Applying Logistic Regression to Predict Diabetic Nephropathy Based on Some Clinical and Paraclinical Characteristics of Type 2 Diabetic Patients
Authors: Van Nga Vu , Thi Kim Anh Le , Thi My Dung Dinh , Thi Binh Minh Nguyen , Thi Diem Hong Le , Thi Thom Vu 
Published: July 2021

Today, the incidence of type 2 diabetes mellitus is increasing rapidly on global. This disease is shown with many complications that significantly affect public health. One of them is kidney complications, which have a high incidence among diabetic patients in Vietnam (25.6-33.1%). Age, history of hypertension, and dyslipidemia are considered to be the main risk factors for diabetic nephropathy. Thus, early detection of these factors for kidney damage is significant for diagnosing, monitoring, treatment, and prognosis of diabetic patients. Our descriptive, cross-sectional study conducting on 120 diabetic patients at E Hospital has observed that blood cholesterol levels, HbA1c levels were independently related to eGFR decline below 60 mL/min/1.73m2. From those data, an equation to predict the risk of diabetic kidney disease was estimated as p =  with k =
Keyword: Type 2 diabetes, Diabetic nephropathy, Risk factor
Today, the incidence of type 2 diabetes mellitus is increasing rapidly on global. This disease is shown with many complications that significantly affect public health. One of them is kidney complications, which have a high incidence among diabetic patients in Vietnam (25.6-33.1%). Age, history of hypertension, and dyslipidemia are considered to be the main risk factors for diabetic nephropathy. Thus, early detection of these factors for kidney damage is significant for diagnosing, monitoring, treatment, and prognosis of diabetic patients. Our descriptive, cross-sectional study conducting on 120 diabetic patients at E Hospital has observed that blood cholesterol levels, HbA1c levels were independently related to eGFR decline below 60 mL/min/1.73m2. From those data, an equation to predict the risk of diabetic kidney disease was estimated as p =  with k =
Keyword
Type 2 diabetes, Diabetic nephropathy, Risk factor.
References
[1] N. H. Cho, J. Kirigia, J. C. Mnanya, K. Ogurstova, L. Guraiguata, W. Rathmann, G. Roglic, N. Forouhi, R. Dajani, A. Esteghmati, E. Boyko, L. Hambleton, O. L. M. Neto, P. A. Montoya, S. Joshi, J. Chan, J. Shaw, T.A. Samuels, M. Pavkov, A. Reja, IDF Diabetes Atlas Eight Edition, International Diabete Federation, England, 2017.[2] N. T. Khue, Diabetes – General Endocrinology, Ho Chi Minh Publisher, Ho Chi Minh city, 2003 (in Vietnamese). [3] H. H. Kiem, Clinical Nephrology, Medical Publishing House, Hanoi, 2010 (in Vietnamese). [4] T. H. Quang, Practice Diabetes - Endocrine Disease, Medical Publishing House Hanoi, Hanoi, 2010 (in Vietnamese). [5] D. T. M. Hao, T. T. A. Thu, Diabetic Kidney Disease: Attention Problems, Vietnam Journal of Diabetes and Endocrinology, Vol. 38, 2020, pp. 12-17 (in Vietnamese), https://doi.org/10.47122/vjde.2020.38.2. [6] K. Tziomalos, A. Vasilios G, Diabetic Nephropathy: New Risk Factors and Improvements in Diagnosis, The Review of Diabetic Studies: RDS, Vol. 12, No. 1-2, 2015, pp. 110-118, https://doi.org/10.1900/RDS.2015.12.110.[7] American Diabetes Association, 2. Classification and Diagnosis of Diabetes: Standards of Medical Care in Diabetes-2020, Journal Diabetes Care, Vol. 43, No. 1, 2020, pp. S14, https://doi.org/10.2337/dc20-S002.