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Despite the evidence demonstrating the clinical utility of cardiac specific biomarkers in improving cardiovascular risk evaluation in several clinical conditions, even the most recent reviews and guidelines fail to consider their measurement in order to enhance the accuracy of the evaluation of cardiovascular risk in pregnant women. The aim of this review article was to examine whether the assay of cardiac specific biomarkers can enhance cardiovascular risk evaluation in pregnant women, first by reviewing the relationships between the physiological state of pregnancy and cardiac specific biomarkers. The clinical relevance of brain natriuretic peptide (BNP)/NT-proBNP and high-sensitivity cardiac troponin I/high-sensitivity cardiac troponin T (hs-cTnI/hs-cTnT) assay in improving cardiovascular risk evaluation is examined based on the results of clinical studies on subjects with normal and those with complicated pregnancy. Finally, the analytical approaches and clinical objectives related to cardio specific biomarkers are advocated in order to allow an early and more accurate evaluation of cardiovascular risk in pregnant women.

The clinical laboratory is often evaluated for the volume of testing. However, it is undeniable that laboratory tests affect clinical decision-making and are included in many clinical guidelines, meaning their contribution to determining clinical outcomes. Therefore, the clinical laboratory professional has the task of enhancing laboratory tests by optimizing the request and reporting phase and addressing patient outcomes. This opinion paper, presenting practical examples of managing value-based health care in the clinical laboratory context, underlines the need to shift towards value-based management to optimize outcome-based health care.

Objectives According to ISO 15189:2022, analytical performance specifications (APS) should relate to intended clinical use and impact on patient care. Therefore, we aimed to develop a web application for laboratory professionals to calculate APS based on a simulation of the impact of measurement uncertainty (MU) on the outcome using the chosen decision limits, agreement thresholds, and data of the population of interest. Methods We developed the “APS Calculator” allowing users to upload and select data of concern, specify decision limits and agreement thresholds, and conduct simulations to determine APS for MU. The simulation involved categorizing original measurand concentrations, generating measured (simulated) results by introducing different degrees of MU, and recategorizing measured concentrations based on clinical decision limits and acceptable clinical misclassification rates. The agreements between original and simulated result categories were assessed, and values that met or exceeded user-specified agreement thresholds that set goals for the between-category agreement were considered acceptable. The application generates contour plots of agreement rates and corresponding MU values. We tested the application using National Health and Nutrition Examination Survey data, with decision limits from relevant guidelines. Results We determined APS for MU of six measurands (blood total hemoglobin, plasma fasting glucose, serum total and high-density lipoprotein cholesterol, triglycerides, and total folate) to demonstrate the potential of the application to generate APS. Conclusions The developed data-driven web application offers a flexible tool for laboratory professionals to calculate APS for MU using their chosen decision limits and agreement thresholds, and the data of the population of interest.

The Contrast Media Safety Committee of the European Society of Urogenital Radiology has, together with the Preanalytical Phase Working Group of the EFLM Science Committee, reviewed the literature and updated its recommendations to increase awareness and provide insight into these interferences.

Objectives Immune monitoring is an important aspect in diagnostics and clinical trials for patients with compromised immune systems. Flow cytometry is the standard method for immune cell counting but faces limitations. Best practice guidelines are available, but lack of standardization complicates compliance with e.g., in vitro diagnostic regulations. Limited sample availability forces immune monitoring to predominantly use population-based reference intervals. Epigenetic qPCR has evolved as alternative with broad applicability and low logistical demands. Analytical performance specifications (APS) have been defined for qPCR in several regulated fields including testing of genetically modified organisms or vector-shedding. Methods APS were characterized using five epigenetic qPCR-based assays quantifying CD3 + , CD4 + , CD8 + T, B and NK cells in light of regulatory requirements. Results Epigenetic qPCR meets all specifications including bias, variability, linearity, ruggedness and sample stability as suggested by pertinent guidelines and regulations. The assays were subsequently applied to capillary blood from 25 normal donors over a 28-day period. Index of individuality (IoI) and reference change values were determined to evaluate potential diagnostic gains of individual reference intervals. Analysis of the IoI suggests benefits for individual over population-based references. Reference change values (RCVs) show that changes of approx. Fifty percent from prior measurement are suggestive for clinically relevant changes in any of the 5 cell types. Conclusions The demonstrated precision, long-term stability and obtained RCVs render epigenetic cell counting a promising tool for immune monitoring in clinical trials and diagnosis.

