Health economic modelling of diabetic kidney disease in patients with type 2 diabetes treated with Canagliflozin in Belgium

2021 ◽  
pp. 1-10
Author(s):  
Winde Jorissen ◽  
Lieven Annemans ◽  
Nicolas Louis ◽  
Andreas Nilsson ◽  
Michael Willis
Diabetes ◽  
2018 ◽  
Vol 67 (Supplement 1) ◽  
pp. 443-P
Author(s):  
YOSHINORI KAKUTANI ◽  
MASANORI EMOTO ◽  
YUKO YAMAZAKI ◽  
KOKA MOTOYAMA ◽  
TOMOAKI MORIOKA ◽  
...  

2019 ◽  
Vol 95 (1) ◽  
pp. 178-187 ◽  
Author(s):  
Guozhi Jiang ◽  
Andrea On Yan Luk ◽  
Claudia Ha Ting Tam ◽  
Fangying Xie ◽  
Bendix Carstensen ◽  
...  

2021 ◽  
Vol 18 (3) ◽  
pp. 17-25
Author(s):  
Stoiţă Marcel ◽  
Popa Amorin Remus

Abstract The presence of albuminuria in patients with type 2 diabetes mellitus is a marker of endothelial dysfunction and also one of the criteria for diagnosing diabetic kidney disease. The present study aimed to identify associations between cardiovascular risk factors and renal albumin excretion in a group of 218 patients with type 2 diabetes mellitus. HbA1c values, systolic blood pressure, diastolic blood pressure were statistically significantly higher in patients with microalbuinuria or macroalbuminuria compared to patients with normoalbuminuria (p <0.01). We identified a statistically significant positive association between uric acid values and albuminuria, respectively 25- (OH)2 vitamin D3 deficiency and microalbuminuria (p <0.01).


2008 ◽  
Vol 11 (4) ◽  
pp. 988-991
Author(s):  
Robert C Atkins ◽  
Paul Zimmet

In 2003, the International Society of Nephrology and the International Diabetes Federation launched a booklet called “Diabetes in the Kidney: Time to act” [1] to highlight the global pandemic of type 2 diabetes and diabetic kidney disease. ration (PZ)


2021 ◽  
Author(s):  
Ning Zhang ◽  
Rui Fan ◽  
Jing Ke ◽  
Qinghua Cui ◽  
Dong ZHAO

Abstract BackgroundMicroalbuminuria is the main characteristic of Diabetic kidney disease (DKD), but it fluctuates greatly under the influence of blood glucose. Our aim was to establish some common clinical variables which could be easily collected to predict the risk of DKD in patients with type 2 diabetes. Methods and resultsWe build an artificial intelligence (AI) model to quantitively predict the risk of DKD based on the biomedical parameters from 1239 patients. An information entropy-based feature selection method was applied to screen out the risk factors of DKD. The dataset was divided with 4/5 into the training set and 1/5 into the test set. By using the selected risk factors, 5-fold cross-validation is applied to train the prediction model and it finally got AUC of 0.72 and 0.71 in the training set and test set respectively. In addition, we provide a method of calculating risk factors’ contribution for individuals to provide personalized guidance for treatment. We set up web-based application available on http://www.cuilab.cn/dkd for self-check and early warning. ConclusionsWe establish a feasible prediction model for DKD and suggest the degree of risk contribution of each indicator for each individual, which has certain clinical significance for early intervention and prevention.


Genes ◽  
2019 ◽  
Vol 10 (10) ◽  
pp. 782 ◽  
Author(s):  
Huang ◽  
Chen ◽  
Liu ◽  
Lin ◽  
Lin ◽  
...  

Cholesteryl ester transfer protein (CETP) plays an important role in lipid metabolism. Low levels of high-density lipoprotein cholesterol (HDL-C) increase the risk of type 2 diabetes (T2D). This study investigated CETP gene variants to assess the risk of T2D and specific complications of diabetic kidney disease (DKD) and diabetic retinopathy. Towards this, a total of 3023 Taiwanese individuals (1383 without T2D, 1640 with T2D) were enrolled in this study. T2D mice (+Leprdb/+Leprdb, db/db) were used to determine CETP expression in tissues. The A-alleles of rs3764261, rs4783961, and rs1800775 variants were found to be independently associated with 2.86, 1.71, and 0.91 mg/dL increase in HDL-C per allele, respectively. In addition, the A-allele of rs4783961 was significantly associated with a reduced T2D risk (odds ratio (OR), 0.82; 95% confidence interval (CI), 0.71‒0.96)), and the A-allele of rs1800775 was significantly related to a lowered DKD risk (OR, 0.78; 95% CI, 0.64‒0.96). CETP expression was significantly decreased in the T2D mice kidney compared to that in the control mice (T2D mice, 0.16 0.01 vs. control mice, 0.21 0.02; p = 0.02). These collective findings indicate that CETP variants in the promoter region may affect HDL-C levels. Taiwanese individuals possessing an allele associated with higher HDL-C levels had a lower risk of T2D and DKD.


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