Development and Validation of a Hypoglycemia Risk Model for Intensive Insulin Therapy in Patients with Type 2 Diabetes. (21st September 2020)

• Record Type: Journal Article
• Authors: Hu, Xiling; Xu, Weiran; Lin, Shuo; Zhang, Cang; Ling, Cong; Chen, Miaoxia
• Other Names: Marfella Raffaele Academic Editor.
• Is Part Of: Journal of diabetes research. Volume 2020(2020)
• Publication Date: 2020-09-21
• Subjects: Diabetes -- Periodicals; Diabetes -- Pathophysiology -- Periodicals; Diabetes -- Prevention -- Periodicals; Diabetes -- Etiology -- Periodicals; Diabetes -- Epidemiology -- Periodicals; Diabetes -- Pathogenesis -- Periodicals; 616.462005
• DOI: 10.1155/2020/7292108
• Languages: English
• ISSNs: 2314-6745

Abstract

Abstract : 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.