Volume 61, Issue 3

Objectives Measurement of high-sensitivity (hs) cardiac troponin (cTn) T and I is widely studied for cardiac assessment of stable populations. Recent data suggest clinical and prognostic discrepancies between both hs-cTn. We aimed at reviewing published studies with respect to underlying causes and clinical implications. Content We summarized current evidence on release and clearance mechanisms of cTnT and I, and on preanalytical and assay-related issues potentially portending to differences in measured concentrations. We also performed a systematic review of outcome studies comparing both hs-cTn in the general population, patients with congestive heart failure, stable coronary artery disease and atrial fibrillation. Summary and outlook For the interpretation of concentrations of hs-cTnT, stronger association with renal dysfunction compared to hs-cTnI should be considered. Hs-cTnT also appears to be a stronger indicator of general cardiovascular morbidity and all-cause mortality. Hs-cTnI concentrations tend to be more sensitive to coronary artery disease and ischemic outcomes. These findings apparently reflect variations in the mechanisms of cardiac affections resulting in cTn release. Whether these differences are of clinically relevance remains to be elucidated. However, having the option of choosing between either hs-cTn might represent an option for framing individualized cardiac assessment in the future.

Introduction Some laboratory testing practices may be of low value, leading to wasted resources and potential patient harm. Our scoping review investigated factors and processes that developers report using to inform decisions about what tests to target for practice improvement. Methods We searched Medline on May 30th, 2019 and June 28th, 2021 and included guidelines, recommendation statements, or empirical studies related to test ordering practices. Studies were included if they were conducted in a tertiary care setting, reported making a choice about a specific test requiring intervention, and reported at least one factor informing that choice. We extracted descriptive details, tests chosen, processes used to make the choice, and factors guiding test choice. Results From 114 eligible studies, we identified 30 factors related to test choice including clinical value, cost, prevalence of test, quality of test, and actionability of test results. We identified nine different processes used to inform decisions regarding where to spend intervention resources. Conclusions Intervention developers face difficult choices when deciding where to put scarce resources intended to improve test utilization. Factors and processes identified here can be used to inform a framework to help intervention developers make choices relevant to improving testing practices.

Reference intervals are established either by direct or indirect approaches. Whereas the definition of direct is well established, the definition of indirect is still a matter of debate. In this paper, a general definition that covers all indirect models presently in use is proposed. With the upcoming popularity of indirect models, it has become evident that further partitioning strategies are required to minimize the risk of patients’ false classifications. With indirect methods, such partitions are much easier to execute than with direct methods. The authors believe that the future of reference interval estimation belongs to indirect models with big data pools either from one laboratory or combined from several regional centres (if necessary). Independent of the approach applied, the quality assurance of the pre-analytical and analytical phase, considering biological variables and other confounding factors, is essential.

In Japan, a national antimicrobial resistance (AMR) action plan was adopted in 2016, advocating a 20% reduction in antibiotic consumption by 2020. However, there is still room for improvement to accomplish this goal. Many randomized controlled trials have reported that procalcitonin (PCT)-guided antimicrobial therapy could help to reduce antibiotic consumption without negative health effects, specifically in acute respiratory infections. In September 2018, some experts in Europe and the USA proposed algorithms for PCT-guided antimicrobial therapy in mild to moderate infection cases outside the ICU and severe cases in the ICU (the international experts consensus). Thereafter, a group of Japanese experts, including specialists in intensive care medicine, emergency medicine, respiratory medicine and infectious diseases, created a modified version of a PCT-guided algorithm (Japanese experts consensus). This modified algorithm was adapted to better fit Japanese medical circumstances, since PCT-guided therapy is not widely used in daily clinical practice in Japan. The Japanese algorithm has three specific characteristics. First, the target patients are limited to only hospitalized ICU or non-ICU patients. Second, pneumonia due to Pseudomonas aeruginosa , Staphylococcus aureus and Legionella species are excluded. Finally, a different timing of PCT follow-up measurement was proposed to meet restrictions of the Japanese medical insurance system. The adapted algorithms has high potential to further improve the safe reduction in antibiotic consumption in Japan, while reducing the spread of AMR pathogens.