Objectives Our study aimed to determine the usefulness of duplicate testing in identifying irregular analytical errors and subsequent prevention of patient mismanagement. Methods In our laboratory, all requests for Na + , Ca 2+ , alkaline phosphatase (ALP), and high-sensitivity cardiac-troponin-I (hs-cTnI) are run in duplicate. Data from four separate weeks for Na + (n=21,649), Ca 2+ (n=14,803) and ALP (n=19,698); and a full year for hs-cTnI (n=17,036) were gathered. For each test, pre-defined limits for differences between duplicates were used to identify erroneous results (Fliers). We further characterised a subset of such fliers as “critical errors”, where duplicates fell on opposing sides of a reference/decision making threshold. The costs/benefits of running these tests in duplicate were then considered in light of increased number of tests analysed by this approach. Results For Na + , 0.03 % of duplicates met our flier defining criteria, and 0.01 % of specimens were considered critical errors. For Ca 2+ requests, 4.58 % of results met our flier defining criteria and 0.84 % were critical errors. For ALP, 0.22 % of results were fliers, and 0.01 % were critical errors. For hs-cTnI, 1.58 % of results were classified as fliers, whilst 0.14 % were classified as a critical error. Depending on the test in question, running all analyses in duplicate increased annual costs by as little as €1,100 (for sodium), and as much as €48,000 (for hs-cTnI). Conclusions Duplicate testing is effective at identifying and mitigating irregular laboratory errors, and is best suited for assays predisposed to such error, where costs are minimal, and clinical significance of an incorrect result can justify the practice.

Objectives Patient-based real-time quality control (PBRTQC), a laboratory tool for monitoring the performance of the testing process, has gained increasing attention in recent years. It has been questioned for its generalizability among analytes, instruments, laboratories, and hospitals in real-world settings. Our purpose was to build a machine learning, nonlinear regression-adjusted, patient-based real-time quality control (mNL-PBRTQC) with wide application. Methods Using computer simulation, artificial biases were added to patient population data of 10 measurands. An mNL-PBRTQC was created using eight hospital laboratory databases as a training set and validated by three other hospitals’ independent patient datasets. Three different Patient-based models were compared on these datasets, the IFCC PBRTQC model, linear regression-adjusted real-time quality control (L-RARTQC), and the mNL-PBRTQC model. Results Our study showed that in the three independent test data sets, mNL-PBRTQC outperformed the IFCC PBRTQC and L-RARTQC for all measurands and all biases. Using platelets as an example, it was found that for 20 % bias, both positive and negative, the uncertainty of error detection for mNL-PBRTQC was smallest at the median and maximum values. Conclusions mNL-PBRTQC is a robust machine learning framework, allowing accurate error detection, especially for analytes that demonstrate instability and for detecting small biases.

