• Francesca Gabriela Martino, Marina Vitillo, Massimo Pieri, Giulia Marrone, Fabio Gangeri, Ferruccio Ansali, Mariarita Dessì, Sergio Bernardini, Nicola Di Daniele, and Annalisa Noce.
• UOC Clinical Pathology, Hospital San Filippo Neri Laboratory HUB, ASL Roma 1, 00135 Rome, Italy.
• Medicina (Kaunas). 2021 Jul 14; 57 (7).

AbstractBackground and Objectives: Glycated hemoglobin (HbA1c) dosage is considered the gold standard in glycol-metabolic monitoring, but it presents limits, which can underestimate the glycemia trend. In this regard, it was introduced the glycated albumin (GA). The aim of the study is to verify the predictivity of the GA compared to HbA1c in identifying glyco-metabolic alterations in non-diabetic and diabetic hemodialysis (HD) patients. Materials and Methods: For this purpose, we conducted a multicenter study involving one analysis laboratory and six dialysis centers in the Lazio region (Rome, Italy). Both diabetic and non-diabetic HD patients represent the study population, and the protocol included five time points. Results: The analyzed data highlighted the ability of GA to predict changes in glycemic metabolism in HD patients, and GA values are not significantly influenced, like HbA1c, by dialysis therapy itself and by comorbidities of the uremic state, such as normochromic and normocytic anemia. Thus, GA seems to reflect early glyco-metabolic alterations, both in patients with a previous diagnosis of diabetes and in subjects without diabetes mellitus. As part of this study, we analyzed two HD patients (one diabetic and one non-diabetic) in which GA was more predictive of glycol-metabolic alterations compared to HbA1c. Our study confirms the need to compare classical biomarkers used for the monitoring of glyco-metabolic alterations with new ones, likely more reliable and effective in specific subgroups of patients in which the classic biomarkers can be influenced by the preexisting pathological conditions. Conclusions: In conclusion, our evidence highlights that in uremic patients, GA shows a better ability to predict glyco-metabolic alterations allowing both an earlier diagnosis of DM and a prompt modulation of the hypoglycemic therapy, thus improving the clinical management of these patients.

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