Objectives Inappropriate use of laboratory testing remains a challenging problem worldwide. Minimum retest intervals (MRI) are used to reduce inappropriate laboratory testing. However, their effectiveness and the usefulness in reducing inappropriate laboratory testing is still a matter of debate. The aim of this study was to evaluate the effectiveness of broadly implemented MRIs as a means of reducing inappropriate laboratory test requests. Methods We performed a retrospective study in a general care and teaching hospital in the Netherlands, where MRI alerts have been implemented as standard care since June 7th 2017. Clinical chemistry test orders in adult internal medicine patients placed between July 13th 2017 and December 31st 2019 were included. The primary outcome was the effectiveness of MRIs, expressed as percentages of tests ordered and barred as a result of MRIs. Results Of a total of 218,511 test requests, 4,159 (1.90%) got an MRI alert. These MRIs were overruled by physicians in 21.76% of the cases. As a result of implementing MRIs, 3,254 (1.49%) tests were barred. The financial savings for the department of internal medicine directly related to the included barred laboratory tests during this period were 11,880 euros on a total amount of 636,598 euros for all performed tests. Conclusions Only a small proportion of laboratory tests are barred after implementation of MRIs, with a limited impact on the annual costs. However, MRIs provide a continuous reminder to focus on appropriate testing and the effectiveness of MRIs is potentially higher than described in this study.

Objectives Accurate prothrombin time international normalized ratio (INR) results are essential for safe anticoagulation treatment. Patients are treated both in primary and secondary healthcare, therefore equivalence of INR results from point-of-care (POC) and hospital measurement procedures (MPs) are important. It is not possible to evaluate this equivalence in traditional external quality assessment (EQA). The aim of this paper is to describe a special quality assurance system consisting of three different EQA schemes to monitor the harmonization of INR results in Norway. Methods The EQA scheme for hospital laboratories uses commutable control materials and evaluates participant performance and the equivalence of hospital MPs. The EQA scheme for primary healthcare laboratories uses non-commutable control materials and evaluates participant performance. A third EQA scheme for selected primary healthcare laboratories uses native patient split samples and evaluates the equivalence between POC and hospital MPs. Results The relationship between the three EQA schemes is presented. The split sample EQA scheme provides a link between the hospital scheme and the scheme for primary healthcare. Results from 2017 to 2022 are presented for all three schemes. When aberrant EQA results occur Noklus takes actions to be able to have a sustainable equivalence between INR results. Conclusions All three EQA schemes are important for monitoring the harmonization of INR results in Norway. This quality assurance system, including help and guidance of the participants, will reduce the risk of harm to patients due to non-equivalence of results from different MPs.

Objectives Alpha-1 antitrypsin (A1AT) deficiency was first identified in patients with emphysema by the absence of the α 1 band on serum protein electrophoresis (SPE). Today, capillary zone electrophoresis is widely performed in laboratories. Here, we compared two SPE systems to detect decreased A1AT concentrations to optimize their use as a screening tool for A1AT deficiency. Methods Serum protein electrophoresis was performed on 200 samples on the Capillarys 2 and the V8 Nexus. The latter presents two α 1 bands (α 1 band 1 and 2) while the Capillarys 2 has only one (Capillarys 2 total α 1 ). The measures of A1AT and α 1 acid glycoprotein (AAG) were performed as well as the phenotyping of M, S and Z alleles. Results At a A1AT cutoff of 0.80 g/L, a cutoff of 1.21 g/L using the V8 Nexus α 1 band 2 corresponded to a 100% sensitivity and a 92.4% specificity while a 1.69% cutoff corresponded to a 100% sensitivity and a 92.4% specificity. The performance of the α 1 band 1 was suboptimal and rather corresponded to AAG. On the Capillarys 2, a cutoff of 2.0 g/L corresponded to a 75.0% sensitivity and a 86.6% specificity, while a 3.2% cutoff showed a 96.4% sensitivity and a 67.4% specificity. The V8 Nexus α 1 band 2 was the method the most correlated with A1AT (r=0.90–0.94). Conclusions The V8 Nexus α 1 band 2 was the best predictor of A1AT deficiency, probably owing to a better resolution. The use of SPE was however unable to predict each phenotype. Phenotype or genotype studies are therefore still advisable in case of A1AT deficiency.