Objectives Large biological variation hinders application of patient-based real-time quality control (PBRTQC). The effect of analyte ratios on the ability of PBRTQC to improve error detection was investigated. Methods Four single analyte-ratio pairs (alanine aminotransferase [ALT] vs. ALT to aspartate aminotransferase ratio [R ALT ]; creatinine [Cr] vs. Cr to cystatin C ratio [R Cr ]; lactate dehydrogenase [LDH] vs. LDH to hydroxybutyrate dehydrogenase ratio [R LDH ]; total bilirubin [TB] vs. TB to direct bilirubin ratio [R TB ]) were chosen for comparison. Various procedures, including four conventional algorithms (moving average [MA], moving median [MM], exponentially weighted moving average [EWMA] and moving standard deviation [MSD]) were assessed. A new algorithm that monitors the number of defect reports per analytical run (NDR) was also evaluated. Results When a single analyte and calculated ratio used the same PBRTQC parameters, fewer samples were needed to detect systematic errors (SE) by taking ratios (p<0.05). Application of ratios in MA, MM and EWMA significantly enhanced their ability to detect SE. The influence of ratio on random error (RE) detection depended upon the analytes and PBRTQC parameters, as consistent advantage was not demonstrated. The NDR method performed well when appropriate parameters were used, but was only effective for unilateral SE. Rearrangement of sample order led to a significant deterioration of conventional algorithms’ performance, while NDR remained almost unaffected. Conclusions For analytes with large variation and poor PBRTQC performance, using ratios as PBRTQC indexes may significantly improve performance and achieve better anti-interference ability, providing a new class of monitoring indicators for PBRTQC.

Objectives Many hospitals use pneumatic tube systems (PTS) for transport of diagnostic samples. Continuous monitoring of PTS and evaluation prior to clinical use is recommended. Data loggers with specifically developed algorithms have been suggested as an additional tool in PTS evaluation. We compared two different data loggers. Methods Transport types – courier, conventional (cPTS) and innovative PTS (iPTS) – were monitored using two data loggers (MSR145 ® logger, CiK Solutions GmbH, Karlsruhe, Germany, and a prototype developed at the University Medicine Greifswald). Data loggers differ in algorithm, recording frequencies and limit of acceleration detection. Samples from apparently healthy volunteers were split among the transport types and results for 37 laboratory measurands were compared. Results For each logger specific arbitrary units were calculated. Area-under-the-curve (AUC)-values (MSR145 ® ) were lowest for courier and highest for iPTS and increased with increasing recording frequencies. Stress (St)-values (prototype logger) were obtained in kmsu (1,000*mechanical stress unit) and were highest for iPTS as well. Statistical differences between laboratory measurement results of transport types were observed for three measurands sensitive for hemolysis. Conclusions The statistical, but not clinical, differences in the results for hemolysis sensitive measurands may be regarded as an early sign of preanalytical impairment. Both data loggers record this important interval of beginning mechanical stress with a high resolution indicating their potential to facilitate early detection of preanalytical impairment. Further studies should identify suitable recording frequencies. Currently, evaluation and monitoring of diagnostic sample transport should not only rely on data loggers but also include diagnostic samples.

Objectives Quantitative human chorionic gonadotropin (hCG) measurements are used to manage women classified with a pregnancy of unknown location (PUL). Two point of care testing (POCT) devices that quantify hCG are commercially available. We verified the i-STAT 1 (Abbott) and the AQT 90 FLEX (Radiometer) prior to use in PUL triage. Methods Tests for precision, external quality assurance (EQA), correlation, hook effect and recovery were undertaken alongside a POCT usability assessment during this prospective multi-center verification. Results Coefficients of variation ranged between 4.0 and 5.1 % for the three i-STAT 1 internal quality control (IQC) solutions and between 6.8 and 7.3 % for the two AQT IQC solutions. Symmetric differences in POCT EQA results when compared with laboratory and EQA stock values ranged between 3.2 and 24.5 % for the i-STAT 1 and between 3.3 and 36.9 % for the AQT. Correlation coefficients (i-STAT 1: 0.96, AQT: 0.99) and goodness of fit curves (i-STAT 1: 0.92, AQT: 0.99) were excellent when using suitable whole blood samples. An hCG hook effect was noted with the i-STAT 1 between 572,194 and 799,089 IU/L, lower than the hook effect noted with the AQT, which was between 799,089 and 1,619,309 IU/L. When hematocrit concentration was considered in sample types validated for use with each device, hCG recovery was 108 % with the i-STAT 1 and 98 % with the AQT. The i-STAT 1 scored lower on usability overall (90/130) than the AQT (121/130, p<0.001, Mann-Whitney). Conclusions Both hCG POCT devices were verified for use in clinical practice. Practical factors must also be considered when choosing which device to use in each unit.

