ABSTRACT
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.
ABSTRACT
Background: Manufacturers evaluate lipemia-induced interference using Intralipid®, but it does not contain all lipoprotein types. The aim of this study was to evaluate lipemiainduced interference in biochemical parameters from endogenous lipemic samples and SMOFlipid® supplemented samples, in order to assess if SMOFlipid® can be used in lipemic interference studies. Methods: Serum pools were supplemented with SMOFlipid® to achieve 800 mg/dL and 1500 mg/dL triglyceride concentration, and analyzed for 25 biochemical parameters both before and after the supplementation. In another independent phase, lipemic serum pools were prepared choosing patient samples of 800 mg/dL and 1500 mg/dL triglyceride concentration. These lipemic serum pools were ultracentrifugated in order to remove lipids. Biochemical parameters were analyzed before and after ultracentrifugation. The bias between SMOFlipid®-supplemented samples and endogenous lipemic samples were compared. The bias between the lipemic and non-lipemic samples were compared with the reference change value. Results: At 800 mg/dL triglyceride concentration, we found that total protein and transferrin had been affected only in endogenous lipemic serum samples. Magnesium and creatinine had been affected only in SMOFlipid®-supplemented samples. At 1500 mg/dL triglyceride concentration, we found that total protein, amylase, ferritin and glucose had lipemic interference only in endogenous lipemic samples, and chloride only in SMOFlipid®-supplemented samples. Conclusions: The use of SMOFlipid®-supplemented samples does not provide suitable data to estimate lipemia-induced interference. Thus, interference studies should be performed using a wide variety of lipemic patient samples that represent the heterogeneity of the lipoprotein particles size.
ABSTRACT
Excessive alcohol consumption leads to overproduction of urates and renal function plays a critical role in serum uric acid levels. We aimed to assess associations of hyperuricemia in patients with alcohol use disorder (AUD) and comparable Glomerular Filtration Rate (GFR). A total of 686 patients undergoing treatment for AUD between 2013 and 2017 were eligible (77% men); age at admission was 47 years [interquartile range (IQR), 40-53 years], age of onset of alcohol consumption was 16 years [IQR, 16-18 years] and the amount of alcohol consumed was 160 g/day [IQR, 120-240 g/day]. Body Mass Index was 24.7 kg/m2 [IQR, 21.9-28.4 kg/m2], eGFR was 105 mL/min/1.73 m2 [IQR, 95.7-113.0 mL], 9.7% had metabolic syndrome and 23% had advanced liver fibrosis (FIB-4 > 3.25). Prevalence of hyperuricemia was 12.5%. The eGFR-adjusted multivariate analysis showed that relative to patients with GGT ≤ 50, those with GGT between 51 and 300 U/L and those with GGT > 300 U/L were 4.31 (95% CI 1.62-11.46) and 10.3 (95% CI 3.50-29.90) times more likely to have hyperuricemia, respectively. Our data shows that hyperuricemia in the context of AUD is strongly associated with serum GGT levels and suggest an increased cardio-metabolic risk in this population.