Objectives Antinuclear antibodies (ANAs) are associated with several autoimmune diseases. Indirect immunofluorescence (IIF) on human epithelial type 2 (HEp-2) cells is the golden standard for ANA detection in the clinic. In case of a positive HEp-2 IIF test result, follow-up tests are done to determine autoantibody specificity. For a fraction of the HEp-2 IIF-positive samples, the nature of the autoantigens remains uncharacterized. Our objective was to characterize autoantigens in such samples. Methods To characterize autoantigens in an unbiased way, we combined protein immunoprecipitation with liquid chromatography (LC) tandem mass spectrometry (MS/MS) sequencing. Results Using such approach we detected the Ki antigen, also referred to as PA28γ, in the immunoprecipitate of serum samples of three individuals with an autoimmune disease. The HEp-2 nuclear speckled IIF fluorescent signal of all three serum samples was abolished after pre-absorption of the serum with recombinant Ki antigen, confirming that autoantibodies against Ki underlie the HEp-2 IIF signal. Conclusions Our data suggest that anti-Ki autoantibodies can underlie a nuclear speckled HEp-2 IIF pattern.

Objectives In this study we describe the development and validation of a liquid chromatography mass spectrometry method (LC-MS/MS) to quantify five tryptophan (TRP) metabolites within the kynurenine– and serotonin pathway and apply the method to serum samples of women in the first trimester of pregnancy. A secondary aim was to investigate the correlation between body mass index (BMI) and the five analytes. Methods A LC-MS/MS was developed for the analysis of TRP, kynurenine (KYN), 5-hydroxytryptophan (5-HTP), hydroxytryptamine (5-HT), and 5-hydroxyindole acetic acid (5-HIAA). Serum samples (n=374) were analyzed of pregnant women (median gestational age: 8 ± 2 weeks) participating in a subcohort of the Rotterdam Periconceptional Cohort (Predict study). Results The LC-MS/MS method provided satisfactory separation of the five analytes (7 min run). For all analytes R 2 was >0.995. Within- and between-run accuracies were 72–97% and 79–104%, and the precisions were all <15% except for the between-run precisions of the low QC-samples of 5-HTP and 5-HT (both 16%). Analyte concentrations were determined in serum samples of pregnant women (median (IQR)); TRP (µmol/L): 57.5 (13.4), KYN (µmol/L): 1.4 (0.4), 5-HTP (nmol/L): 4.1 (1.2), 5-HT (nmol/L): 615 (323.1), and 5-HIAA (nmol/L): 39.9 (17.0). BMI was negatively correlated with TRP, 5-HTP, and 5-HIAA (TRP: r=−0.18, p<0.001; 5-HTP: r=−0.13, p=0.02; natural log of 5-HIAA: r=−0.11, p=0.04), and positively with KYN (r=0.11, p=0.04). Conclusions The LC-MS/MS method is able to accurately quantify kynurenine– and serotonin pathway metabolites in pregnant women, providing an opportunity to investigate the role of the TRP metabolism in the (patho)physiology of pregnancy.

