Volume 63, Issue 10

Artificial intelligence (AI) is rapidly transforming laboratory medicine, impacting medical devices and healthcare practices. Despite these advancements, AI-based medical device software (MDSW) introduces a new layer of complexity in regulatory compliance. This paper outlines the regulatory landscape for MDSW and AI-driven MDSW, clarifying the responsibilities of laboratory professionals and manufacturers under the In Vitro Diagnostic Regulation (IVDR), ISO 15189:2022, and the Artificial Intelligence Act. An analysis of 89 MDSWs approved under the IVDR, derived from the European Database on Medical Devices (EUDAMED) reveals a diverse landscape of applications, ranging from digital pathology and molecular diagnostics to laboratory automation and clinical decision support. While Germany currently dominates the EU market for these devices, and the majority of approved MDSW remain non-AI driven and classified as low-risk, the increasing presence of AI-powered Class C devices underscores the growing potential of software in complex diagnostic scenarios. However, realizing the full potential of AI in laboratory medicine requires careful navigation of the evolving regulatory landscape. Key challenges persist, including defining intended use, ensuring robust clinical evidence, mitigating data bias, and establishing rigorous post-market surveillance. Balancing regulatory oversight with innovation is critical to fostering the development of trustworthy AI systems without stifling progress. As regulatory frameworks continue to evolve, establishing clear validation methodologies and transparent compliance pathways will be essential to unlocking the full potential of AI in laboratory medicine while ensuring the highest standards of safety and clinical effectiveness.

The indirect immunofluorescence assay (IFA) on HEp-2 cells is the prevailing method used to screen for autoantibodies in the investigation of systemic autoimmune diseases (SAID). When positive, the titer provides a semi-quantitative assessment of the autoantibody serum concentration whereas the immunofluorescence pattern indicates the possible autoantibody specificities. The Brazilian Consensus on ANA Patterns (BCA) and the International Consensus on ANA Patterns (ICAP) provide recommendations for the harmonization on the pattern nomenclature and test reporting. Nuclear patterns are among the most frequent in the clinical laboratory and some of them are highly relevant in the diagnosis of SAID. Nuclear patterns with stained metaphase plate (MP) indicate autoantibodies against chromatin components or against chromatin-bound antigens. These include the nuclear homogeneous (AC-1), nuclear dense fine speckled (AC-2), Topo 1-like (AC-29), and nuclear fine speckled with stained MP (AC-30) patterns. The Brazilian consensus has also classified the quasi -homogeneous nuclear pattern (QH). The correct identification of these patterns is important because each one is associated with different autoantibody specificities and clinical scenarios. However, the recognition of the nuances in texture of the staining pattern and other specific features that characterize each of them may be challenging for the analyst at the microscope. This review focuses on the morphological characteristics, immunological identities, and clinical relevance of nuclear patterns with stained MP. The aim is to assist laboratory analysts and clinicians in identifying and interpreting these patterns, thus optimizing the use of the HEp-2 IFA test in the investigation of patients under suspicion of SAID.

Laboratory diagnostics play a crucial role in modern medicine and healthcare economics. The effective management of a medical laboratory is based on reliable assessment of indicators characterizing quality of testing, productivity, velocity (speed) and cost-effectiveness. The usual concepts of laboratory management focus on one or two groups of these indicators and exclude a comprehensive assessment of the effectiveness of a medical laboratory. Various guidelines and concepts (ISO, Lean, Six Sigma, etc.) often provide similar approaches but use different terms. This review discusses common options for performance indicators in medical laboratories, as well as practical experience in using these indicators to assess the overall effectiveness of the laboratory and improve medical care for patients. All indicators were divided into four broad groups: quality, economy, velocity, and productivity. Based on these four groups, we describe the new” four-dimensional model” for assessment of medical laboratory performance based on different combinations of indicator groups for different types of laboratories.