[8] A. S. Levey, J. Coresh, E. Balk, A. T. Kausz, A. Levin, M. W. Steffes, R. J. Hogg, R. D. Perrone, J. Lau, G. Eknoyan, National Kidney Foundation Practice Guidelines for Chronic Kidney Disease: Evaluation, Classification, and Stratification, Ann Intern Med, Vol. 139, 2003, pp. 137-147, https://doi.org/10.7326/0003-4819-139-2-200307150-00013.[9] D. S. Freedman, M. Horlick, G. S. Berenson, A Comparison of The Slaughter Skinfold-thickness Equations and BMI in Predicting Body Fatness and Cardiovascular Disease Risk Factor Levels in Children, The American Journal of Clinical Nutrition, Vol. 98, No. 6, 2013, pp. 1417-1424, https://doi.org/10.3945/ajcn.113.065961.[10] National Heart, Lung and Blood Institutes, National Cholesterol Education Program: ATP III Guidelines at-a-glance Quick Desk Reference, https://www.nhlbi.nih.gov/files/docs/guidelines/atglance.pdf, (accessed on: 5th April 2021).[11] K. Eckardt, B. Kasiske, D. Wheeler, K. Uhlig, D. Miskulin, A. Earley, S. Haynes, J. Lamont, KDIGO 2012 Clinical Practice Guideline for the Evaluation and Management of Chronic Kidney Disease: Definition and Classification of CKD, Kidney International Supplements, Vol. 3, 2013, pp. 5-14, https://doi.org/10.1038/kisup.2012.77.[12] I. H. Boer, M. L. Caramori, J. C. N. Chan, H. J. L. Heerspink, C. Hurst, K. Khunti, A. Liew, E. D. Michos, S. D. navaneethan, P. Rossing, W. A. Olowu, T. Sadusky, N. Tandon, K. R. Tuttle, C. Wanner, K. G. Wilkens, S. Zoungas, KDIGO 2020 Clinical Practice Guideline for Diabetes Management in Chronic Kidney Disease, Kidney international, Vol. 98, No. 4S, 2020, pp. S1-S115, http://dx.doi.org/10.1016/j.kint.2020.06.019.[13] B. T. T. Huong, N. T. Giang, Values of Cystatin C in Early Diagnosis of Renal Disease in Patients with Typ 2 Diabetes in Thai Nguyen National Hospital, Vietnam Medical Journal, Vol. 498, No. 2, 2021, pp. 13-17 (in Vietnamese).[14] L. X. Truong, N. D. Tai, T. Q. P. Linh, T. T. Nhung, The Prevalence of The Positive Microalbumin Urine in The Type 2 Diabetic Patients at District 2 Hospital, Y Hoc TP. Ho Chi Minh, Vol. 22, No. 2, 2018, pp. 139-143 (in Vietnamese).[15] S. Yi, S. Park, Y. Lee, H Park, B. Balkau, J. Yi, Association Between Fasting Glucose and All-cause Mortality According to Sex and Age: A Prospective Cohort Study, Scientific Reports, Vol. 7, No. 1, 2017, pp. 1-9, https://doi.org/10.1038/s41598-017-08498-6.[16] R. Gupta, M. Sharma, N. K. Goyal, P. S. Lodha, K. K. Sharma, Gender Differences in 7 Years Trends in Cholesterol Lipoproteins and Lipids in India: Insights From A Hospital Database, Indian Journal of Endocrinology Metabolism, Vol. 20, No. 2, 2016, pp. 211-8, https://doi.org/10.4103/2230-8210.176362.[17] X. Zhang, Z. Meng, X. Li, M. Liu, X. Ren, M. Zhu, Q. He, Q Zhang, K. Song, Q. Jia, C. Zhang, X Wang, X. Liu, The Association Between Total Bilirubin and Serum Triglyceride in Both Sexes in Chinese, Lipids In Health and Disease, Vol. 17, No. 1, 2017, pp. 1-8, https://doi.org/10.1186/s12944-018-0857-7.[18] S. Palazhy, V. Viswanathan, Lipid Abnormalities in Type 2 Diabetes Mellitus Patients with Overt Nephropathy, Diabetes Metabolism Journal, Vol. 41, No. 2, 2017, pp. 128-134, https://doi.org/ 10.4093/dmj.2017.41.2.128.[19] R. I. Papacocea, D. Timofte, M. Tanasescu, A. Balcangiu stroescu, D. G. Balan, A. Tulin, O. Stiru, I. A. Vacaroiu, A. Mihai, C. C. Popa, C. Cosconel, M. Enyedi, D. Miricescu, L. Raducu, D. Ionescu, Kidney Aging Process and The Management of The Elderly Patient with Renal Impairment, Experimental and Therapeutic Medicine, Vol. 21, 2021, pp. 266, https://doi.org/10.3892/etm.2021.9697.