Comparison of Glycated Hemoglobin (Hba1c%) between High Performance Liquid Chromatography (HPLC) and Non-HPLC Methodology
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Abstract
Background: Glycated hemoglobin (HbA1c) serves as a pivotal marker for the long-term management of glucose levels in patients with diabetes. Accurate measurement of HbA1c is crucial for effective diabetes management and prevention of associated complications. While High-Performance Liquid Chromatography (HPLC) is widely used, non-HPLC methods have also gained popularity due to their simplicity and cost-effectiveness. Discrepancies in measurement between these methods have been a concern, impacting clinical decisions.
Objective: The objective of this study was to compare the measurement of HbA1c% using HPLC and non-HPLC methods in a cohort of diabetic patients, evaluating the consistency and reliability of these methodologies.
Methods: A cross-sectional study was conducted at Hayatabad Medical Complex, MTI, Peshawar from November 2023 to March 2024. A total of 65 diabetic patients aged between 18 and 70 years were enrolled. Participants were excluded if they had conditions known to affect HbA1c measurement. HbA1c levels were measured using both HPLC and non-HPLC methods. Statistical analysis was performed using SPSS version 25, employing t-tests to compare the mean HbA1c levels and Bland-Altman analysis to assess agreement between the two methods.
Results: The HPLC method showed a mean HbA1c% of 8.2 (SD = 1.4) while the non-HPLC method showed a mean HbA1c% of 7.6 (SD = 1.3). The Bland-Altman analysis indicated that 91.5% of the values fell within the limits of agreement, suggesting substantial agreement between the methods. The mean difference in HbA1c% between methods was 0.6%, with limits of agreement from -0.3 to 1.5.
Conclusion: Both HPLC and non-HPLC methods provided reliable HbA1c measurements, with a high degree of agreement. Despite minor discrepancies in mean values, both methodologies are suitable for the clinical monitoring of glycemic control in diabetic patients. Further studies with larger sample sizes and multiple centers are recommended to validate these findings.
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