Assessment of Diabetic Retinopaty Risk Factors in Type II Diabetes Mellitus
Abstract
Diabetic retinopathy (DR) is a leading microvascular complication of diabetes mellitus (DM), primarily caused by chronic hyperglycemia. It leads to vascular occlusion, increased vascular permeability, retinal abnormalities, and detachment, ultimately resulting in visual impairment and blindness. Implementing Evidence Based Nursing Practice using diagnostic tests to determine the sensitivity and specificity of the assessment instrument for Diabetic Retinopathy Risk Factors in Type II DM Diagnostic tests are descriptive observational studies with a cross-sectional study design. This application is classified as descriptive observational because only observations are made without any intervention (treatment). The test is carried out with ROC where to see the sensitivity and specificity of the application instrument. The results of the analysis showed that the sensitivity of the application of the assessment of diabetic retinopathy risk factors using the ROC Curve Test was 100%. Meanwhile, the specificity of the instrument for the application of the assessment of diabetic retinopathy risk factors was 81.3%. The application of diabetic retinopathy risk factor assessment can be used to assess the risk of diabetic retinopathy because it has good sensitivity (%) and specificity (%) values. However, when applying the diabetic retinopathy risk factor assessment, only the risk value of diabetic retinopathy was obtained where the application patient did not experience complaints and decreased visual acuity.
References
Alswaina, N. (2024). Association Between HbA1c Levels and the Severity of Diabetic Retinopathy. 16(12), 1–8. https://doi.org/10.7759/cureus.76395
Bantounou, M. A., Nahar, T. A. K., Plascevic, J., Kumar, N., Nath, M., Myint, P. K., & Philip, S. (2024). Drug Exposure As a Predictor in Diabetic Retinopathy Risk Prediction Models—A Systematic Review and Meta-Analysis. American Journal of Ophthalmology, 268, 29–44. https://doi.org/10.1016/j.ajo.2024.07.012
Cherchi, S., Gigante, A., Spanu, M. A., Contini, P., Meloni, G., Fois, M. A., Pistis, D., Pilosu, R. M., Lai, A., Ruiu, S., Campesi, I., & Tonolo, G. (2020). Sex-Gender Differences in Diabetic Retinopathy. Diabetology. https://doi.org/10.3390/diabetology1010001
Hana, N., & Hakim, A. W. (2023). Retinopati Diabetik Proliferatif : Faktor Risiko dan Penatalaksanaan. Pandu Husada, 4.
Jeong, I. S., & Kang, C. M. (2022). Prevalence and Risk Factors of Diabetic Retinopathy in Diabetes People using Korean National Health and Nutrition Examination Survey VII. Korean Academy of Community Health Nursing, 33, 408–417. https://doi.org/https://doi.org/10.12799/jkachn.2022.33.4.408
Long, M., Wang, C., & Liu, D. (2017). Glycated hemoglobin A1C and vitamin D and their association with diabetic retinopathy severity. Nature Publishing Group, https://do.
Lopez, J., Gange, W. S., Lung, K., Xu, B. Y., Seabury, S. A., & Toy, B. C. (2022). Incidence of Proliferative Diabetic Retinopathy and Other Neovascular Sequelae at 5 Years Following Diagnosis of Type 2 Diabetes. Diabetes Care 2021;44:2518–2526. Diabetes Care, 45(3), e61–e62. https://doi.org/10.2337/dci21-0057
Ma, Y., Wang, H., Jiang, J., Han, C., Lu, C., Zeng, S., Wang, Y., Zheng, Z., Peng, Y., & Ding, X. (2022). Prevalence of and risk factors for diabetic retinopathy in residents with different types of abnormal glucose metabolism with or without hypertension: A suburban community-based cross-sectional study. Frontiers in Endocrinology, 13(August), 1–12. https://doi.org/10.3389/fendo.2022.966619
Mehraban Far, P., Tai, F., Ogunbameru, A., Pechlivanoglou, P., Sander, B., Wong, D. T., Brent, M. H., & Felfeli, T. (2022). Diagnostic accuracy of teleretinal screening for detection of diabetic retinopathy and age-related macular degeneration: a systematic review and meta-analysis. In BMJ open ophthalmology (Vol. 7, Issue 1, p. e000915). https://doi.org/10.1136/bmjophth-2021-000915
PERDAMI. (2018). Pedoman Nasional Pelayanan Kedokteran Retinopati Diabetika (C. E. Center (ed.)).
Qian, J., Haq, Z., Yang, D., & Stewart, J. M. (2022). Male sex increases the risk of diabetic retinopathy in an urban safety-net hospital population without impacting the relationship between axial length and retinopathy. Scientific Reports, 12(1), 1–5. https://doi.org/10.1038/s41598-022-13593-4
Shukla, U. V, Koushik, ;, & Affiliations, T. (2024). Diabetic Retinopathy. https://pubmed.ncbi.nlm.nih.gov/32809640/
Teo, Z. L., Tham, Y. C., Yu, M., C., M. L., Rim, T. H., Cheung, N., & Cheng, C. Y. (2021). Global prevalence of diabetic retinopathy and projection of burden through 2045: systematic review and meta-analysis. Elsevier, 111, 1580–1591.
Trevethan, R. (2017). Sensitivity, Specificity, and Predictive Values: Foundations, Pliabilities, and Pitfalls in Research and Practice. Frontiers in Public Health, 5(November), 1–7. https://doi.org/10.3389/fpubh.2017.00307
Wondmeneh, T. G., & Mohammed, J. A. (2024). Prevalence of diabetic retinopathy and its associated risk factors among adults in Ethiopia: a systematic review and meta-analysis. Scientific Reports, 14(1), 1–17. https://doi.org/10.1038/s41598-024-78596-9
Yang, Z., Tan, T. E., Shao, Y., Wong, T. Y., & Li, X. (2022). Classification of diabetic retinopathy: Past, present and future. Frontiers in Endocrinology, 13(December), 1–18. https://doi.org/10.3389/fendo.2022.1079217
Yusran, M. (2017). Retinopati Diabetik: Tinjauan Kasus Diagnosis dan Tatalaksana. Kedokteran Universitas Lampung, 1, 578–582.
Zhu, C., Zhu, J., Wang, L., Xiong, S., Zou, Y., Huang, J., Xie, H., Zhang, W., Wu, H., & Liu, Y. (2023). Development and validation of a risk prediction model for diabetic retinopathy in type 2 diabetic patients. Scientific Reports, 13(1), 1–8. https://doi.org/10.1038/s41598-023-31463-5
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