Cardiac injury, encompassing a spectrum of heart muscle damage, requires prompt and accurate diagnosis to improve patient outcomes. Early detection using cardiac biomarkers is vital for timely intervention and reducing mortality. This review highlights the role of high-sensitivity cardiac troponins (hs-cTns) in diagnosing cardiac injury. This article offers an overview of cardiac injury, including its causes, diagnostic challenges, and the evolution of biomarkers, up to the development and commercialization of “high-sensitivity” (hs-) cTns. The molecular structure of cardiac isoforms cTnI and cTnT, release kinetics, guidelines incorporation, diagnostic performance, and clinical application will be analyzed. It is concluded that the advent of hs-cTn assays has further expanded diagnostic capabilities by enabling the detection of low-level cTn elevations, which were previously undetectable using conventional methods. This enhanced sensitivity allows earlier identification of even minor cardiac injuries, facilitating prompt intervention and improving patient outcomes. However, this increased sensitivity also introduces interpretive challenges in understanding the nature of cardiac involvement, especially in distinguishing mild cTn elevations that may signify non-ischemic cardiac injury or be associated with other non-cardiac conditions.

Theranos was a biotechnology company which, in the 2010s, promised to revolutionize traditional clinical chemistry testing by using novel technology, microvolumes of blood obtained by finger pricks, and performance of tests outside traditional clinical chemistry laboratories, such as in pharmacies. Theranos did not publish any details of their technology, nor sought to evaluate it independently. Despite this, it attracted millions of dollars of investments, and at a point, its market valuation reached $9 billion. Around 2015 the Theranos business practices and technology were scrutinized and it was revealed that they misled investors, doctors, and patients by falsely claiming of using their own technology, when in fact, they were using traditional clinical chemistry analyzers. The leaders of Theranos are now serving prison time. This year it was announced that a new effort is underway, by people who are related to Theranos, to start a new company, with objectives that partially overlap with those of the old company. Here, we comment on these new developments, with the hope that the lessons learned from the past will guide the new leaders to find success while mentioning that some new developments in the field will likely pose formidable competition.

The sweat test is used as a biological marker of cystic fibrosis transmembrane conductance regulator (CFTR) dysfunction, but there is growing recognition that sweat chloride concentrations of people with cystic fibrosis (CF) can overlap with those without CF. There are also people without CF whose symptoms are caused by abnormalities of CFTR. To support clinical decisions, the sweat chloride test conducted appropriately should provide consistent results between laboratories and common decision limits should be used. International consensus guidelines now recommend a standard set of clinical decision limits for sweat chloride, with values between 30 and 59 mmol/L, as the intermediate result for all ages. It is therefore timely to update the Australasian guideline decision limits to align with international consensus guidelines and peak body recommendations. At the same time, the technical aspects for performance of the sweat chloride test should be reviewed. This paper updates (and replaces) the guideline for the performance of the sweat chloride test that were last published by the AACB in 2017. This freely available guideline was developed to support Australasian laboratories, and laboratories from other regions, with the accurate performance of sweat chloride testing. The guideline provides 16 recommendations for the performance of the sweat chloride test encompassing the total testing process. Previous recommendations related to sweat conductivity testing have been removed from this guideline. The sweat chloride decision limits of ≥30 mmol/L support a review by a CF physician for all age groups. Sweat chloride concentrations of ≥60 mmol/L are supportive of a diagnosis of CF.

Objectives Quality indicator (QI) monitoring is essential to quality assurance for point of care testing (POCT). QI standardization is needed in the POCT field to provide clear guidance to hospitals and produce National and International benchmarks. A central aim was to standardize POCT QIs with existing QIs of the MQI program recommended by the International Federation of Clinical Chemistry and Laboratory Medicine (IFCC) for central laboratory testing for integration in Comparison programs. Methods Process mapping and risk assessment of the POC glucose testing process were used to establish potential QI. Group consensus was used to rank each potential QI based on the ability to retrieve data for the specific QI. Higher scores were attributed to QI where data could be retrieved electronically and automatically. The highest scoring QI were chosen for follow-up. Members of the working group (authors) were asked to submit data from their own institutions for each QI to evaluate the feasibility of monitoring each QI and to develop preliminary benchmarks. Results Five QI recommendations are provided for glucose POCT, including: positive patient identification, operator training, internal quality control monitoring, external quality assessment and critical results follow-up. Preliminary QI data are presented along with implementation strategies and challenges associated with each recommended QI. Conclusions This study builds upon previous work by the Canadian Society of Clinical Chemists in developing a process to establish QIs for POCT based on process mapping and risk assessment. The recommended QIs are applicable to most other types of POCT, in addition to glucose testing.

