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      Development and Validation of a Model That Predicts the Risk of Diabetic Nephropathy in Type 2 Diabetes Mellitus Patients: A Cross-Sectional Study

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          Abstract

          Purpose

          To develop a nomogram model that predicts the risk of diabetic nephropathy (DN) incidence in type 2 diabetes mellitus (T2DM) patients.

          Methods

          We collect information from electronic medical record systems. The data were split into a training set (n=521) containing 73.8% of patients and a validation set (n=185) holding the remaining 26.2% of patients based on the date of data collection. Stepwise and multivariable logistic regression analyses were used to screen out DN risk factors. A predictive model including selected risk factors was developed by logistic regression analysis. The results of binary logistic regression are presented through forest plots and nomogram. Lastly, the c-index, calibration plots, and receiver operating characteristic (ROC) curves were used to assess the accuracy of the nomogram in internal and external validation. The clinical benefit of the model was evaluated by decision curve analysis.

          Results

          Predictors included serum creatinine (Scr), hypertension, glycosylated hemoglobin A1c (HbA1c), blood urea nitrogen (BUN), body mass index (BMI), triglycerides (TG), and Diabetic peripheral neuropathy (DPN). Harrell’s C-indexes were 0.773 (95% CI:0.726–0.821) and 0.758 (95% CI:0.679–0.837) in the training and validation sets, respectively. Decision curve analysis (DCA) demonstrated that the novel nomogram was clinically valuable.

          Conclusion

          Our simple nomogram with seven factors may help clinicians predict the risk of DN incidence in patients with T2DM.

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          Most cited references51

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          Diagnosis and Classification of Diabetes Mellitus

          Vittorio Basevi (2014)
          Article 0 comments Cited 899 times – based on 0 reviews     Review now
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            Global Prevalence of Chronic Kidney Disease – A Systematic Review and Meta-Analysis

            Nathan Hill, Samuel T Fatoba, Jason L. Oke … (2016)
            Chronic kidney disease (CKD) is a global health burden with a high economic cost to health systems and is an independent risk factor for cardiovascular disease (CVD). All stages of CKD are associated with increased risks of cardiovascular morbidity, premature mortality, and/or decreased quality of life. CKD is usually asymptomatic until later stages and accurate prevalence data are lacking. Thus we sought to determine the prevalence of CKD globally, by stage, geographical location, gender and age. A systematic review and meta-analysis of observational studies estimating CKD prevalence in general populations was conducted through literature searches in 8 databases. We assessed pooled data using a random effects model. Of 5,842 potential articles, 100 studies of diverse quality were included, comprising 6,908,440 patients. Global mean(95%CI) CKD prevalence of 5 stages 13·4%(11·7–15·1%), and stages 3–5 was 10·6%(9·2–12·2%). Weighting by study quality did not affect prevalence estimates. CKD prevalence by stage was Stage-1 (eGFR>90+ACR>30): 3·5% (2·8–4·2%); Stage-2 (eGFR 60–89+ACR>30): 3·9% (2·7–5·3%); Stage-3 (eGFR 30–59): 7·6% (6·4–8·9%); Stage-4 = (eGFR 29–15): 0·4% (0·3–0·5%); and Stage-5 (eGFR<15): 0·1% (0·1–0·1%). CKD has a high global prevalence with a consistent estimated global CKD prevalence of between 11 to 13% with the majority stage 3. Future research should evaluate intervention strategies deliverable at scale to delay the progression of CKD and improve CVD outcomes.
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              Mechanisms of diabetic complications.

              Josephine Forbes, Mark E. Cooper (2013)
              It is increasingly apparent that not only is a cure for the current worldwide diabetes epidemic required, but also for its major complications, affecting both small and large blood vessels. These complications occur in the majority of individuals with both type 1 and type 2 diabetes. Among the most prevalent microvascular complications are kidney disease, blindness, and amputations, with current therapies only slowing disease progression. Impaired kidney function, exhibited as a reduced glomerular filtration rate, is also a major risk factor for macrovascular complications, such as heart attacks and strokes. There have been a large number of new therapies tested in clinical trials for diabetic complications, with, in general, rather disappointing results. Indeed, it remains to be fully defined as to which pathways in diabetic complications are essentially protective rather than pathological, in terms of their effects on the underlying disease process. Furthermore, seemingly independent pathways are also showing significant interactions with each other to exacerbate pathology. Interestingly, some of these pathways may not only play key roles in complications but also in the development of diabetes per se. This review aims to comprehensively discuss the well validated, as well as putative mechanisms involved in the development of diabetic complications. In addition, new fields of research, which warrant further investigation as potential therapeutic targets of the future, will be highlighted.
              Article 0 comments Cited 492 times – based on 0 reviews     Review now
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                Author and article information

                Journal
                Journal ID (nlm-ta): Int J Gen Med
                Journal ID (iso-abbrev): Int J Gen Med
                Journal ID (publisher-id): ijgm
                Title: International Journal of General Medicine
                Publisher: Dove
                ISSN (Electronic): 1178-7074
                Publication date (Electronic): 20 May 2022
                Publication date Collection: 2022
                Volume: 15
                Pages: 5089-5101
                Affiliations
                [1 ]State Key Laboratory of Pathogenesis, Prevention and Treatment of High Incidence Diseases in Central Asia; Department of Endocrinology, The First Affiliated Hospital of Xinjiang Medical University , Urumqi, 830017, People’s Republic of China
                Author notes
                Correspondence: Sheng Jiang, Email xjjiangsheng@126.com
                [*]

                These authors contributed equally to this work

                Article
                Publisher ID: 363474
                DOI: 10.2147/IJGM.S363474
                PMC ID: 9130557
                PubMed ID: 35645579
                SO-VID: cdddcf22-080d-4833-8855-61a59206b82c
                Copyright © © 2022 Yang and Jiang.
                License:

                This work is published and licensed by Dove Medical Press Limited. The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License ( http://creativecommons.org/licenses/by-nc/3.0/). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. For permission for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms ( https://www.dovepress.com/terms.php).

                History
                Date received : 21 February 2022
                Date accepted : 12 May 2022
                Page count
                Figures: 7, Tables: 3, References: 52, Pages: 13
                Categories
                Subject: Original Research

                ScienceOpen disciplines: Medicine
                Keywords: type 2 diabetes mellitus,diabetic nephropathy,nomogram,risk factors
                Data availability:
                ScienceOpen disciplines: Medicine
                Keywords: type 2 diabetes mellitus, diabetic nephropathy, nomogram, risk factors

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