Introduction: Hemolysis, icterus, and lipemia (HIL) are frequent preanalytical interferences, leading to erroneous results or sample rejection.While individual effects of these indices have been studied, their interferences on each other remain largely unexplored.This study aimed to evaluate the cross-interference of HIL parameters using endogenous patient-derived samples, thereby ensuring clinically relevant conditions, and to propose a decision algorithm for improved sample quality assessment.Materials and methods: Following the CLSI-EP07 guideline, high-concentration icterus and lipemia pools from leftover clinical samples and hemolizate pool have been prepared.These pools were serially diluted with low-index serum (HIL0) to obtain defined combinations.Indices were measured using the Abbott Alinity c system.Cross interferences were calculated as percentage bias compared to baseline values.Results: High level hemolysis remained largely unaffected by other indices.Hemolysis in the range of 2.5-10.0g/L caused a 20-150% false increase in lipemia and a 10-60% false decrease in icterus.Conversely, lipemia in the range of 25-100 index led to a 20-150% false increase in icterus and reduced low level of hemolysis by 10-30%.Similarly, icterus at 42.75-171 µmol/L resulted in a 15-45% false reduction in low levels of hemolysis.No concentration-dependent systematic bias was observed for lipemia and icterus, whereas hemolysis showed level-dependent effects.Conclusions: Cross-interference among HIL indices can lead to misinterpretation if indices are assessed independently.A rule-based, threshold-dependent algorithm incorporating these interactions is proposed to enhance accuracy in sample rejection decisions.Implementation of such integrated approaches, along with manufacturer transparency may significantly improve laboratory reliability.
Yavuz et al. (Thu,) studied this question.