Objectives Conventionally, reference intervals are established by direct methods, which require a well-characterized, obviously healthy study population. This elaborate approach is time consuming, costly and has rarely been applied to steroid hormones measured by mass spectrometry. In this feasibility study, we investigate whether indirect methods based on routine laboratory results can be used to verify reference intervals from external sources. Methods A total of 11,259 serum samples were used to quantify 13 steroid hormones by mass spectrometry. For indirect estimation of reference intervals, we applied a “modified Hoffmann approach”, and verified the results with a more sophisticated statistical method (refineR). We compared our results with those of four recent studies using direct approaches. Results We evaluated a total of 81 sex- and age-specific reference intervals, for which at least 120 measurements were available. The overall agreement between indirectly and directly determined reference intervals was surprisingly good as nearly every fourth reference limit could be confirmed by narrow tolerance limits. Furthermore, lower reference limits could be provided for some low concentrated hormones by the indirect method. In cases of substantial deviations, our results matched the underlying data better than reference intervals from external studies. Conclusions Our study shows for the first time that indirect methods are a valuable tool to verify existing reference intervals for steroid hormones. A simple “modified Hoffmann approach” based on the general assumption of a normal or lognormal distribution model is sufficient for screening purposes, while the refineR algorithm may be used for a more detailed analysis.

Objectives Ovarian cancer is the most lethal gynecological malignancy in developed countries. One of the key associations with the high mortality rate is diagnosis at late stages. This clinical limitation is primarily due to a lack of distinct symptoms and detection at the early stages. The ovarian cancer biomarker, CA125, is mainly effective for identifying serous ovarian carcinomas, leaving a gap in non-serous ovarian cancer detection. Mucin 13 (MUC13) is a transmembrane, glycosylated protein with aberrant expression in malignancies, including ovarian cancer. We explored the potential of MUC13 to complement CA125 as an ovarian cancer biomarker, by evaluating its ability to discriminate serous and non-serous subtypes of ovarian cancer at FIGO stages I–IV from benign conditions. Methods We used our newly developed, high sensitivity ELISA to measure MUC13 protein in a large, well-defined cohort of 389 serum samples from patients with ovarian cancer and benign conditions. Results MUC13 and CA125 serum levels were elevated in malignant compared to benign cases (p<0.0001). Receiver-operating characteristic (ROC) curve analysis showed similar area under the curve (AUC) of 0.74 (MUC13) and 0.76 (CA125). MUC13 concentrations were significantly higher in mucinous adenocarcinomas compared to benign controls (p=0.0005), with AUC of 0.80. MUC13 and CA125 showed significant elevation in early-stage cases (stage I–II) in relation to benign controls (p=0.0012 and p=0.014, respectively). Conclusions We report the novel role of MUC13 as a serum ovarian cancer biomarker, where it could complement CA125 for detecting some subtypes of non-serous ovarian carcinoma and early-stage disease.

Objectives Due to lack of effective biomarkers for non-small cell lung cancer (NSCLC), many patients are diagnosed at an advanced stage, which leads to poor prognosis. Dysregulation of N6-methyladenosine (m 6 A) RNA contributes significantly to tumorigenesis and tumor progression. However, the diagnostic value of m 6 A RNA status in peripheral blood to screen NSCLC remains unclear. Methods Peripheral blood samples from 152 NSCLC patients and 64 normal controls (NCs) were applied to assess the m 6 A RNA levels. Bioinformatics and qRT-PCR analysis were performed to identify the specific immune cells in peripheral blood cells and investigate the mechanism of the alteration of m 6 A RNA levels. Results Robust elevation of m 6 A RNA levels of peripheral blood cells was exhibited in the NSCLC group. Moreover, the m 6 A levels increased as NSCLC progressed, and reduced after treatment. The m 6 A levels contained area under the curve (AUC) was 0.912, which was remarkably greater than the AUCs for CEA (0.740), CA125 (0.743), SCC (0.654), and Cyfra21-1 (0.730). Furthermore, the combination of these traditional biomarkers with m 6 A levels elevated the AUC to 0.970. Further analysis established that the expression of m 6 A erasers FTO and ALKBH5 were both markedly reduced and negatively correlated with m 6 A levels in peripheral blood of NSCLC. Additionally, GEO database and flow cytometry analysis implied that FTO and ALKBH5 attributes to peripheral CD4 + T cells proportion and activated the immune functions of T cells. Conclusions These findings unraveled that m 6 A RNA of peripheral blood immune cells was a prospective biomarker for the diagnosis of NSCLC.