Objectives Tissue transglutaminase (tTG) IgA antibodies are a hallmark for celiac disease (CD). In CD patients on gluten free diet (GFD) these antibodies are transient. Few studies are available comparing the tTG-IgA assay characteristics for monitoring response to GFD. Since discrepant results were reported in patients on GFD after switching tTG-IgA assays, we conducted a retrospective observational study to monitor GFD response using three different tTG-IgA assays. Methods Diagnostic samples from 44 adults and 17 children with CD were included. Of most patients two follow-up samples after introduction of GFD were available. In all samples tTG-IgA were assessed using one fluorochrome-enzyme immuno-assay (FEIA) and two chemiluminescence immuno-assays (CLIA) and intestinal fatty acid binding protein (i-FABP) as surrogate marker for intestinal epithelial damage was measured. Results Using CLIA assays, normalization of antibody levels was delayed compared to FEIA (p<0.001). Of all samples taken after at least 6 months on GFD with elevated i-FABP indicating intestinal epithelial damage, 40 % had positive tTG-IgA according to the FEIA, 85 and 90 % according to the two CLIA. Conclusions Normalization of tTG-IgA in patients on GFD depends on the assay used. Both CLIA appear to be more sensitive in detecting suboptimal treatment response in CD-indicated by elevated i-FABP – when applying the manufacturer’s recommended cut-off for the diagnosis of CD.

Objectives Antineutrophil cytoplasmic antibody (ANCA) testing assists clinicians diagnose ANCA-associated vasculitis (AAV). We aimed to verify and harmonize chemiluminescent immunoassays for the detection of myeloperoxidase (MPO)- and proteinase 3 (PR3)-ANCA. Methods An in-house ELISA, a capture ELISA, and a chemiluminescent assay QUANTA Flash on a BIO-FLASH analyzer were used to detect MPO- and PR3-ANCA in sera from 39 patients with AAV, 55 patients with various non-AAV, and 66 patients with connective tissue diseases. The results of the assays were evaluated, and their clinical performance was assessed. The precision and linearity of the QUANTA Flash assays were determined, and likelihood ratios (LRs) for AAV at diagnosis were calculated. Results The precision and linearity of the QUANTA Flash assays were confirmed. Overall agreement between 97.5 and 98.8 % and Cohen’s kappa coefficients between 0.861 and 0.947 were observed for the results of the QUANTA Flash assays and ELISAs. The diagnostic sensitivity, specificity, and ROC analysis of the assays for AAV were statistically similar (in-house ELISA 89.7 %, 95.0 %, and 0.937; capture ELISA 92.3 %, 98.3 %, and 0.939; and QUANTA Flash 89.7 %, 95.9 %, and 0.972). For the QUANTA Flash assay results, the interval-specific LRs for AAV at diagnosis were: 0–8 CU had LR 0.08, 8–29 CU had LR 1.03, 29–121 CU had LR 7.76, 121–191 CU had LR 12.4, and >191 CU had LR ∞. Conclusions The QUANTA Flash MPO and PR3 assays provide precise and consistent results and have comparable clinical utility for AAV. The calculated LRs were consistent with published LRs, confirming the utility of LRs for harmonization of ANCA results.

