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      Determinants of Intraocular Pressure and Time to Blindness for Glaucoma Patients at Felege Hiwot Referral Hospital, Bahir Bar, Ethiopia: A Comparison of Separate and Joint Models

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          Abstract

          Background:

          Due to the substantial increase in the number of glaucoma cases within the next several decades, glaucoma is a significant public health issue. The main objective of this study was to investigate the determinant factors of intraocular pressure and time to blindness of glaucoma patients under treatment at Felege Hiwot Referral Hospital, Bahir Dar, Ethiopia.

          Methods:

          A retrospective study design was conducted on 328 randomly selected glaucoma patients using simple random sampling based on the identification number of patients in an ophthalmology clinic at the hospital under the follow-up period from January 2014 to December 2018. A linear mixed effects model for intraocular pressure data, a semi-parametric survival model for the time-to-blindness data and joint modeling of the 2 responses were used for data analysis. However, the primary outcome was survival time of glaucoma patients.

          Results:

          The comparison of joint and separate models revealed that joint model was more adequate and efficient inferences because of its smaller standard errors in parameter estimations. This was also approved using AIC, BIC, and based on a significant likelihood ratio test as well. The estimated association parameter (α) in the joint model was .0160 and statistically significant ( P-value = .0349). This indicated that there was strong evidence for positive association between the effects of intraocular pressure and the risk of blindness. The result indicated that the higher value of intraocular pressure was associated with the higher risk of blindness. Age, hypertension, type of medication, cup-disk ratio significantly affects both average intraocular pressure and survival time of glaucoma patients ( P-value < .05).

          Conclusion:

          The predictors; age, hypertension, type of medication, and cup-disk ratio were significantly associated with the 2 responses of glaucoma patients. Health professionals give more attention to patients who have blood pressure and cup-disk ratio greater than 0.7 during the follow-up time to reduce the risk of blindness of glaucoma patients.

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          Most cited references25

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          Contact lens sensors in ocular diagnostics.

          Contact lenses as a minimally invasive platform for diagnostics and drug delivery have emerged in recent years. Contact lens sensors have been developed for analyzing the glucose composition of tears as a surrogate for blood glucose monitoring and for the diagnosis of glaucoma by measuring intraocular pressure. However, the eye offers a wider diagnostic potential as a sensing site and therefore contact lens sensors have the potential to improve the diagnosis and treatment of many diseases and conditions. With advances in polymer synthesis, electronics and micro/nanofabrication, contact lens sensors can be produced to quantify the concentrations of many biomolecules in ocular fluids. Non- or minimally invasive contact lens sensors can be used directly in a clinical or point-of-care setting to monitor a disease state continuously. This article reviews the state-of-the-art in contact lens sensor fabrication, their detection, wireless powering, and readout mechanisms, and integration with mobile devices and smartphones. High-volume manufacturing considerations of contact lenses are also covered and a case study of an intraocular pressure contact lens sensor is provided as an example of a successful product. This Review further analyzes the contact lens market and the FDA regulatory requirements for commercialization of contact lens sensors.
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            Basic concepts and methods for joint models of longitudinal and survival data.

            Joint models for longitudinal and survival data are particularly relevant to many cancer clinical trials and observational studies in which longitudinal biomarkers (eg, circulating tumor cells, immune response to a vaccine, and quality-of-life measurements) may be highly associated with time to event, such as relapse-free survival or overall survival. In this article, we give an introductory overview on joint modeling and present a general discussion of a broad range of issues that arise in the design and analysis of clinical trials using joint models. To demonstrate our points throughout, we present an analysis from the Eastern Cooperative Oncology Group trial E1193, as well as examine some operating characteristics of joint models through simulation studies.
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              Is Open Access

              Glaucoma: the retina and beyond

              Over 60 million people worldwide are diagnosed with glaucomatous optic neuropathy, which is estimated to be responsible for 8.4 million cases of irreversible blindness globally. Glaucoma is associated with characteristic damage to the optic nerve and patterns of visual field loss which principally involves the loss of retinal ganglion cells (RGCs). At present, intraocular pressure (IOP) presents the only modifiable risk factor for glaucoma, although RGC and vision loss can continue in patients despite well-controlled IOP. This, coupled with the present inability to diagnose glaucoma until relatively late in the disease process, has led to intense investigations towards the development of novel techniques for the early diagnosis of disease. This review outlines our current understanding of the potential mechanisms underlying RGC and axonal loss in glaucoma. Similarities between glaucoma and other neurodegenerative diseases of the central nervous system are drawn before an overview of recent developments in techniques for monitoring RGC health is provided, including recent progress towards the development of RGC specific contrast agents. The review concludes by discussing techniques to assess glaucomatous changes in the brain using MRI and the clinical relevance of glaucomatous-associated changes in the visual centres of the brain.
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                Author and article information

                Journal
                Cancer Inform
                Cancer Inform
                CIX
                spcix
                Cancer Informatics
                SAGE Publications (Sage UK: London, England )
                1176-9351
                18 September 2021
                2021
                : 20
                : 11769351211045975
                Affiliations
                [1 ]Department of Statistics, Faculty of Natural and Computational Science, Debre Tabor University, Debre Tabor, Ethiopia
                [2 ]Department of Statistics, College of Science, Bahir Dar University, Bahir Dar, Ethiopia
                Author notes
                [*]Mitiku Wale Muluneh, Department of Statistics, Faculty of Natural and Computational Science, Debre Tabor University, P.O.Box 272, Debre Tabor, Ethiopia. Email: mitikuwale@ 123456gmail.com
                Author information
                https://orcid.org/0000-0002-2413-8026
                Article
                10.1177_11769351211045975
                10.1177/11769351211045975
                8450691
                a18c8c8a-9cc0-4e0f-aeb4-1dde78ae8324
                © The Author(s) 2021

                This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License ( https://creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access page ( https://us.sagepub.com/en-us/nam/open-access-at-sage).

                History
                : 17 May 2021
                : 21 August 2021
                Categories
                Original Research
                Custom metadata
                January-December 2021
                ts1

                Oncology & Radiotherapy
                intraocular pressure,time to blindness,linear mixed model,joint model,cox proportional hazard model

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