Allergy: Evaluation of 16 years (2007-2022) results of the shared external quality assessment program in Belgium, Finland, Portugal and The Netherlands.

OBJECTIVES: This paper evaluates 16 year results of the Allergy EQA program shared by EQA organisers in Belgium, Finland, Portugal, and The Netherlands. METHODS: The performance of Thermo Fisher and Siemens user groups (in terms of concordance between both groups, between laboratory CV, prevalence of clinically significant errors) and suitability of samples (stability and validity of dilution of patient samples) are evaluated using data of 192 samples in the EQA programs from 2007 to 2022. Measurands covered are total IgE, screens and mixes, specific IgE extracts and allergen components. RESULTS: There is perfect (53 %), acceptable (40 %) and poor (6 %) concordance between both method groups. In case of poor concordance the best fit with clinical data is seen for Thermo Fisher (56 %) and Siemens (26 %) respectively. The between laboratory CV evolves from 7.8 to 6.6 % (Thermo Fisher) and 7.3 to 7.7 % (Siemens). The prevalence of blunders by individual laboratories is stable for Siemens (0.4 %) and drops from 0.4 to 0.2 % for Thermo Fisher users. For IgE, the between year CV of the mean of both user groups is 1 %, and a fifteen-fold dilution of a patient sample has an impact of 2 and 4 % on the recovery of Thermo Fisher and Siemens user groups. CONCLUSIONS: The analytical performance of Thermo Fisher is slightly better than that of Siemens users but the clinical impact of this difference is limited. Stability of the sample and the low impact of dilution on the recovery of measurands demonstrates the suitability for purpose of the EQA program.

NUMBER: standardized reference intervals in the Netherlands using a 'big data' approach.

Background External quality assessment (EQA) programs for general chemistry tests have evolved from between laboratory comparison programs to trueness verification surveys. In the Netherlands, the implementation of such programs has reduced inter-laboratory variation for electrolytes, substrates and enzymes. This allows for national and metrological traceable reference intervals, but these are still lacking. We have initiated a national endeavor named NUMBER (Nederlandse UniforMe Beslisgrenzen En Referentie-intervallen) to set up a sustainable system for the determination of standardized reference intervals in the Netherlands. Methods We used an evidence-based 'big-data' approach to deduce reference intervals using millions of test results from patients visiting general practitioners from clinical laboratory databases. We selected 21 medical tests which are either traceable to SI or have Joint Committee for Traceability in Laboratory Medicine (JCTLM)-listed reference materials and/or reference methods. Per laboratory, per test, outliers were excluded, data were transformed to a normal distribution (if necessary), and means and standard deviations (SDs) were calculated. Then, average means and SDs per test were calculated to generate pooled (mean±2 SD) reference intervals. Results were discussed in expert meetings. Results Sixteen carefully selected clinical laboratories across the country provided anonymous test results (n=7,574,327). During three expert meetings, participants found consensus about calculated reference intervals for 18 tests and necessary partitioning in subcategories, based on sex, age, matrix and/or method. For two tests further evaluation of the reference interval and the study population were considered necessary. For glucose, the working group advised to adopt the clinical decision limit. Conclusions Using a 'big-data' approach we were able to determine traceable reference intervals for 18 general chemistry tests. Nationwide implementation of these established reference intervals has the potential to improve unequivocal interpretation of test results, thereby reducing patient harm.

Analytical validation of the Hevylite assays for M-protein quantification.

BACKGROUND: The heavy/light chain (HLC) immunoassay quantifies the different heavy chain/light chain combinations of each immunoglobulin (Ig) class. This makes the HLC assay suited to quantify monoclonal immunoglobulins (M-protein) and for monitoring of patients with monoclonal gammopathies. This method is particularly advantageous for those samples in which electrophoretic quantification of the M-protein is not possible. METHODS: In this study we tested the analytical performance of the HLC assay in 166 routine clinical samples and in 27 samples derived from the Dutch external quality assessment (EQA) for M-protein diagnostics (74 participating laboratories). Analytical accuracy was assessed by verification that the sum of the HLC-pairs equaled total Ig concentration. Sensitivity of the HLC assay was determined in a direct method comparison with immunofixation electrophoresis (IFE). RESULTS: Comparison of HLC data with routine Ig diagnostics in 27 EQA samples showed very good correlation for both the quantification of polyclonal and monoclonal IgG, IgA and IgM (Pearson correlations [r] were 0.94, 0.99 and 0.99, respectively; slopes were 0.94, 1.07 and 0.98, respectively). The overall concordance between IFE and the HLC ratio was high (93%) with a Cohen κ coefficient of 0.84. Discrepancies between both assays were mainly caused by the higher sensitivity of IFE to detect monoclonality. CONCLUSIONS: We conclude that the HLC assay is an accurate method to quantify M-proteins that can improve monitoring of M-proteins in the beta fraction that cannot be quantified using electrophoretic techniques.

Can serum L-lactate, D-lactate, creatine kinase and I-FABP be used as diagnostic markers in critically ill patients suspected for bowel ischemia.

BACKGROUND: The prognostic value of biochemical tests in critically ill patients with multiple organ failure and suspected bowel ischemia is unknown. METHODS: In a prospective observational cohort study intensive care patients were included when the attending intensivist considered intestinal ischemia in the diagnostic workup at any time during intensive care stay. Patients were only included once. When enrolment was ended each patient was classified as 'proven intestinal ischemia', 'ischemia likely', 'ischemia unlikely' or 'no intestinal ischemia'. Proven intestinal ischemia was defined as the gross disturbance of blood flow in the bowel, regardless of extent and grade. Classification was based on reports from the operating surgeon, pathology department, endoscopy reports and CT-scan. Lactate dehydrogenase (LDH), creatine kinase (CK), alanine aminotransferase (ALAT), L-lactate were available for the attending physician. D-lactate and intestinal fatty acid binding protein (I-FABP) were analysed later in a batch. I-FABP was only measured in patients with proven ischemia or no ischemia. RESULTS: For 44 of the 120 included patients definite diagnostic studies were available. 23/44 patients (52%) had proven intestinal ischemia as confirmed by surgery, colonoscopy, autopsy and/or histopathological findings. LDH in these patients was 285 U/l (217-785) vs 287 U/l (189-836) in no-ischemia; p = 0.72. CK was 226 U/l in patients with proven ischemia (126-2145) vs 347 U/l (50-1427), p = 0.88. ALAT was 53 U/l (18-300) vs 34 U/l (14-34), p-0,56. D-lactate 0.41 mmol/l (0.11-0.75) vs 0.56 mmol/l (0.27-0.77), p = 0.46. L-lactate 3.5 mmol/l (2.2-8.4) vs 2.6 mmol/l (1.7-3.9), p = 0.09. I-FABP 2872 pg/ml (229-4340) vs 1020 pg/ml (239-5324), p = 0.98. Patient groups proven and likely ischemia together compared to unlikely and no-ischemia together showed significant higher L-lactate (p = 0.001) and higher D-lactate (p = 0.003). CONCLUSIONS: Measurement of LDH, CK, and ALAT did not discriminate critically ill patients with proven intestinal ischemia from those with definite diagnosis no-ischemia. However, L-lactate and D-lactate levels were higher in patients with proven or likely ischemia and need further study just as I-FABP.