Objectives Automated hematology analysis is expected to improve the performance of platelet counting. We evaluated the performance of a new platelet counting, hybrid (PLT-H) and also impedance (PLT-I) and optical (PLT-O) on the BC-780 automated hematology analyzer compared to the international reference method (IRM) in blood samples with thrombocytopenic and platelet interference. Methods The basic platelet count performance of the BC-780 automated hematology analyzer was evaluated according to the requirements of the Clinical Laboratory and Standards Institute (CLSI) Document H26-A2. Additionally, the thrombocytopenic (low PLT count) blood samples and the platelet interference blood samples including fragmented red blood cells (RBCs), microcytes or small RBCs, and giant platelets were determined with the BC-780 hematology analyzer compared to the IRM. Results Blank counting and the carry-over contamination rate of platelet count using the BC-780 both met the manufacturers’ claim. For both 123 thrombocytopenic and 232 platelet interference blood samples (72 fragmented RBCs, 91 microcytes and 51 giant platelets), all three platelet counting methods exhibited high comparability with the IRM (the lowest correlation (r)=0.916). Interestingly, the comparability of PLT-H (r=0.928–0.986) with the IRM was better than that of PLT-I (r=0.916–0.979). Conclusions The performance of PLT-H in the BC-780 met the manufacturer’s specifications. PLT-H exhibits better reproducibility than did PLT-I, correlates well with the PLT-O for thrombocytopenic samples and demonstrates good anti-interference ability. PLT-H counting is therefore recommended as a zero-cost alternative platelet counting method for platelet interference samples in clinical settings.

Objectives Blood biomarkers have the potential to transform diagnosis and prognosis for multiple neurological indications. Establishing normative data is a critical benchmark in the analytical validation process. Normative data are important in children as little is known about how brain development may impact potential biomarkers. The objective of this study is to generate pediatric reference intervals (RIs) for serum neurofilament light (NfL), an axonal marker, and glial fibrillary acidic protein (GFAP), an astrocytic marker. Methods Serum from healthy children and adolescents aged 1 to <19 years were obtained from the Canadian Laboratory Initiative on Pediatric Reference Intervals (CALIPER) cohort. Serum NfL (n=300) and GFAP (n=316) were quantified using Simoa technology, and discrete RI (2.5th and 97.5th percentiles) and continuous RI (5th and 95th percentiles) were generated. Results While there was no association with sex, there was a statistically significant (p<0.0001) negative association between age and serum NfL (Rho −0.400) and GFAP (Rho −0.749). Two statistically significant age partitions were generated for NfL: age 1 to <10 years (lower, upper limit; 3.13, 20.6 pg/mL) and 10 to <19 years (1.82, 7.44 pg/mL). For GFAP, three statistically significant age partitions were generated: age 1 to <3.5 years (80.4, 601 pg/mL); 3.5 to <11 years (50.7, 224 pg/mL); and 11 to <19 years (26.2, 119 pg/mL). Conclusions Taken together with the literature on adults, NfL and GFAP display U-shaped curves with high levels in infants, decreasing levels during childhood, a plateau during adolescence and early adulthood and increasing levels in seniors. These normative data are expected to inform future pediatric studies on the importance of age on neurological blood biomarkers.

Objectives The aims of this study were to determine the biological variation (BV), reference change value (RCV), index of individuality (II), and quality specifications for serum neopterin concentrations; a measurand provided by clinical laboratories as an indicator of cellular immunity. Methods The study delivered serum samples collected for 10 consecutive weeks from 12 apparently healthy individuals (3 male, 9 female). Serum neopterin concentrations were measured using high-performance liquid chromatography with fluorometric detection. The data analysis was performed using an online statistical tool and addressed published criteria for estimation of biological variation. Results The mean neopterin concentration was 5.26 nmol/L. The within-subject biological variation (CV I ) with 95 % confidence interval (CI) of neopterin serum concentrations was 11.54 % (9.98–13.59), and the between-subject biological variation (CV G ) with 95 % CI was 43.27 % (30.52–73.67). The neopterin asymmetrical RCV was −24.9 %/+33.1 %, and the II was 0.27. The desirable quality specifications for neopterin were <5.77 % for precision, <11.20 % for bias, and <20.72 % for total allowable error (TEa). When analytical variation was used instead of CV I to calculate TEa, the desirable TEa was <18.39. Conclusions This study determined BV data for neopterin, an indicator of cell-mediated immune response. Asymmetric RCV values, of 24.9 % decrease or a 33.1 % increase between consecutive measurements indicate significant change. The II of 0.27 indicates a high degree of individuality, therefore that it is appropriate to consider the use of personal reference data and significance of change rather than the reference interval as points of reference for the evaluation of neopterin serum concentrations.