Objectives The N-terminal fragment of pro-B-type natriuretic peptide (NT-proBNP) is a widely used heart failure (HF) biomarker. Commercial NT-proBNP immunoassays detect only a subfraction of endogenous NT-proBNP, as the antibodies target a region of NT-proBNP that could be glycosylated at Ser44. The diagnostic utility of immunoassays measuring total NT-proBNP remains unclear. Methods NT-proBNP was measured in 183 HF and 200 non-HF patients diagnosed by two independent cardiologists blinded to NT-proBNP results. Plasma samples either non-treated or treated with a mixture of glycosidases were analyzed by the Elecsys proBNP II assay (Roche Diagnostics, based on antibodies targeting a glycosylated region of NT-proBNP) and the SuperFlex NT-proBNP assay (PerkinElmer, based on antibodies targeting regions of NT-proBNP that are free of O-glycans). The diagnostic accuracy of the two assays was analyzed by comparison of ROC curves. Results The ROC-AUC for the proBNP II assay was 0.943 (95% CI 0.922–0.964) for NT-proBNP measured in untreated samples and 0.935 (0.913–0.958) for NT-proBNP measured in glycosidase-treated samples. The SuperFlex NT-proBNP assay in untreated samples gave a ROC-AUC of 0.930 (95% CI 0.907–0.954). The median percentage of non-glycosylated NT-proBNP to total NT-proBNP was 1.5–1.6-fold lower in the non-HF group compared to that in the HF group. Conclusions The clinical value of total NT-proBNP for HF diagnosis was similar to the subfraction of NT-proBNP that was non-glycosylated at Ser44. The lower percentage of non-glycosylated NT-proBNP to total NT-proBNP in non-HF patients suggests that total NT-proBNP might be more sensitive in individuals without current or prior symptoms of HF.

Objectives Circulating calprotectin (cCLP) has been shown to be a promising prognostic marker for COVID-19 severity. We aimed to investigate the prognostic value of serial measurements of cCLP in COVID-19 patients admitted to an intensive care unit (ICU). Methods From November 2020 to May 2021, patients with COVID-19, admitted at the ICU of the OLV Hospital, Aalst, Belgium, were prospectively included. For sixty-six (66) patients, blood samples were collected at admission and subsequently every 48 h during ICU stay. On every sample (total n=301), a cCLP (EliA™ Calprotectin 2, Phadia 200, Thermo Fisher Scientific; serum/plasma protocol (for Research Use Only, -RUO-) and C-reactive protein (CRP; cobas c501/c503, Roche Diagnostics) analysis were performed. Linear mixed models were used to associate biomarkers levels with mortality, need for mechanical ventilation, length of stay at ICU (LOS-ICU) and medication use (antibiotics, corticosteroids, antiviral and immune suppressant/modulatory drugs). Results Longitudinally higher levels of all biomarkers were associated with LOS-ICU and with the need for mechanical ventilation. Medication use and LOS-ICU were not associated with variations in cCLP and CRP levels. cCLP levels increased significantly during ICU hospitalization in the deceased group (n=21/66) but decreased in the non-deceased group (n=45/66). In contrast, CRP levels decreased non-significantly in both patient groups, although significantly longitudinally higher CRP levels were obtained in the deceased subgroup. Conclusions Serial measurements of cCLP provides prognostic information which can be useful to guide clinical management of COVID-19 patients in ICU setting.

