Longitudinal analysis of intraocular pressure and its associated risk factors of glaucoma patients using Bayesian linear mixed model: A data from Felege Hiwot Hospital, Ethiopia

• Published in: Scientific African Vol. 16; p. e01160
• Main Authors: Belay, Denekew Bitew, Derseh, Minilik, Damtie, Destaw, Shiferaw, Yegnanew A., Adigeh, Senait Cherie
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01-07-2022; Elsevier
• Subjects: Bayesian analysis; Glaucoma; Intraocular pressure; Longitudinal data analysis; Glaucoma; POAG; MCMC; FHCSH; LMEM; AIC; IOP; Bayesian analysis; BIC; Intraocular pressure; Longitudinal data analysis
• ISSN: 2468-2276; 2468-2276
• DOI: 10.1016/j.sciaf.2022.e01160

Glaucoma is a neurodegenerative condition that affects the eye and is associated with increased intraocular pressure. Intraocular pressure is the fluid pressure inside the eye and its disturbance often is implicated in the development of pathologies such as glaucoma, uveitis and retinal detachment. The aim of the present study was to identify factors that affect the longitudinal intraocular pressure of glaucoma patients attending the ophthalmology clinic at Felege Hiwot Comprehensive Specialized Hospital, Bahir Dar, Ethiopia, using a Bayesian linear mixed model analysis.
In a longitudinal study with data obtained from glaucoma patients admitted to Felege Hiwot Hospital, the measurement of intraocular pressure change was applied. The study subjects were enrolled in the period between 1st January 2016 and 1st January 2020 and a total of 328 patients were selected for the study. Data were explored using descriptive statistics and individual and mean profile plots throughout study time. A Bayesian linear mixed model for the longitudinal data was used along with their model comparison, model estimation, model diagnosis and missing data analysis.
The analysis included 328 individuals with 9 for maximum and 2 for minimum repeated measurements of intraocular pressure change, including the baseline. From the Bayesian linear mixed model variables, observation time, age, place of residence, gender, the cup-disk ratio of patients, type of medication (like Pilocarpin, Timolol with Pilocarpin, Timolol with Diamox with Pilocarpin), and blood pressure of the glaucoma patients significantly affected the intraocular pressure changes over time. However, the type of medication (Diamox and Timolol with Diamox) did not affect the intraocular pressure changes over time.
Based on the Bayesian linear mixed model analysis, we found that the predictor variables of age, blood pressure, family history, residence, gender, diabetic disease, treatment duration, stages of glaucoma, type of medication and cup-disk ratio significantly affected the average intraocular pressure and had a positive association with the responses of intraocular pressure of glaucoma patients. Furthermore, the type of medication was statistically significant and negatively associated with the responses to intraocular pressure.
We recommend the health professionals to give more attention to the type of medication especially Timolol with Pilocarpin, Timolol with Diamox and Timolol with Diamox with Pilocarpine. And taking the combination with the other type of medication minimizes the risk of blindness and intraocular pressure.