Optimisation of glycaemic control during episodes of severe/acute hyperglycaemia in patients with type 2 diabetes mellitus
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Background Patients with type 2 diabetes mellitus (T2DM) are frequently admitted to the hospital with severe or acute hyperglycaemia secondary to an acute illness or disease. Uncontrolled glycaemia is a significant problem during severe or acute hyperglycaemia. Objective This study sought to identify demographic, clinical, and genetic factors that may contribute to increased insulin resistance or worsening of glycaemic control in patients with T2DM. Setting This prospective cohort study included 156 patients with T2DM and severe or acute hyperglycaemia who were treated with insulin at any medical ward of the National University of Malaysia Medical Centre. Method Insulin resistance was determined using the homeostatic model assessment–insulin resistance index. Glycaemic control during the episode of hyperglycaemia was assessed as the degree to which the patient achieved the target glucose levels. The polymerase chain reaction–restriction fragment length polymorphism method was used to identify polymorphisms in insulin receptor substrate (IRS) genes. Main outcome measure Identification of possible predictors (demographic, clinical, or genetic) for insulin resistance and glycaemic control during severe/acute hyperglycaemia. Results A polymorphism in IRS1, r.2963 G>A (p.Gly972Arg), was a significant predictor of both insulin resistance [odds ratios (OR) 4.48; 95 % confidence interval (CI) 1.2–16.7; P = 0.03) and worsening of glycaemic control (OR 6.04; 95 % CI 0.6–64.6; P = 0.02). The use of loop diuretics (P < 0.05) and antibiotics (P < 0.05) may indirectly predict worsening of insulin resistance or glycaemic control in patients with severe/acute hyperglycaemia. Conclusion Clinical and genetic factors contribute to worsening of insulin resistance and glycaemic control during severe/acute hyperglycaemia in patients with T2DM. Early identification of factors that may influence insulin resistance and glycaemic control may help to achieve optimal glycaemic control during severe/acute hyperglycaemia.
KeywordsAcute hyperglycaemia Genetics Glycaemic control Insulin resistance Malaysia Predictive models Predictors Type 2 diabetes
The authors would like to thank the National University of Malaysia, University of Malaya, Malaysia, and the Ministry of Higher Education, Malaysia, for financial and technical support.
Conflicts of interest
The authors have no conflict of interest to report.
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