Does Homeostasis Model Assessment Insulin Resistance Have a Predictive Value for Post-Coronary Artery Bypass Grafting Surgery Outcomes?
Year: 2014
Type: article
Study design: Observational Study
Abstract: OBJECTIVE: This study aims to investigate whether pre-operative Homeostasis Model Assessment Insulin Resistance (HOMA-IR) value is a predictor in non-diabetic coronary artery bypass grafting patients in combination with hemoglobin A1c, fasting blood glucose and insulin levels. METHODS: Eighty one patients who were admitted to Cardiovascular Surgery Clinic at our hospital between August 2012 and January 2013 with a coronary artery bypass grafting indication were included. Patients were non-diabetic with <6.3% hemoglobin A1c and were divided into two groups including treatment and control groups according to normal insulin resistance (HOMA-IR<2.5, Group A; n=41) and high insulin resistance (HOMA-IR>2.5, Group B; n=40), respectively. Pre-operative fasting blood glucose and insulin were measured and serum chemistry tests were performed. The Homeostasis Model Assessment Insulin Resistance values were calculated. Statistical analysis was performed. RESULTS: There was a statistically significant difference in fasting blood glucose and HOMA-IR values between the groups. Cross-clamping time, and cardiopulmonary bypass time were longer in Group B, compared to Group A (P=0.043 and P=0.031, respectively). Logistic regression analysis revealed that hemoglobin A1c was not a reliable determinant factor alone for pre-operative glucometabolic evaluation of non-diabetic patients. The risk factors of fasting blood glucose and cardiopulmonary bypass time were more associated with high Homeostasis Model Assessment Insulin Resistance levels. CONCLUSION: Our study results suggest that preoperative screening of non-diabetic patients with Homeostasis Model Assessment Insulin Resistance may improve both follow-up visit schedule and short-term outcomes, and may be useful in risk stratification of the high-risk population for impending health problems.
Authors: Ebuzer Aydin, Mehmet Ozkokeli
Language: English
Subfield: Endocrinology, Diabetes and Metabolism
Field: Medicine
Domain: Health Sciences
Open Access status: diamond
OpenAlex ID: W1996732280