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dc.contributor.authorMaz Jamilah, Masnan
dc.contributor.authorKarniza, Khalid
dc.contributor.authorSafwati, Ibrahim
dc.contributor.authorSyafawati, Ab Saad
dc.contributorFaculty of Applied & Human Sciences, Institute of Engineering Mathematics, Universiti Malaysia Perlis (UniMAP)en_US
dc.contributorCentre of Excellence for Social Innovation and Sustainability, Universiti Malaysia Perlis (UniMAP)en_US
dc.contributorMinistry of Health Malaysia, Clinical Research Centre, Hospital Tuanku Fauziah (HTF), Perlisen_US
dc.creatorSyafawati, Ab Saad
dc.date.accessioned2023-01-24T13:06:28Z
dc.date.available2023-01-24T13:06:28Z
dc.date.issued2022-12
dc.identifier.citationApplied Mathematics and Computational Intelligence (AMCI), vol.11(1), 2022, pages 164-173en_US
dc.identifier.issn2289-1315 (print)
dc.identifier.issn2289-1323 (online)
dc.identifier.urihttp://dspace.unimap.edu.my:80/xmlui/handle/123456789/77708
dc.descriptionLink to publisher's homepage at https://amci.unimap.edu.my/en_US
dc.description.abstractDiabetic retinopathy is one of the microvascular complications caused by prolonged uncontrolled diabetes. It is believed that diabetic retinopathy correlates with certain predictors and risk factors that might worsen the disease, eventually causing visual loss and blindness among diabetes patients. There are some predictors and risk factors that attribute to the development and progression of diabetic retinopathy, such as the duration of diabetes and HbA1c trends. This study aims to evaluate the predictors and risk factors associated with the development and/or progression of diabetic retinopathy. Retrospective data were collected from a single healthcare facility in the northwest of Peninsular Malaysia. Patients included in this study were those with type 2 diabetes mellitus diagnosed with diabetic retinopathy. The total number of patients involved in this study were 197, where 161 of them were newly diagnosed or with progressive diabetic retinopathy. The characteristics of diabetes patients with complication of diabetic retinopathy were described through descriptive statistics. Characteristics include demographics data such as age, gender, race and clinical data such as HbA1c readings HbA1c, estimated glomerular filtration rate (eGFR), urea and haemoglobin concentration (Hb). The results show that 7 predictors and risk factors are significant to the development and progression of diabetic retinopathy among diabetes patients. By using multinomial logistic regression, this study offers better understanding of the significant predictors and risk factors related to diabetic retinopathy.en_US
dc.language.isoenen_US
dc.publisherInstitute of Engineering Mathematics, Universiti Malaysia Perlisen_US
dc.subject.otherDiabetic retinopathyen_US
dc.subject.otherPredictorsen_US
dc.subject.otherMultinomial logistic regressionen_US
dc.titleEvaluation of predictors for the development and progression of diabetic retinopathy among diabetes mellitus type 2 patientsen_US
dc.typeArticleen_US
dc.identifier.urlhttps://amci.unimap.edu.my/
dc.contributor.urlsyafawatisaad@unimap.edu.myen_US


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