scholarly journals Observations of Microalbuminuria and its Association with CardioVascular Complication in Type 2 Diabetes

2021 ◽  
Vol 09 (07) ◽  
Author(s):  
Dr Anand Kumar ◽  
2016 ◽  
Vol 57 (3) ◽  
pp. 7-16
Author(s):  
N. A. Kravchun ◽  
O. V. Zemlianitsyna ◽  
I. V. Cherniavskaya ◽  
Yu. I. Karachentsev

The necessity to identify was grounded and assesses the dynamics of albuminuria and glomerular filtration rate in patients with type 1 and type 2 diabetes (as an early marker of endothelial dysfunction and a predictor of cardiovascular complication) on the background of pathogenetic therapy with glycosaminoglycans sulodexide was done. Clinically significant reduction in the excretion of both total protein and albumin in the urine was found. It indicates an improvement of microcirculation in the kidney along with an increase in glomerular filtration rate. The increase in the glomerular filtration rate is most pronounced in patients with type 2 diabetes with comorbid non-alcoholic fatty liver disease.


Author(s):  
Napa Rachata ◽  
Punnarumol Temdee ◽  
Worasak Rueangsirarak ◽  
Chayapol Kamyod

Cardiovascular diseases are chronic diseases that cause serious morbidity and mortality worldwide. Unfortunately, the patients with type 2 diabetes mellitus and hypertension have a high risk of having a cardiovascular complication. For these reasons, patients with type 2 diabetes mellitus and hypertension should be aware of cardiovascular complication along their healthcare journey. To prevent cardiovascular complication from diabetes and hypertension, accurate risk prediction is required for a long term self-management process. Consequently, this paper proposes a fuzzy logic based method for predicting cardiovascular risk particularly for a patient with type 2 diabetes mellitus and hypertension. This paper also proposes a set of factors based on the patient’s lifestyle as the key factors besides clinical factors because of their implicit impact on the quality of life of the patient. The proposed model thus employs 15 predictors for both clinical and lifestyle risk factors. Additionally, the proposed model is constructed based on the scientific data and implicit knowledge of the experts. The experiment with 121 patients shows that the proposed prediction model provides 96.69% accuracy compared to those decided by the experts.


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