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.
{"title":"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.","authors":"Mitiku Wale Muluneh, Awoke Seyoum Tegegne","doi":"10.1177/11769351211045975","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>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.</p><p><strong>Methods: </strong>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.</p><p><strong>Results: </strong>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 (<i>P</i>-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 (<i>P</i>-value < .05).</p><p><strong>Conclusion: </strong>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.</p>","PeriodicalId":35418,"journal":{"name":"Cancer Informatics","volume":"20 ","pages":"11769351211045975"},"PeriodicalIF":2.4000,"publicationDate":"2021-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/89/81/10.1177_11769351211045975.PMC8450691.pdf","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Cancer Informatics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1177/11769351211045975","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2021/1/1 0:00:00","PubModel":"eCollection","JCR":"Q2","JCRName":"MATHEMATICAL & COMPUTATIONAL BIOLOGY","Score":null,"Total":0}
引用次数: 1
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.
期刊介绍：
The field of cancer research relies on advances in many other disciplines, including omics technology, mass spectrometry, radio imaging, computer science, and biostatistics. Cancer Informatics provides open access to peer-reviewed high-quality manuscripts reporting bioinformatics analysis of molecular genetics and/or clinical data pertaining to cancer, emphasizing the use of machine learning, artificial intelligence, statistical algorithms, advanced imaging techniques, data visualization, and high-throughput technologies. As the leading journal dedicated exclusively to the report of the use of computational methods in cancer research and practice, Cancer Informatics leverages methodological improvements in systems biology, genomics, proteomics, metabolomics, and molecular biochemistry into the fields of cancer detection, treatment, classification, risk-prediction, prevention, outcome, and modeling.
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号
