Association between serum pancreatic regenerating protien Ⅰα and the risk of chronic kidney disease in patients with diabetes mellitus
Journal Title: Chinese Journal of Clinical Research - Year 2024, Vol 37, Issue 7
Abstract
"<b>Objective</b> To investigate the correlation between serum pancreatic regenerating (Reg) protein Ⅰα and chronic kidney disease (CKD) in diabetic patients, to develop a risk prediction model for diabetes combined with CKD. <b>Methods</b> The clinical data of 500 diabetic patients admitted to the Zhongda Hospital Southeast University from September 2021 to September 2023 were collected for a retrospective study, including general data, medical history, and laboratory indexes［blood routine tests, fasting plasma glucose (FPG), blood urea nitrogen (BUN), serum creatinine (Scr), serum uric acid (UA), and urinary albumin/creatinine ratio (UACR)］. Additionally, the estimated glomerular〖LM〗 filtration rate (eGFR) was calculated. Serum Reg Ⅰα level was measured by enzyme-linked immunosorbent assay, and patients were classified into groups R1 (Reg Ⅰα≤38.60 ng/mL,n=98), R2 (38.60＜Reg Ⅰα≤82.17ng/mL,n=97), R3 (82.17＜Reg Ⅰα≤196.15 ng/mL,n=97) and R4 (Reg Ⅰα＞196.15 ng/mL,n=97), according to quartile levels. Patients were randomly divided into a training set (234 cases) and a validation set (155 cases) using a random number table method in a ratio of 6∶4. Multivariate logistic stepwise regression was utilized to identify model variables and create a nomogram model for predicting the risk of diabetes combined with CKD, and evaluate its efficiency. <b>Results</b> (1) A total of 389 diabetic patients with complete data were included, and 210 (53.98%) patients with CKD. Patients in the R4 group exhibited significantly higher levels of FPG, BUN, Scr, and UA, increased rates of hypertension, coronary heart disease, and CKD, as well as lower levels of red blood cell count, hemoglobin(HGB), and eGFR compared to those in the R1 group (P＜0.05). (2) The indicators in the training and validation sets were found to be well-balanced (P＞0.05). In the training set, the CKD group showed higher levels of Reg Ⅰα, white blood cell count, BUN, Scr, and UA, higher prevalences of hypertension and coronary artery disease, and lower levels of erythrocyte count, HGB, and eGFR compared to the NCKD group (P＜0.05). Binary logistic regression analysis was performed on the basis of collinearity diagnosis,and the results showed that history of hypertension (OR=2.901), Reg Ⅰα＞82.17 ng/mL, decreased HGB (OR=0.965) and increased UA (OR=1.005) were the risk factors of diabetes complicated with CKD (P＜0.05). (3) The areas under the ROC of the training set and validation set were 0.846(95%CI: 0.796-0.896) and 0.920(95%CI： 0.875-0.965), respectively. The calibration curves and the Hosmer-Lemeshow test indicated good agreement of the predicted and observed outcomes (P＞0.05). <b>Conclusion</b> Hypertension, elevated Reg Ⅰα levels, decreased HGB and elevated UA are risk factors for CKD in diabetic patients, and the nomogram model constructed in this study has good predictive power and clinical value."
Authors and Affiliations
WU Xiaodong*, LIU Yijun, HUANG Nan, CHEN Sheng, SHU Zhiyi, HUANG Xi, LI Ling
Keywords
Related Articles
- EP ID EP740722
- DOI 10.13429/j.cnki.cjcr.2024.07.008
- Views 45
- Downloads 1
Effect of resistance exercise on vasculardiastolic function and atherosclerosis in patients with hypertension
Objective To investigate the effect of resistance exercise on self-management ability, vascular diastolic function and atherosclerosis in patients with hypertension. Methods A total of 160 patients with hypertension trea...
Research hotspots analysis of patient reported outcome measurement information system based on bicomb co-word clustering
Objective To summarize the research trends and hotspots of patient reported outcome measurement information system (PROMIS). Methods China National Knowledge Infrastructure (CNKI) and PubMed databases were systematical...
Fully automatic classification of lumbar disc degeneration based on deep learning
<b>Objective</b> To investigate the feasibility of a deep learning model for the fully automatic classification of disc degeneration based on lumbar structures on sagittal T2WI images. <b>Methods</b> The lumbar T2WI im...
Prognostic factors of triple-negative inflammatory breast cancer based on SEER database
"Objective To investigate the clinicopathological features and survival prognostic factors of patients with triple-negative inflammatory breast cancer (TNIBC). Methods The data of patients with TNIBC from 2010 to 2015...
Artificial intelligence advancements in breast cancer ultrasound screening
Ultrasound is the first-line screening method for breast cancer. The application of BI-RADS makes the ultrasound diagnosis of breast diseases relatively consistent, but it is still affected by subjective factors of opera...