ArticleJournal of medical biochemistry2015
Correlation Between Glycated Hemoglobin and Homa Indices in Type 2 Diabetes Mellitus: Prediction of Beta-Cell Function from Glycated Hemoglobin.
Article in Journal of medical biochemistry, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed, 22 citations in OpenAlex.
- Article
- The effects of salvia hispanica (chia seeds) on insulin sensitivity, hematological inflammatory indices and liver function in obese patients with non-alcoholic fatty liver disease (NAFLD).Nutrition & metabolism · 2025Article
- The effect of myo-inositol supplementation on AMPK/PI3K/AKT pathway and insulin resistance in patients with NAFLD.Food science & nutrition · 2024Article
- The Potential Diagnostic Utility of SMAD4 and ACCS in the Context of Inflammation in Type 2 Diabetes Mellitus Patients.Biomedicines · 2024Article
- Maternal Tryptophan Catabolites and Insulin Resistance Parameters in Preeclampsia.Biomolecules · 2023Article
- Intersections between Copper, β-Arrestin-1, Calcium, FBXW7, CD17, Insulin Resistance and Atherogenicity Mediate Depression and Anxiety Due to Type 2 Diabetes Mellitus: A Nomothetic Network Approach.Journal of personalized medicine · 2022Article
- HbA mutation causing false-normal HbA1c results determined by HPLC in a patient with type 2 diabetes mellitus: A case report.Experimental and therapeutic medicine · 2021Article
- The immune-opioid axis in prediabetes: predicting prediabetes with insulin resistance by plasma interleukin-10 and endomorphin-2 to kappa-opioid receptors ratio.Diabetology & metabolic syndrome · 2021Article
- Serum cytokine dependent hematopoietic cell linker (CLNK) as a predictor for the duration of illness in type 2 diabetes mellitus.Journal of diabetes and metabolic disorders · 2020Article
- Heterozygote Hemoglobin G-Coushatta as the Cause of a Falsely Decreased Hemoglobin A1C in an Ion-exchange HPLC Method.Journal of medical biochemistry · 2017Article
- Comparison of the Usefulness of the Updated Homeostasis Model Assessment (HOMA2) with the Original HOMA1 in the Prediction of Type 2 Diabetes Mellitus in Koreans.Diabetes & metabolism journal · 2016Article
Corrections and comments
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe 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.
methodsT2DM 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.
resultsHbA1c 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.
conclusionsBeta-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.
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