 85134797997
  Abstract View: 191
  PDF Download: 81
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Original Article

Bivariate Survival Copula Analysis of Glaucoma Patients during Blindness: Glaucoma Cases at Alert Hospital in Addis Ababa City of Ethiopia

Firomsa Shewa Gari, Gurmessa Nugussu Gelcho*
*Corresponding Author: Email: gurmessang3.88@gmail.com

Abstract

Background: Glaucoma is a worldwide problem that causes vision loss and even blindness, with a prevalence rate ranging from 1.9% to 15%. In Ethiopia, glaucoma is the fifth cause of blindness. This study aimed to explore the dependence between blindness of the right and the left eyes of glaucoma patients and assess the effects of the covariates under the dependence structure.

Study Design: A retrospective cohort study.

Methods: The study population included the glaucoma patients at Alert hospital from January 1, 2018, to December 30, 2021. The copula model was used to estimate the time to the blindness of the right and the left eyes of the glaucoma patients by specifying the dependence between the event times.

Results: Out of 537 glaucoma patients, 224 (41.71%) became blind at least in one eye during the follow-up period. The results of the Clayton copula model revealed that factors, such as age, residence, diabetes mellitus, stage of glaucoma, and hypertension are considered the most prognostic factors for blindness in glaucoma patients. The findings also revealed that there was a strong dependence between the time to the blindness of the right and the left eyes in the glaucoma patients (Ï„ = 0.43).

Conclusion: Based on the obtained results, high age, urban residence, hypertension, diabetes mellitus, and higher stage of glaucoma were factors associated with time to the blindness in the glaucoma patients. There was also a dependence between the right and the left eyes of the glaucoma patients. The results revealed that the Clayton Archimedean copula model was the best statistical model for accurate description of glaucoma patients’ datasets.

 

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Submitted: 17 Feb 2022
Revision: 12 Jul 2022
ePublished: 11 May 2022
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