[20] R. D. Lindeman, Overview: Renal Physiology and Pathophysiology of Aging, Am J Kidney Dis, Vol. 16, 1990, pp. 275–282, https://doi.org/10.1016/s0272-6386(12)80002-3.[21] G. Zoppini, G. Targher, M. Chonchol, V. Ortalda, C. Negri, V. Stoicio, E. Bonora, Predictors of Estimated GFR Decline in Patients With Type 2 Diabetes and Preserved Kidney Function, Clinical Journal of the American Society of Nephrology, Vol. 7, No. 3, 2012, pp. 401-408, https://doi.org/10.2215/CJN.07650711.[22] R. Trevisan, A. R. Dodesini, G. Lepore, Lipids and Renal Disease, Journal of the American Society of Nephrology, Vol. 17, No. 2-4, 2006, pp. S145-S147. https://doi.org/10.1681/ASN.2005121320.[23] V. T. Samuel, G. I. Shulman, Mechanisms for Insulin Resistance: Common Threads and Missing Links, Cell, Vol. 148, No. 5, 2012, pp. 852-871, https://doi.org/10.1016/j.cell.2012.02.017.[24] W. Patricia, D. Gloria Michelle, F. Alessia, Systemic and Renal Lipids in Kidney Disease Development and Progression, American Journal of Physiology-Renal Physiology, Vol. 310, No. 6, 2016, pp. F433-F445, https://doi.org/ 10.1152/ajprenal.00375.2015.[25] F. M. Sacks, M. P. Hermans, P. Fioretto, P. Valensi, T. Davis, E. Horton, C. Wanner, K. A. Rubeaan, I. Barzon, L. Bishop, E. Bonora, P. Bunnag, L. Chuang, C. Deerochanawong, R. Goldenberg, B. Harshfiled, C. Hernandez, S. H. Botein, H. Itoh, W. Jia, Y. Jiang, T. Kadowaki, N. Laranjo, L. Leiter, T. Miwwa, M. Odawara, K. Ohashi, A. Ohno, C. Pan, J. Pan, J. P. Botet, Z. Reiner, C. M. Rotella, R. Simo, M. Tanaka, E. T. Reiner, D. T. Barima, G. Zoppini, V. J. Carey, Association between Plasma Triglycerides and High-density Lipoprotein Cholesterol and Microvascular Kidney Disease and Retinopathy in Type 2 Diabetes Mellitus: A Global Case–control Study In 13 Countries, Circulation. Vol. 129, No. 9, 2014, pp. 999-1008, https://doi.org/10.1161/CIRCULATIONAHA.113.002529.[26] Y. Wang, X. Qiu, L. Lv, C. Wang, Z. Ye, S. Li, Q. Liu, T. Lou, X. Liu, Correlation Between Serum Lipid Levels and Measured Glomerular Filtration Rate In Chinese Patients With Chronic Kidney Disease, PLoS One, Vol. 11, No. 10, 2016, pp. e0163767, https://doi.org/10.1371/journal.pone.0163767.[27] N. J. Radcliffe, J. Seah, M. Clarke, R. J. Maclsaac, G. Jerrums, E. I. Ekinci, Clinical Predictive Factors in Diabetic Kidney Disease Progression, Journal of Diabetes Investigation, Vol. 8, No. 1, 2017, pp. 6-18, https://doi.org/10.1111/jdi.12533.[28] D. D. Miao, E. C. Pan, Q. Zhang, Z. M. Sun, Y. Qin, M. Wu, Development and Validation of A Model for Predicting Diabetic Nephropathy in Chinese People, Biomedical and Environmental Sciences, Vol. 30, No. 2, 2017, pp. 106-112, https://doi.org/10.3967/bes2017.014.[29] R. G. Nelson, M. E. Grams, S. H. Ballew, Y. Sang, F. Azizi, S. J. Chadban, L. Chaker, S. C. Dunning, C. Fox, Y. Hirakawa, K. Iseki, J. Ix, T. H. Jafar, A. Kottgen, D. M. J. Naimark, T. Ohjubo, G. J. Prescott, C. M. Bebholz, C. Sabanayagam, T. Sairenchi, B. Schottker, Y. Shibagaki, M. Tonelli, L. Zhang, R. T. Gansevoort, K. Matsushita, M. Woodward, J. Coresh, V. Shalev, Development of Risk Prediction Equations For Incident Chronic Kidney Disease, Jama, Vol. 322, No. 21, 2019, pp. 2104-2114, https://doi.org/10.1001/jama.2019.17379.