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Insulin Injection and Hemolymph Extraction to Measure Insulin Sensitivity in Adult Drosophila melanogaster
Published on: June 30, 2011
Individualized correction of insulin measurement in hemolyzed serum samples
Zhi-Qi Wu1, Ju Lu1, Huanhuan Chen1
1Department of Laboratory Medicine, The First Affiliated Hospital of Nanjing Medical University, 300 Guang Zhou Road, Nanjing, Jiangsu Province, 210029, China.
Abstract:
Insulin measurement plays a key role in the investigation of patients with hypoglycemia, subtype classification of diabetes mellitus, insulin resistance, and impaired beta cell function. However, even slight hemolysis can negatively affect insulin measurement due to RBC insulin-degrading enzyme (IDE). Here, we derived and validated an individualized correction equation in an attempt to eliminate the effects of hemolysis on insulin measurement. The effects of hemolysis on insulin measurement were studied by adding lysed self-RBCs to serum. A correction equation was derived, accounting for both percentage and exposure time of hemolysis. The performance of this individualized correction was evaluated in intentionally hemolyzed samples. Insulin concentration decreased with increasing percentage and exposure time of hemolysis. Based on the effects of hemolysis on insulin measurement of 17 donors (baseline insulin concentrations ranged from 156 to 2119 pmol/L), the individualized hemolysis correction equation was derived: INScorr = INSmeas/(0.705lgHbplasma/Hbserum - 0.001Time - 0.612). This equation can revert insulin concentrations of the intentionally hemolyzed samples to values that were statistically not different from the corresponding insulin baseline concentrations (p = 0.1564). Hemolysis could lead to a negative interference on insulin measurement; by individualized hemolysis correction equation for insulin measurement, we can correct and report reliable serum insulin results for a wide range of degrees of sample hemolysis. This correction would increase diagnostic accuracy, reduce inappropriate therapeutic decisions, and improve patient satisfaction with care.
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