Objectives Serum tryptase is a biomarker of mast cell activation. Among others, it is used in the diagnosis of anaphylaxis where a significant increase during the acute phase supports the diagnosis. When evaluating changes in biomarker levels, it is of utmost importance to consider the biological variation of the marker. Therefore, the aim of this study was to evaluate the short-term biological variation of serum tryptase. Methods Blood samples were drawn at 9 AM three days in a row from apparently healthy subjects. On day two, additional blood samples were drawn every third hour for 12 h. The tryptase concentration was measured in serum using a fluoroenzyme immunoassay (ImmunoCAP™, Thermo Fisher Scientific). Linear mixed-effects models were used to calculate components of biological variation. Results In 32 subjects, the overall mean concentration of tryptase was 4.0 ng/mL (range, 1.3–8.0 ng/mL). The within-subject variation was 3.7 % (95 % confidence interval (CI) 3.0–4.4 %), the between-subject variation was 31.5 % (95 % CI 23.1–39.8 %), and the analytical variation was 3.4 % (95 % CI 2.9–4.1 %). The reference change value was 13.3 % for an increase in tryptase at a 95 % level of significance. No significant day-to-day variation was observed (p=0.77), while a minute decrease in the serum concentration was observed during the day (p<0.0001). Conclusions Serum tryptase is a tightly regulated biomarker with very low within-subject variation, no significant day-to-day variation, and only minor semidiurnal variation. In contrast, a considerable between-subject variation exists. This establishes serum tryptase as a well-suited biomarker for monitoring.

Objectives Numerous studies have proven the potential of cytokeratin 19 fragment 21-1 (CYFRA 21-1) detection in the (early) diagnosis and treatment monitoring of non-small cell lung cancer (NSCLC). Conventional immunoassays for CYFRA 21-1 quantification are however prone to interferences and lack diagnostic sensitivity and standardization. Liquid chromatography-tandem mass spectrometry (LC-MS/MS) is an emerging approach based on a different, often superior, detection principle, which may improve the clinical applicability of CYFRA 21-1 in cancer diagnostics. Therefore, we developed and validated a protein precipitation, immunoaffinity (IA) LC-MS/MS assay for quantitative analysis of serum CYFRA 21-1. Methods Selective sample preparation was performed using ammonium sulfate (AS) precipitation, IA purification, tryptic digestion and LC-MS/MS quantification using a signature peptide and isotopically labeled internal standard. The workflow was optimized and validated according to EMA guidelines and results were compared to a conventional immunoassay. Results Significant interference effects were seen during IA purification, which were sufficiently solved by performing AS precipitation prior to IA purification. A linear calibration curve was obtained in the range of 1.0–100 ng/mL (R 2 =0.98). Accuracy and precision were well within acceptance criteria. In sera of patients suspected of lung cancer, the method showed good correlation with the immunoassay. Conclusions A robust AS precipitation-IA LC-MS/MS assay for the quantification of serum CYFRA 21-1 was developed. With this assay, the clinically added value of LC-MS/MS-based detection over immunoassays can be further explored.