Objectives We compared the performance of a new interferon gamma release assay (IGRA) format assay, the ichroma™ COVID-19 IGRA (IGRA-SARS), with that of the widely used QuantiFERON SARS-CoV-2 ELISA kit (QFN-SARS) in vaccinated healthcare workers (HCWs). Additionally, we analyzed the long-term changes in IGRA results after the final vaccine dose. Methods A total of 383 specimens from 281 HCWs were enrolled in this study, and the results of SARS-IGRA and QFN-SARS assays were compared. In addition, we performed the receive operator curve analysis to estimate the optimal cut-off value for IGRA-SARS. Results For all specimens, IGRA-SARS and QFN-SARS showed 75.7% and 64.2% of the positive results, respectively. The absolute agreement between IGRA-SARS and QFN-SARS was 80.0%, and the Fleiss’ κ value was 0.525, indicating moderate agreement. ROC curve analysis of the IGRA-SARS results showed a cut-off value of >0.254 IU/mL, which was consistent with the manufacturer’s specifications. The positive rates of both IGRA assays decreased significantly after a postvaccination period of 6 months. Conclusions IGRA-SARS showed acceptable performance in the detection of vaccine-induced immunity against COVID-19; however, harmonization of IGRA assays has not yet been achieved. Additionally, the significant decline of positive rates of IGRA after the last vaccination would support the necessity of booster vaccination after a postvaccination period of 6 months.

Objectives Various comorbidities associated with COVID-19 add up in severity of the disease and obviously prolonged the time for viral clearance. This study investigated a novel ultrasensitive MAGLUMI ® SARS-CoV-2 Ag chemiluminescent immunoassay assay (MAG-CLIA) for diagnosis and monitoring the infectivity of COVID-19 patients with comorbid conditions during the pandemic of 2022 Shanghai. Methods Analytical performances of the MAG-CLIA were evaluated, including precision, limit of quantitation, linearity and specificity. Nasopharyngeal specimens from 232 hospitalized patients who were SARS-CoV-2 RT-qPCR positive and from 477 healthy donors were included. The longitudinal studies were performed by monitoring antigen concentrations alongside with RT-qPCR results in 14 COVID-19 comorbid participants for up to 22 days. The critical antigen concentration in determining virus infectivity was evaluated at the reference cycle threshold (Ct) of 35. Results COVID-19 patients were well-identified using an optimal threshold of 0.64 ng/L antigen concentration, with sensitivity and specificity of 95.7% (95% CI: 92.2–97.9%) and 98.3% (95% CI: 96.7–99.3%), respectively, while the Wondfo LFT exhibited those of 34.9% (95% CI: 28.8–41.4%) and 100% (95% CI: 99.23–100%), respectively. The sensitivity of MAG-CLIA remained 91.46% (95% CI: 83.14–95.8%) for the samples with Ct values between 35 and 40. Close dynamic consistence was observed between MAG-CLIA and viral load time series in the longitudinal studies. The critical value of 8.82 ng/L antigen showed adequate sensitivity and specificity in evaluating the infectivity of hospitalized convalescent patients with comorbidities. Conclusions The MAG-CLIA SARS-CoV-2 Ag detection is an effective and alternative approach for rapid diagnosis and enables us to evaluate the infectivity of hospitalized convalescent patients with comorbidities.

Objectives Early recognition and timely intervention for urosepsis are key to reducing morbidity and mortality. Blood culture has low sensitivity, and a long turnaround time makes meeting the needs of clinical diagnosis difficult. This study aimed to use biomarkers to build a machine learning model for early prediction of urosepsis. Methods Through retrospective analysis, we screened 157 patients with urosepsis and 417 patients with urinary tract infection. Laboratory data of the study participants were collected, including data on biomarkers, such as procalcitonin, D-dimer, and C-reactive protein. We split the data into training (80%) and validation datasets (20%) and determined the average model prediction accuracy through cross-validation. Results In total, 26 variables were initially screened and 18 were statistically significant. The influence of the 18 variables was sorted using three ranking methods to further determine the best combination of variables. The Gini importance ranking method was found to be suitable for variable filtering. The accuracy rates of the six machine learning models in predicting urosepsis were all higher than 80%, and the performance of the artificial neural network (ANN) was the best among all. When the ANN included the eight biomarkers with the highest influence ranking, its model had the best prediction performance, with an accuracy rate of 92.9% and an area under the receiver operating characteristic curve of 0.946. Conclusions Urosepsis can be predicted using only the top eight biomarkers determined by the ranking method. This data-driven predictive model will enable clinicians to make quick and accurate diagnoses.