title: Correlation Between Glycated Hemoglobin and Homa Indices in Type 2 Diabetes Mellitus: Prediction of Beta-Cell Function from Glycated Hemoglobin.
abstract: BACKGROUND
  The present study aimed to determine the most efficient insulin resistance function related to glycemic control expressed as glycated hemoglobin (HbA1c) in type 2 diabetes mellitus patients (T2DM). The other aim is to derive equations for the prediction of beta cell functions containing HbA1c as a parameter in addition to fasting glucose and insulin.
  
  
  METHODS
  T2DM Patients were grouped according to the following: (1) degree of control (good, fair, and poor control) and (2) insulin resistance as observed in obtained data and significant differences revealed by the homeostasis model assessment (HOMA) of related parameters (insulin resistance = HOMA2IR, beta-cell function = HOMA%B, and insulin sensitivity = HOMA%S) among groups. Correlations and forecasting regression analysis were calculated.
  
  
  RESULTS
  HbA1c was found to be correlated with insulin resistance parameters in T2DM subgroups. This correlation was also significantly correlated with HOMA%B and the quantitative insulin sensitivity check index (QUICKI) in fair and poor control groups. Regression analysis was used to predict the forecasting equations for HOMA%B. The best applicable equations were derived for healthy control (HOMA2%B=-1.76*FBG+5.00*Insulin+4.69*HbA1c+189.84) and poor control groups (HOMA2%B=0.001* FBG+0.5*Insulin-8.67*HbA1c+101.96). These equations could be used to predict β-cell function (HOMA%B) after FBG, insulin and HbA1c values were obtained for healthy and poor control groups. In the good and fair control groups, the applicability of the HOMA model fails to yield appropriate results.
  
  
  CONCLUSIONS
  Beta-cell function is correlated with QUICKI and HbA1c and could be predicted properly from HbA1c, insulin, and glucose in the healthy and poor control groups. New regression equations were established that involve HbA1c.
authors.affiliation: College of Science, Kufa University, Iraq.
authors.forename: Hussein Kadhem
authors.initials: HK
authors.lastname: Al-Hakeim
authors.affiliation: Dean of the College of Medicine, Kufa University, Iraq.
authors.forename: Mohammed Saied
authors.initials: MS
authors.lastname: Abdulzahra
keywords: Bennett index; HbA1c; QUICKI; insulin resistance; type 2 diabetes mellitus