Methods to reduce lipemic interference in clinical chemistry tests: a systematic review and recommendations

Handling of lipemic samples in the clinical laboratory

Interferences in the clinical laboratory may lead physicians misinterpret results for some biological analytes. The most common analytical interferences in the clinical laboratory include hemolysis, icterus and lipemia. Lipemia is defined as turbidity in a sample caused by the accumulation of lipoproteins, mainly very-low density lipoproteins (VLDL) and chylomicrons. Several methods are available for the detection of lipemic samples, including the lipemic index, or triglyceride quantification in serum or plasma samples, or mean corpuscular hemoglobin (MCHC) concentration in blood samples. According to the European Directive 98/79/CE, it is the responsibility of clinical laboratories to monitor the presence of interfering substances that may affect the measurement of an analyte. There is an urgent need to standardize interference studies and the way interferences are reported by manufacturers. Several methods are currently available to remove interference from lipemia and enable accurate measurement of biological quantities. The clinical laboratory should establish a protocol for the handling of lipemic samples according to the biological quantity to be tested.

Interferences in immunoassays: review and practical algorithm

Immunoassays are currently the methods of choice for the measurement of a large panel of complex and heterogenous molecules owing to full automation, short turnaround time, high specificity and sensitivity. Despite remarkable performances, immunoassays are prone to several types of interferences that may lead to harmful consequences for the patient (e.g., prescription of an inadequate treatment, delayed diagnosis, unnecessary invasive investigations). A systematic search is only performed for some interferences because of its impracticality in clinical laboratories as it would notably impact budget, turnaround time, and human resources. Therefore, a case-by-case approach is generally preferred when facing an aberrant result. Hereby, we review the current knowledge on immunoassay interferences and present an algorithm for interference workup in clinical laboratories, from suspecting their presence to using the appropriate tests to identify them. We propose an approach to rationalize the attitude of laboratory specialists when faced with a potential interference and emphasize the importance of their collaboration with clinicians and manufacturers to ensure future improvements.