ArticleIndian journal of endocrinology and metabolism
Glycosylation Gap in Patients with Diabetes with Chronic Kidney Disease and Healthy Participants: A Comparative Study.
Article in Indian journal of endocrinology and metabolism. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed, 5 citations in OpenAlex.
- The Correlation Between Glycation Gap and Renal Complications in Patients with Type 2 Diabetes Mellitus.Diabetes, metabolic syndrome and obesity : targets and therapy · 2024Article
- Positive-unlabelled learning of glycosylation sites in the human proteome.BMC bioinformatics · 2019Article
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2 authors at 1 institution in 1 country.
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Abstract
aimThe aim of this study it to determine the level of glycosylation gap in patients with type 2 diabetes and its relation with kidney dysfunction. MATERIALS AND
methodsIn this study, 150 individuals were enrolled (aged 20-75 year) and divided into three groups. Group 1 included 50 nondiabetic individuals who served as control. Group 2 included 50 patients with type 2 diabetes without chronic kidney disease (CKD), and in Group 3, there were 50 patients with type 2 diabetes with CKD. Glycated hemoglobin (HbA1c) and fructosamine (FA) were measured in all groups to determine the glycosylation gap (GG), predicted HbA1c, and mean blood glucose (MBG). GG is defined as the difference between measured HbA1c and HbA1c predicted from FA based on the population regression of HbA1c on FA. The variables were compared by correlation analysis.
resultsSerum creatinine level was significantly high in patients with CKD (1.93 ± 0.99) as compared to patients with diabetes and control (0.891 ± 0.16; 0.912 ± 0.1), respectively. The study demonstrated a significant elevation in serum FA, measured HbA1c and predicted HbA1c, MBG in patients with diabetes with CKD as compared with those of without CKD, and controls. GG was found in healthy control (0.51 ± 0.78), patients with type 2 diabetes without CKD (0.62 ± 0.45), and patients with diabetes with CKD (1.0 ± 0.91), respectively.
conclusionIt is concluded that GG may be a useful clinical research tool for evaluating pathological source of variation in diabetes complications such as kidney disease.
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