Objectives Anti-nuclear antibodies (ANA) testing on indirect immunofluorescence (IIF) has been for a long time the gold standard assay in the diagnosis of rheumatic diseases; more recently different solid phase assays (SPA) have been recommended to increase specificity of positive results. The best combination of the different assays should both reduce the time to diagnosis and the costs of testing. Methods Serum samples from 995 unselected outpatients were analysed simultaneously using IIF and a fluorescent enzyme SPA as initial screening test. Any IIF or SPA positive sample was further analysed for individual antibody specificities and three algorithm models with different timelines were adopted. The cost-effectiveness assessment was performed by calculating the total number of positive patients and the cost of diagnosis for each algorithm. Results IIF and SPA were both positive in 112 (11.3 %) patients, and both negative in 597 (60 %) patients; 257 results (25.8 %) were conflicting between the two methods. The three algorithms resulted in a different number of positive patients and had a different cost per single diagnosis: the combined algorithm revealed the highest number of positive patients with a lower cost per diagnosis than the traditional one. Conclusions The combined approach of two different methods ensures the highest reliability of ANA screening test; however, specific appropriate SPA testing might be chosen according to IIF pattern as recommended in International guidelines. Each clinical laboratory should carefully evaluate its diagnostic algorithm for ANA testing on the volume and type of requests, eventually designing new cost-effective reimbursement models based on patients outcomes.

Objectives Accurate 25-hydroxyvitamin D (25-(OH)D) assays are essential for defining vitamin D status and ensuring appropriate clinical decisions. Standardization efforts, including the Vitamin D Standardization Program (VDSP), aim to minimize assay variability. This study evaluates the measurement uncertainty (MU) of various 25-(OH)D assays and their ability to detect physiologically relevant changes over time. Methods Seventeen pooled and eight single-donor serum samples were analyzed using two LC-MS/MS methods and 13 immunoassays, each applied in two independent laboratories. Imprecision, bias, and MU were assessed relative to the University of Ghent’s reference measurement procedure (RMP). Results were compared against analytical performance specifications (APS) from VDSP, JCTLM-TF-RMSI, and IFCC C-BM based on physiological 25-(OH)D variation. A graphical approach was introduced to visualize MU in relation to clinical relevance. Results LC-MS/MS methods consistently met all APS criteria. Several immunoassays also achieved acceptable MU, although significant bias or inter-laboratory variability was observed for some of them. Slightly more than half of the assays met the desirable Joint Committee for Traceability in Laboratory Medicine Task Force on Reference Measurement System Implementation (JCTLM TF-RMSI) MU threshold (≤10 %), while four exceeded the minimum acceptable limit (≤15 %). The IFCC C-BM physiological approach identified a similar subset of assays. The graphical representation effectively illustrated method reliability across the tested concentration range. Conclusions Measurement uncertainty remains a major challenge for 25-(OH)D assays. The integration of MU-based APS and graphical visualization provides a comprehensive framework for evaluating assay performance. These findings highlight the importance of selecting assays capable of reliably detecting clinically meaningful changes in vitamin D status.

Objectives Copeptin, a stable and simple-to-measure surrogate marker for arginine vasopressin (AVP), demonstrates excellent clinical values, particularly in diagnosing polyuria-polydipsia syndromes. However, conventional immunoassay methods are limited and lack comparability. Our aim was to establish a targeted liquid chromatography-tandem mass spectrometry (LC-MS/MS) method for quantifying copeptin in human serum. Methods Copeptin was extracted from serum using immunoprecipitation, digested with trypsin, and prepared using anion exchange solid-phase extraction before LC-MS/MS detection. The analytical performance was validated in accordance with current guidelines. The method was compared to an immunofluorescent assay on the B.R.A.H.M.S platform. Results The LC-MS/MS method had a runtime of 8.5 min. The within-run precision ranged from 5.2 to 12.1 %, and total coefficients of variation ranged from 8.1 to 13.5 %. Copeptin quantitation showed linearity within the range of 5–1,000 pg/mL, with a limit of detection of 2.5 pg/mL. Recovery rates ranged from 95.2 to 103.1 %, and no significant matrix effect was observed with internal standard correction. The LC-MS/MS method had a good consistency with the immunoassay (r=0.926, slope=0.989). The reference interval for healthy individuals was 3.66–58.25 pg/mL. Conclusions We demonstrated the accuracy and reliability of this targeted LC-MS/MS method for quantifying copeptin. This innovative application showed satisfactory precision, a wide linear range, and a low limit of detection. Clinical studies are anticipated to be conducted to assess diagnostic accuracy using this method.

