ECE2024 Poster Presentations Diabetes, Obesity, Metabolism and Nutrition (130 abstracts)
Use of glycated albumin in transfusion-dependent β-thalassemic (TDT) patients with diabetes mellitus: preliminary results
Martina Verrienti 1 , Alberto Gobbo 1 , Camilla Alice Cattaneo 1 , Elisa Mari 2 , Olga Sofritti 2 , Marcello Monesi 3 , Stefano Pizzicotti 4 , Filomena Longo 2 , Maria Rosaria Ambrosio 1 & Maria Chiara Zatelli 1
1Section of Endocrinology and Internal Medicine, Department of Medical Sciences, University of Ferrara, Ferrara, Italy; 2Regional HUB Centre for Thalassaemia and Haemoglobinopathies, Department of Medicine, AOU S. Anna, Ferrara, Italy; 3Primary Care Department, Diabetes Unit, Ferrara "Sant’ Anna" Hospital, Ferrara, Italy; 4Department of Translational Medicine and for Romagna, University of Ferrara, Ferrara, Italy
Background: Patients with transfusion-dependent β -thalassemia (TDT) often experience several endocrine complications, including diabetes mellitus (DM). In TDT, the reliability of glycated haemoglobin (HbA1c) assessment is compromised due to elevated erythrocytes turnover and frequent transfusions. Glycated Albumin (GA), a product of non-enzymatic albumin glycation, has been investigated as a medium-term glycaemic marker (21 days) in the general diabetic population. Since GA is not affected by erythropoiesis nor by iron imbalance, it could potentially serve as a reliable marker for diagnosing and monitoring DM in TDT.
Objective: To evaluate the use of GA assessment in a population of TDT patients with DM.
Methods: We conducted a single-centre observational study, enrolling 28 TDT adults (15F, 13M, mean age 53.7±7.4 years, mean BMI 23.7±3.4 Kg/m2) with DM. Patients were tested for fasting glucose (FG), HbA1c, fructosamine, GA and iron deposit indexes (ferritin, T2* pancreas). GA measurement was performed using a standardized enzymatic quantitative method. Two hours after a standardized meal (50 g carbohydrates), post-prandial glycaemia (PPG) was assessed. Based on glycaemic control, patients were divided into groups according to FG (A ≥ 130 mg/dl; B < 130 mg/dl) or PPG (C ≥ 180 mg/dl; D < 180 mg/dl).
Results: GA was associated with FG (Pearson’s r=0.613, P<. 01), HbA1c (Pearson’s r=0.748, P<. 001), fructosamine (Pearson’s r=0.620, P<. 001), and with PPG (Pearson’s r=0.432, P<. 05), but not with sex, age, BMI and iron deposits. By using ROC curves we identified a GA cut-off value of 15.7% as displaying 100% sensitivity and 58% specificity to differentiate A from B patients (AUC=0.845, P=.005). Similarly, a GA threshold of 15.2% had 100% sensitivity and 50% specificity in discriminating C from D patients (AUC=0.769, P=.025).
Conclusion: To the best of our knowledge, these are the first data regarding the use of GA in diabetic TDT patients. The identified GA thresholds may help the identification of non-compensated TDT diabetic patients, taking into account the risk of false positives. Further studies, using continuous glucose monitoring to assess glycaemic control, are warranted in order to understand more about the role of GA in monitoring diabetic TDT patients.
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Endocrine Abstracts
ISSN 1470-3947 (print) | ISSN 1479-6848 (online)
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