Objectives Chronic myocardial injury (CMI) is defined as stable concentrations of cardiac troponin T or I (cTnT or cTnI) above the assay-specific 99th percentile upper reference limit (URL) and signals poor outcome. The clinical implications of diagnosing CMI are unclear. We aimed to assess prevalence and association of CMI with long-term prognosis using three different high-sensitivity cTn (hs-cTn) assays. Methods A total of 1,292 hospitalized patients without acute myocardial injury had cTn concentrations quantified by hs-cTn assays by Roche Diagnostics, Abbott Diagnostics and Siemens Healthineers. The median follow-up time was 4.1 years. The prevalence of CMI and hazard ratios for mortality and cardiovascular (CV) events were calculated based on the URL provided by the manufacturers and compared to the prognostic accuracy when lower percentiles of cTn (97.5, 95 or 90), limit of detection or the estimated bioequivalent concentrations between assays were used as cutoff values. Results There was no major difference in prognostic accuracy between cTnT and cTnI analyzed as continuous variables. The correlation between cTnT and cTnI was high (r=0.724–0.785), but the cTnT assay diagnosed 3.9–4.5 times more patients with having CMI based on the sex-specific URLs (TnT, n=207; TnI Abbott, n=46, TnI Siemens, n=53) and had higher clinical sensitivity and AUC at the URL. Conclusions The prevalence of CMI is highly assay-dependent. cTnT and cTnI have similar prognostic accuracy for mortality or CV events when measured as continuous variables. However, a CMI diagnosis according to cTnT has higher prognostic accuracy compared to a CMI diagnosis according to cTnI.

Objectives The biomarker N-terminal pro B-type natriuretic peptide (NT-proBNP) has predictive value for identifying individuals at risk for cardiovascular disease (CVD). However, it is not widely used for screening in the general population, potentially due to financial and operational reasons. This study aims to develop a deep-learning model as an efficient means to reliably identify individuals at risk for CVD by predicting serum levels of NT-proBNP from the ECG. Methods A deep convolutional neural network was developed using the population-based cohort study Hamburg City Health Study (HCHS, n=8,253, 50.9 % women). External validation was performed in two independent population-based cohorts (SHIP-START, n=3,002, 52.1 % women, and SHIP-TREND, n=3,819, 51.2 % women). Assessment of model performance was conducted using Pearson correlation (R) and area under the receiver operating characteristics curve (AUROC). Results NT-proBNP was predictable from the ECG (R, 0.566 [HCHS], 0.642 [SHIP-START-0], 0.655 [SHIP-TREND-0]). Across cohorts, predicted NT-proBNP (pNT-proBNP) showed good discriminatory ability for prevalent and incident heart failure (HF) (baseline: AUROC 0.795 [HCHS], 0.816 [SHIP-START-0], 0.783 [SHIP-TREND-0]; first follow-up: 0.669 [SHIP-START-1, 5 years], 0.689 [SHIP-TREND-1, 7.3 years]), comparable to the discriminatory value of measured NT-proBNP. pNT-proBNP also demonstrated comparable results for other incident CVD, including atrial fibrillation, stroke, myocardial infarction, and cardiovascular death. Conclusions Deep learning ECG algorithms can predict NT-proBNP concentrations with high diagnostic and predictive value for HF and other major CVD and may be used in the community to identify individuals at risk. Long-standing experience with NT-proBNP can increase acceptance of such deep learning models in clinical practice.

Objectives The escalating prevalence of diabetes worldwide has resulted in a dramatic increase in the number of people who need testing, which in turn necessitates faster HbA 1c measurement. The Tosoh GR01 addresses the need for fast turnaround times of whilst offering pragmatic steps to maintain result accuracy in a single instrument by offering two distinct operating modes: Short Mode (SM) and Long Mode (LM). The aim of this study was to evaluate all relevant aspects of the performance of the Tosoh GR01 with a view to accepting the instrument as a future Secondary Reference Measurement Procedure (SRMP) for the IFCC. Methods Certified Clinical & Laboratory Standards Institute (CLSI) Evaluation Protocols (EP) were used to evaluate precision (EP-5), accuracy (EP-9), linearity (EP-6), carry-over (EP-10) and the effect of hemoglobin variants and other potential interferences. Results Both modes demonstrated CVs <0.6 % in SI units and <0.4 % in NGSP units at 46 mmol/mol (6.4 %) and 75 mmol/mol (9.0 %) and passed both National Glycohemoglobin Standardization Program (NGSP) and International Federation of Clinical Chemistry and Laboratory Medicine (IFCC) certification procedures when compared with 7 IFCC Certified Secondary Reference Measurement Procedures (SRMP). Sigma for both modes was >6 when using the results of EP-5 and EP-9 at an HbA 1c concentration of 50 mmol/mol (6.7 %). Neither mode showed any interference with common Hb-variants except for HbAE when HbA 1c was >65 mmol/mol. In the SM HbAS, HbAD and HbAC were recognized but no result was reported. Conclusions There is a good balance between speed and accuracy for determining HbA 1c with the Tosoh GR01 in both analytical modes and the device is suitable for use as an IFCC SRMP.