Objectives Histamine, mainly produced in mast cells (MC), plays a key role in allergy and inflammation. Measuring its urinary metabolites, N-methylhistamine (NMH) and 1-methyl-4-imidazoleacetic acid (MIMA), is essential in assessing histamine-related pathologies. Patients with concurrent systemic mastocytosis (SM) and hereditary alpha tryptasemia (HαT) may show increased MC mediator-related symptom severity. We developed and validated a liquid chromatography-tandem mass spectrometry (LC-MS/MS) assay to quantify histamine, NMH, and MIMA, and explored their correlation with basal serum tryptase (BST) levels. Methods Using an in-matrix double derivatization, enhancing extraction, we analyzed urinary histamine, NMH, and MIMA with an online solid-phase extraction LC-MS/MS system. Analytical method validation assessed recovery, imprecision, and detection limits. For clinical validation, correlation analysis between BST levels, NMH, and MIMA in SM and HαT patients was performed. Results The assay demonstrated recoveries>98 %, imprecision<3 %, and limits of quantification at 2.0 nmol/L for histamine, 0.53 nmol/L for NMH, and 0.011 μmol/L for MIMA. Patients with a combination of SM and HαT showed a 2.6–3.6 fold increase in BST compared to those with SM alone. A BST/NMH ratio>0.129 predicted HαT with 91.3 % sensitivity and 85.6 % specificity, and a BST/MIMA ratio>7.46 predicted HαT with 89.9 % sensitivity and 86.0 % specificity, independent of SM status. Conclusions Our LC-MS/MS method provides highly accurate and efficient quantification of histamine, NMH, and MIMA. Integrating BST/NMH and BST/MIMA ratios in diagnostic protocols enhances detection of HαT in MC-related disorders, supporting improved diagnostics and tailored patient management.

Objectives This study aimed to develop and validate a machine learning (ML) model utilizing cerebrospinal fluid (CSF) body fluid parameters from hematology analyzers to screen for malignant cells. Methods We analyzed 643 consecutive CSF samples from patients with central nervous system symptoms, with 191 samples classified as positive for malignant cells based on cytological examination, for model derivation. Body fluid parameters were measured using the body fluid mode of a hematology analyzer. Least Absolute Shrinkage and Selection Operator (LASSO) regression was applied to identify predictive biomarkers, followed by performance evaluations of six ML algorithms. Model interpretability was assessed using SHapley Additive exPlanations (SHAP). The selected model was also externally validated with an additional 136 CSF samples. Results The median leukocyte (WBC) and total nucleated cell (TNC) counts in the cytology-positive samples were significantly lower than those in the cytology-negative samples (5.4 vs. 31.8 and 7.4 vs. 32.6, respectively, p<0.001). The support vector machine (SVM) model achieved the highest area under the curve (AUC) of 0.899 (SD: 0.035) and the highest sensitivity of 0.827 (SD: 0.059) in internal validation. SHAP analysis identified the percentage of high fluorescence cells and monocytes as the two most significant predictors, both positively correlated with malignant cell outcomes. External validation demonstrated a comparable AUC and sensitivity, confirming the model’s generalizability. Conclusions We developed an ML model that predicts cytological outcomes in CSF using routinely available body fluid parameters. The model demonstrated consistent performance during external validation.

