Nationwide Harmonization Effort for Semi-Quantitative Reporting of SARS-CoV-2 PCR Test Results in Belgium.

From early 2020, a high demand for SARS-CoV-2 tests was driven by several testing indications, including asymptomatic cases, resulting in the massive roll-out of PCR assays to combat the pandemic. Considering the dynamic of viral shedding during the course of infection, the demand to report cycle threshold (Ct) values rapidly emerged. As Ct values can be affected by a number of factors, we considered that harmonization of semi-quantitative PCR results across laboratories would avoid potential divergent interpretations, particularly in the absence of clinical or serological information. A proposal to harmonize reporting of test results was drafted by the National Reference Centre (NRC) UZ/KU Leuven, distinguishing four categories of positivity based on RNA copies/mL. Pre-quantified control material was shipped to 124 laboratories with instructions to setup a standard curve to define thresholds per assay. For each assay, the mean Ct value and corresponding standard deviation was calculated per target gene, for the three concentrations (107, 105 and 103 copies/mL) that determine the classification. The results of 17 assays are summarized. This harmonization effort allowed to ensure that all Belgian laboratories would report positive PCR results in the same semi-quantitative manner to clinicians and to the national database which feeds contact tracing interventions.

Covid-19: contribution of clinical characteristics and laboratory features for early detection of patients with high risk of severe evolution.

BACKGROUND: The aim of this study was to identify early clinical and laboratory predictive factors of a severe coronavirus disease 2019 (COVID-19). METHODS: A retrospective study was conducted on adult patients hospitalized for COVID-19 in our hospital. Diagnosis was based on a positive real-time reverse transcription-polymerase chain reaction (RT-PCR) on nasopharyngeal samples. The cohort was divided into two groups, i.e. a favorable evolution (FE) group and an unfavorable evolution (UFE) group, including intensive care unit (ICU) and deceased patients.Results: A total of 198 patients were enrolled in the study, with 138 FE (70%) and 60 UFE (30%). Older age, male gender, comorbidities and dyspnea at admission constituted significantly worse prognosis factors. Among laboratory features, lymphocyte and platelet counts as well as corrected glomerular filtration rate were significantly lower in UFE patients, while neutrophil to lymphocyte ratio, inflammation biomarkers, creatinine, aspartate aminotransferase, lactate dehydrogenase (LDH), glycemia and D-dimer were significantly higher. Procalcitonin and LDH appeared as the most accurate variables according to receiver operating characteristic curves. CONCLUSIONS: This Belgian study revealed clinical and laboratory features able to predict high risk of ICU requirement, or even death, at admission time. These results provide a potential tool for patient's triage in a context of pandemic.Abbreviations: COVID-19: coronavirus disease 2019; ARDS: acute respiratory distress syndrome; DIC: disseminated intravascular coagulopathy; MOF: multi-organ failure; RT-PCR: real-time reverse transcription-polymerase chain reaction; UFE: unfavorable evolution; ICU: intensive care unit; EDTA: ethylenediamine tetraacetic acid; WBC: white blood cell count; Hb: hemoglobin level; PCT: procalcitonin; Na: sodium; K: potassium; PT: total protein, CRP: c-reactive protein; Cr: creatinine; ALAT: alanine aminotransferase; ALAT: aspartate aminotransferase; TB: total bilirubin, LDH: lactate dehydrogenase, FERR: ferritin; hs-Tnt: high sensitive-troponin T; cGFR: corrected glomerular filtration rate; QR: quick ratio; DDIM: D-dimer; FIB: fibrinogen; SD: standard deviation; IQR: interquartile ranges; ROC: receiver operating characteristics; ECMO: extracorporeal membrane oxygenation; NLR: neutrophil to lymphocyte ratio; AUC: area under the curve; BMI: body mass index.

The pathway through LC-MS method development: in-house or ready-to-use kit-based methods?

Historically, the determination of low concentration analytes was initially made possible by the development of rapid and easy-to-perform immunoassays (IAs). Unfortunately, typical problems inherent to IA technologies rapidly appeared (e.g. elevated cost, cross-reactivity, lot-to-lot variability, etc.). In turn, liquid chromatography tandem mass spectrometry (LC-MS/MS) methods are sensitive and specific enough for such analyses. Therefore, they would seem to be the most promising candidates to replace IAs. There are two main choices when implementing a new LC-MS/MS method in a clinical laboratory: (1) Developing an in-house method or (2) purchasing ready-to-use kits. In this paper, we discuss some of the respective advantages, disadvantages and mandatory requirements of each choice. Additionally, we also share our experiences when developing an in-house method for cortisol determination and the implementation of an "ready-to-use" (RTU) kit for steroids analysis.

Evolution of the slopes of ST2 and galectin-3 during marathon and ultratrail running compared to a control group.