Objectives Estimates of glucose concentrations vary among types of blood samples, which impact on the assessment of diabetes prevalence. Guidelines recommend a conversion factor to calculate plasma glucose from measurements of glucose in whole blood. The American Diabetes Association recommends the use of blood drawing tubes containing sodium fluoride (NaF) and citrate, which have not yet been evaluated regarding possible differences in glucose concentration and conversion factors. Thus, we compared glucose measurements in NaF-citrate plasma and venous whole blood and estimated the impact of differences on diabetes and prediabetes prevalence. Methods Glucose differences were calculated by Bland-Altman analysis with pairwise comparison of glucose measurements from whole blood and NaF-citrate plasma (n=578) in clinical studies of the German Diabetes Center. Subsequently, we computed the impact of the glucose difference on diabetes and prediabetes prevalence in the population-based National Health and Nutrition Examination Survey (NHANES). Results Even upon conversion of whole blood to plasma glucose concentrations using the recommended conversion factor, mean glucose concentration difference remained 4.72 % higher in NaF-citrate plasma. Applying the higher glucose estimates, increases the population-based diabetes and prediabetes prevalence by 13.67 and 33.97 % or more than 7.2 and 13 million people in NHANES, respectively. Additional economic burden could be about 20 $ billion per year due to undiagnosed diabetes. Conclusions The recommended conversion factor is not valid for NaF-citrate plasma. Systematic bias of glucose measurements due to sampling type leads to clinically relevant higher estimates of diabetes and prediabetes prevalence.

Objectives The stratification of individuals suffering from acute and post-acute SARS-CoV-2 infection remains a critical challenge. Notably, biomarkers able to specifically monitor viral progression, providing details about patient clinical status, are still not available. Herein, quantitative metabolomics is progressively recognized as a useful tool to describe the consequences of virus-host interactions considering also clinical metadata. Methods The present study characterized the urinary metabolic profile of 243 infected individuals by quantitative nuclear magnetic resonance (NMR) spectroscopy and liquid chromatography mass spectrometry (LC–MS). Results were compared with a historical cohort of noninfected subjects. Moreover, we assessed the concentration of recently identified antiviral nucleosides and their association with other metabolites and clinical data. Results Urinary metabolomics can stratify patients into classes of disease severity, with a discrimination ability comparable to that of clinical biomarkers. Kynurenines showed the highest fold change in clinically-deteriorated patients and higher-risk subjects. Unique metabolite clusters were also generated based on age, sex, and body mass index (BMI). Changes in the concentration of antiviral nucleosides were associated with either other metabolites or clinical variables. Increased kynurenines and reduced trigonelline excretion indicated a disrupted nicotinamide adenine nucleotide (NAD + ) and sirtuin 1 (SIRT1) pathway. Conclusions Our results confirm the potential of urinary metabolomics for noninvasive diagnostic/prognostic screening and show that the antiviral nucleosides could represent novel biomarkers linking viral load, immune response, and metabolism. Moreover, we established for the first time a casual link between kynurenine accumulation and deranged NAD + /SIRT1, offering a novel mechanism through which SARS-CoV-2 manipulates host physiology.