Effect of electrical stimulation on blood glucose level and lipid profile of sedentary type 2 diabetic patients

2010 ◽  
Vol 30 (4) ◽  
pp. 194 ◽  
Author(s):  
Deepshikha Sharma ◽  
Shweta Shenoy ◽  
Jaspal Singh
Keyword(s):  
Electrical Stimulation ◽  
Blood Glucose ◽  
Blood Glucose Level ◽  
Lipid Profile ◽  
Glucose Level ◽  
Diabetic Patients ◽  
Type 2 Diabetic Patients ◽  
Type 2 Diabetic

Lower occurrence of low blood glucose level in elderly type 2 diabetic patients treated with gliclazide versus glibenclamide

2007 ◽  
Vol 7 (1) ◽  
pp. 91-93 ◽  
Author(s):  
Kenzo Oba ◽  
Yuki Inuzuka ◽  
Naoko Yamashita-Onodera ◽  
Kentaro Watanabe ◽  
Noriaki Matsumura ◽  
...  
Keyword(s):  
Blood Glucose ◽  
Blood Glucose Level ◽  
Glucose Level ◽  
Diabetic Patients ◽  
Type 2 Diabetic Patients ◽  
Type 2 Diabetic

scholarly journals Comparison of Different Clinical and Metabolic Parameters Among Type 2 Diabetic Patients With and Without Retinopathy in Primary Health Clinics in Medan City, North Sumatera, Indonesia

2020 ◽  
Vol 31 (2) ◽  
pp. 64-68
Author(s):  
Rusdiana ◽  
Sry Suryani Widjaja ◽  
Mila Hayati Daulay ◽  
Almaycano Ginting
Keyword(s):  
Diabetes Mellitus ◽  
Body Mass Index ◽  
Blood Glucose ◽  
Lipid Profile ◽  
Diabetic Patients ◽  
Type 2 Diabetic Patients ◽  
Primary Health ◽  
Significant Difference ◽  
Type 2 Diabetic

Background: The global prevalence of type 2 diabetes mellitus is increasing steadily and diabeticretinopathy is one of the microvascular complications of diabetes mellitus. This research aims tocompare different clinical and metabolic parameters among type 2 diabetic patients with and withoutdiabetic retinopathy. Methods: This cross-sectional study was done at various primary health care centers in Medan cityand the surrounding areas in North Sumatera from May to July 2020. Collected medical data includedblood pressure, body mass index, duration of disease, family history and medical treatment. Laboratorydata included blood glucose, glycated hemoglobin (HbA1c) and lipid profile. Diabetic retinopathy wasdetected by funduscopic examination by an ophthalmologist. Results: Total patients were 88 and 26 had retinopathy. There was significant difference betweenthe average blood pressure, blood glucose and HbA1C values among patients with type 2 diabetesmellitus with and without retinopathy (p<0.005). But, there was no significant difference between theaverage body mass index (BMI), abdominal circumference and lipid profile. Conclusion: Study showed that type 2 diabetic patients with retinopathy had increased blood glucoselevels and HbA1c than patients without retinopathy. Bangladesh J Medicine July 2020; 31(2) :64-68

Potential effect of opium addiction on lipid profile and blood glucose concentration in type 2 diabetic patients in Iran

2019 ◽  
Vol 24 (4) ◽  
pp. 420-425
Author(s):  
Somaye Sadat Hoseini ◽  
Seyed Alireza Saadatjoo ◽  
Samaneh Nakhaee ◽  
Alireza Amirabadizadeh ◽  
Maryam Rezaie ◽  
...  
Keyword(s):  
Blood Glucose ◽  
Lipid Profile ◽  
Glucose Concentration ◽  
Blood Glucose Concentration ◽  
Potential Effect ◽  
Diabetic Patients ◽  
Type 2 Diabetic Patients ◽  
Opium Addiction ◽  
Type 2 Diabetic

scholarly journals Application of Deep Neural Network Model Combined with Factor Analysis in Clinical Nursing Effect Analysis of Blood Glucose Level in Elderly Type 2 Diabetic Patients

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Yi Ding ◽  
DanDan Zhang
Keyword(s):  
Neural Network ◽  
Factor Analysis ◽  
Blood Glucose ◽  
Blood Glucose Level ◽  
Deep Neural Network ◽  
Diabetic Patients ◽  
Type 2 Diabetic Patients ◽  
Clinical Nursing ◽  
Type 2 Diabetic

In order to explore the clinical nursing effect of blood glucose level in elderly type 2 diabetic patients, this paper combines the deep neural network model and factor analysis from the perspective of multifactor analysis to construct a multifactor analysis model for the clinical nursing effect of blood glucose levels in elderly type 2 diabetic patients. Moreover, this paper analyzes the effects through experimental methods, collects cases through hospitals, and formulates research methods and related standards based on nursing research needs. In addition, this paper uses statistical methods to perform data processing, uses factor analysis to screen critical factors, and uses deep neural networks to process nursing data. The statistical results of the experimental research show that the deep neural network model combined with factor analysis can play a certain role in the clinical nursing effect. Thus, the blood glucose level analysis in elderly type 2 diabetic patients can provide a reference direction for the clinical care of blood glucose levels in elderly type 2 diabetic patients.

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