Background Previous studies have suggested that exercising may induce cardiac damage. Galectin-3 (Gal-3) and soluble suppression of tumorigenicity 2 (ST2) are very interesting biomarkers for heart failure and myocardial fibrosis. We aimed to compare the kinetics of emerging fibrosis cardiac biomarkers as Gal-3 and ST-2 in endurance runners, and recreational runners before and after a running event represented by a marathon and an ultratrail event. Methods Blood samples were taken from 19 healthy non-elite marathon runners (42 km), 27 ultratour runners (67 km), and 14 recreational runners who represented the control group (10 km) just before the run (T0), just after (T1) and 3 h after (T2), in order to analyze Gal-3, ST2, hsTnT, NT-proBNP, CKMB and hsCRP. We compared the percentage of evolution and the slopes obtained from T0 to T1 (pT0T1) and from T1 to T2 (pT1T2), between the different groups of runners participating in three different races. Results Plasma cardiac biomarker concentrations increased significantly from baseline to immediately post-exercise and most of the time decreased over the subsequent 3-h period. For pT0T1 and pT1T2, the markers Gal-3 and ST2 showed a significant difference between types of run (p < 0.05 and p < 0.0001, respectively). During the recovery time, Gal-3 returned to the baseline values but not ST2 which continued to increase. Conclusions Gal-3 and ST2 are considered as a reflection of cardiac fibrosis and remodeling. The evolution of both was different, particularly after the recovery time. ST2 values exceeding cutoff values at any time.

Estimated glomerular filtration rate using a point of care measure of creatinine in patients with iohexol determinate GFR.

INTRODUCTION: Determination of creatinine and estimation of Glomerular Filtration Rate (GFR) rapidly before injection of contrast media provides early detection of high-risk patients for acute kidney failure. Hence, a rapid point-of-care (POC) device (result in 30 s) allowing creatinine measurement and eGFR could be of interest. To validate this method, we considered a population referred for measuring GFR. METHODS: Iohexol plasma clearance was used to measure GFR. For each subject, enzymatic creatinine was quantified with two different devices: in plasma with the Roche Cobas analyzer and in capillary blood with the Nova Biomedical POC device. Both values of creatinine were used in the CKD-EPI equation for estimated glomerular filtration rate (eGFR). eGFR using POC was compared to eGFR using Cobas and to mGFR by Passing Bablok regression, calculation of bias, precision and accuracy (or concordance) within 30%. Also, we calculated the rate of discrepant staging (eGFR >60 or ≤ 60 when mGFR is actually ≤60 and > 60) with both creatinine methods. RESULTS: 120 subjects (52 ±â€¯13 years, 49% of women) were included. Mean mGFR was 77 ±â€¯27 mL/min/1.73m2 with 29 patients presenting mGFR <60 mL/min/1.73m2. Passing- Bablok regression comparing eGFR obtained with the POC and the Cobas was: eGFRPOC = -0.1 (95% CI: -7.4; 3.0) + 1.06 (95% CI: 1.00; 1.15) x eGFRCOBAS. Mean bias was 3.7 ±â€¯14.1 mL/min/1.73m2. Concordance within 30% was 82%. Compared to mGFR, Passing-Bablok with POC was: eGFRPOC = -11.5 (95% CI: -22.9; -0.7) + 1.15 (95% CI: 1.02; 1.29) x mGFR. Mean bias was 0.1 ±â€¯17.6 mL/min/1.73m2. Accuracy within 30% was 81%. Between eGFRCOBAS and mGFR, mean bias was -3.7 ±â€¯12.5 mL/min/1.73m2. Accuracy within 30% was 95%. With POC (and Cobas), 3.3% (0.8%) of patients would have been considered with GFR > 60 mL/min/1.73m2 whereas mGFR it was ≤60 and 10% (9.2%) of them would have been considered with GFR ≤60 mL/min/1.73m2 when mGFR was >60. CONCLUSION: Creatinine measured with the POC has an acceptable performance when used with the CKD-EPI equation to estimate GFR. Its ability to detect GFR <60 mL/min/1.73m2 is not significantly different from the classical Roche assay. StatSensor Creatinine (Nova Biomedical) can be used for GFR screening before contrast media injection.

The Effect of Dietary Glycemic Properties on Markers of Inflammation, Insulin Resistance, and Body Composition in Postmenopausal American Women: An Ancillary Study from a Multicenter Protein Supplementation Trial.

Controversy exists as to whether high glycemic index/glycemic load (GI/GL) diets increase the risk of chronic inflammation, which has been postulated as a pathogenic intermediary between such diets and age-related alterations in body composition and insulin resistance. We conducted an ancillary study to a randomized, double-blind trial comparing the effects of a whey protein supplement (PRO, n = 38) and a maltodextrin supplement (CHO, n = 46) on bone density to evaluate the impact of a calibrated increase in GI/GL on inflammation, insulin resistance, and body composition in a healthy aging population. Markers of inflammation, HOMA, body composition, and GI/GL (estimated from 3-day food records) were assessed at baseline and 18 months. By 18 months, the GL in the CHO group increased by 34%, 88.4 ± 5.2 → 118.5 ± 4.9 and did not change in the PRO group, 86.5 ± 4.1 → 82.0 ± 3.6 (p < 0.0001). Despite this change there were no differences in serum CRP, IL-6, or HOMA at 18 months between the two groups, nor were there significant associations between GL and inflammatory markers. However, trunk lean mass (p = 0.0375) and total lean mass (p = 0.038) were higher in the PRO group compared to the CHO group at 18 months There were also significant associations for GL and change in total fat mass (r = 0.3, p = 0.01), change in BMI (r = 0.3, p = 0.005), and change in the lean-to-fat mass ratio (r = -0.3, p = 0.002). Our data suggest that as dietary GL increases within the moderate range, there is no detectable change in markers of inflammation or insulin resistance, despite which there is a negative effect on body composition.