Effects of intensive insulin therapy alone and with added pioglitazone on renal salt/water balance and fluid compartment shifts in type 2 diabetes

2010 ◽  
Vol 12 (2) ◽  
pp. 133-138 ◽  
Author(s):  
S. Mudaliar ◽  
A. R. Chang ◽  
V. R. Aroda ◽  
E. Chao ◽  
P. Burke ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Water Balance ◽  
Insulin Therapy ◽  
Intensive Insulin Therapy ◽  
Salt Water ◽  
Fluid Compartment

Effect of short-term intensive insulin therapy on the incretin response in early type 2 diabetes

2019 ◽  
Vol 45 (2) ◽  
pp. 197-200 ◽  
Author(s):  
H. Choi ◽  
C.K. Kramer ◽  
B. Zinman ◽  
P.W. Connelly ◽  
R. Retnakaran
Keyword(s):  
Type 2 Diabetes ◽  
Insulin Therapy ◽  
Intensive Insulin Therapy ◽  
Early Type ◽  
Short Term

scholarly journals Development and Validation of a Hypoglycemia Risk Model for Intensive Insulin Therapy in Patients with Type 2 Diabetes

2020 ◽  
Vol 2020 ◽  
pp. 1-7
Author(s):  
Xiling Hu ◽  
Weiran Xu ◽  
Shuo Lin ◽  
Cang Zhang ◽  
Cong Ling ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Insulin Therapy ◽  
Intensive Insulin Therapy ◽  
Risk Model ◽  
Treatment Time ◽  
Fasting Blood Glucose ◽  
Prediction Rule ◽  
Derivation Cohort ◽  
Total Treatment Time

Aims. To develop a simple hypoglycemic prediction model to evaluate the risk of hypoglycemia during hospitalization in patients with type 2 diabetes treated with intensive insulin therapy. Methods. We performed a cross-sectional chart review study utilizing the electronic database of the Third Affiliated Hospital of Sun Yat-sen University, and included 257 patients with type 2 diabetes undergoing intensive insulin therapy in the Department of Endocrinology and Metabolism. Logistic regression analysis was used to derive the clinical prediction rule with hypoglycemia (blood glucose≤3.9 mmol/L) as the main result, and internal verification was performed. Results. In the derivation cohort, the incidence of hypoglycemia was 51%. The final model selected included three variables: fasting insulin, fasting blood glucose, and total treatment time. The area under the curve (AUC) of this model was 0.666 (95% CI: 0.594–0.738, P<0.001). Conclusions. The model’s hypoglycemia prediction and the actual occurrence are in good agreement. The variable data was easy to obtain and the evaluation method was simple, which could provide a reference for the prevention and treatment of hypoglycemia and screen patients with a high risk of hypoglycemia.

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