EVALUATION OF THE ASSOCIATION BETWEEN C-PEPTIDE AND HBA1C IN PAEDIATRIC TYPE 1 DIABETES MELLITUS

Abstract

Introduction: Type 1 diabetes mellitus is a chronic autoimmune disorder characterized by progressive destruction of pancreatic β-cells, resulting in reduced endogenous insulin secretion. Serum C-peptide is a reliable biomarker of residual β-cell function, while HbA1c reflects long-term glycaemic control. This study was conducted to evaluate the association between serum C-peptide and HbA1c among paediatric patients with type 1 diabetes mellitus. Methods: This hospital-based cross-sectional study was conducted in the Department of Paediatrics, Government Cuddalore Medical College and Hospital, over a period of 18 months. A total of 45 children and adolescents aged 1–18 years with type 1 diabetes mellitus receiving regular insulin therapy were included by consecutive sampling. Demographic details, disease duration, BMI, daily insulin requirement, serum C-peptide, and HbA1c levels were recorded. Data were analyzed using descriptive statistics, comparison of means, and correlation analysis. Results: The majority of participants belonged to the 6–10 years age group (37.8%), and males constituted 53.3% of the study population. Serum C-peptide levels ≤0.6 ng/mL were observed in 64.4% of children, while 35.6% had levels >0.6 ng/mL. The mean HbA1c was 8.94 ± 1.42%. Mean HbA1c declined progressively with increasing C-peptide categories, from 10.5 ± 1.0% among children with C-peptide <0.2 ng/mL to 7.8 ± 1.0% among those with C-peptide >0.6 ng/mL, and this difference was statistically significant (p < 0.001). Serum C-peptide showed significant negative correlations with HbA1c, duration of diabetes, and daily insulin dose, and significant positive correlations with age at diagnosis and BMI. Conclusion: Serum C-peptide was significantly associated with HbA1c among paediatric patients with type 1 diabetes mellitus. Lower C-peptide levels were associated with poorer glycaemic control and higher insulin requirement. C-peptide estimation may be useful as a supportive biomarker for individualized diabetes management.