Prognostic evaluation model of diabetic nephropathy patients

医学 糖尿病肾病 内科学 糖尿病 肾病 肾功能 肌酐 重症监护医学 泌尿科 蛋白尿 肾脏疾病 内分泌学
作者
Xiao Tu,Na Luo,Yiqi Lv,Bijuan Wang,Yayu Li
出处
期刊:Annals of palliative medicine [AME Publishing Company]
卷期号:10 (6): 6867-6872 被引量:1
标识
DOI:10.21037/apm-21-1454
摘要

BACKGROUND Diabetic nephropathy (DN) affects about 40% of diabetes mellitus (DM) patients and is the leading cause of chronic kidney disease (CKD) and end-stage renal disease (ESRD) globally, especially in advanced countries. We aimed to explore the risk factors affecting the prognosis of DN, and to establish a prognostic evaluation line map. METHODS We analyzed 471 cases of DN from December 2011 to April 2020, and extracted the basic clinical factors, including gender, age, and history of diabetes. Analysis included that of associations between DN and hypertension, creatinine (CR), body mass index (BMI), and fundus lesions. Statistical analysis was performed using R software and the related R package. The above clinical factors were analyzed by both single- and multiple-factor Cox regression. The participants were divided into two groups, including a high risk and a low risk group. A Kaplan-Meier curve was drawn for survival analysis of the high and low risk groups, and the log-rank method was used for statistical testing. A receiver operating characteristic (ROC) curve was drawn with the area under the curve (AUC) calculated to evaluate the predictive effectiveness of the line map. RESULTS This study initially included 471 patients; however, 33 patients (7.0%) were lost to follow-up due to inaccessibility. A total of 93 cases (21.2%) died during the follow-up. The 3-year and 5-year renal survival rates were 74.5% and 22.6%, respectively. Single factor Cox analysis showed that the course of diabetes, fundus lesions, BMI, and grade of hypertension were risk factors for renal survival, and had adverse effects on prognosis (P<0.05). Multivariate Cox regression analysis showed that BMI and grade of hypertension were independent risk factors for survival of DKD, and had adverse effects on prognosis (P<0.05). Survival analysis showed that low risk group participants had significantly better survival rates than high risk group participants (P<0.05). The AUC was 0.742, which meant that the line map could accurately predict the survival rate of DN patients. CONCLUSIONS The influence of risk factors on prognosis can be accurately evaluated by line diagram which can provide a basis for clinical decision making.

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