Objectives Machine learning (ML) models, using laboratory data, support early sepsis prediction. However, analytical bias in laboratory measurements can compromise their performance and validity in real-world settings. We aimed to evaluate how analytically acceptable bias may affect the validity and generalizability of ML models trained on laboratory data. Methods A support vector machine model (SVM) for sepsis prediction was developed using complete blood count and erythrocyte sedimentation rate data from outpatients (CS, n=104) and patients from acute inflammatory status wards (SS, n=107). Twenty-six combinations were derived by white blood cells (WBC), platelets (PLT), and erythrocyte sedimentation rate (ESR) biases from analytical performance specifications (APS). The diagnostic performances of the 26 conditions tested were compared to the original dataset. Results SVM performance of the original dataset was AUC 90.6 % [95 %CI: 80.6–98.7 %]. Minimum, desirable and optimum acceptable biases for WBC were 7.7 , 5.1 and 2.6 %, respectively, for PLT were 6.7 , 4.5 and 2.2 %, respectively and for ESR were 31.6 , 21.1 and 10.5 %, respectively. Across all conditions, AUC varied from 89.8 % [95 %CI: 79.0–97.7 %] (for PLT bias −6.7 %), to 89.5 % [95 %CI: 79.1–98.0 %] (for ESR Bias +31.6 %) to 90.4 % [95 %CI: 79.3–98.4 %] (for WBC Bias −5.1 %). Using a combination of biases, the lowest AUC was 87.8 % [95 %CI: 75.9–96.6 %]. No statistically significant differences were observed for AUC (p>0.05). Conclusions Bias can influence model performance depending on the parameters and their combinations. Developing new validation strategies to assess the impact of analytical bias on laboratory data in ML models could improve their reliability.

Objectives To evaluate the characteristics of an immunochemical urinary free light chains (uFLC) test in screening and quantifying Bence Jones proteinuria (BJP) and its potential application in laboratory practice as an alternative to the gold standard method, urine immunofixation (UIFE) and densitometric quantification on 24 h urine sample. Methods A total of 300 subjects were divided into five groups: controls, patients with BJP Kappa and Lambda present in trace amounts not densitometrically quantifiable, and patients with BJP Kappa and Lambda present in densitometrically measurable quantities. The Wilcoxon-Mann-Whitney test was applied to compare uFLC in controls and BJP trace samples. The correlation between immunochemical and densitometric measurements was assessed using Spearman’s correlation coefficient, and agreement was evaluated with Bland-Altman plots. Samples were also stratified by estimated glomerular filtration rate (eGFR) and total urinary proteins (TUP). Results Despite significant differences between the median values of uFLC measures in controls and BJP in trace sample groups, using the uFLC upper reference ranges would have led to over 50 % false negative results. Although a strong correlation existed between the two methods, turbidimetry consistently overestimated BJP levels. Conclusions uFLC turbidimetric measurements cannot accurately differentiate negative samples from those containing trace BJP, lacking the sensitivity required for clinical use. UIFE has shown greater sensitivity compared to turbidimetry. In monitoring, the systematic overestimation in the quantification of BJP, aggravated in cases of reduced renal function or high TUP concentration, makes it challenging for clinicians to evaluate therapeutic efficacy since the decision thresholds outlined in clinical guidelines are based on densitometric measurements.

Objectives Spontaneous subarachnoid hemorrhage (sSAH) is a life-threatening neurological event with high morbidity and mortality. Predicting patient outcomes remains challenging, necessitating novel prognostic tools. This study evaluates the prognostic value of central and systemic serum biomarkers, including S100, neuron-specific enolase (NSE), glial fibrillary acidic protein (GFAP), ubiquitin carboxy-terminal hydrolase L1 (UCHL-1), soluble suppression of tumorigenicity 2 (sST2), and soluble urokinase plasminogen activator receptor (suPAR) in acute sSAH. Methods A prospective observational study was conducted on 91 sSAH patients admitted to the Emergency Department. Biomarkers were measured 24 h post-admission and correlated with clinical severity using the modified Rankin Scale (mRS) at 24 h and 3 months. Statistical analyses included correlation tests, receiver operating characteristic (ROC) curves, and partial least squares discriminant analysis with 10-fold cross-validation (PLS-DA) to assess predictive accuracy. Results Patients with unfavorable outcomes (mRS 3–6) exhibited significantly higher median levels of all biomarkers. GFAP (ρ=0.74, p<0.0001) and S100 (ρ=0.65, p<0.0001) strongly correlated with hemorrhage volume. ROC analysis confirmed GFAP and S100 as the most effective central biomarkers (AUC=0.951), while sST2 demonstrated the highest prognostic sensitivity (97.1 %). PLS-DA further validated the prognostic relevance of sST2, GFAP, and S100. Conclusions Early biomarker assessment enhances sSAH prognosis, complementing neuroimaging. GFAP and S100 strongly correlate with brain injury severity, while sST2 predicts 3-months outcomes. Integrating these biomarkers into routine practice may improve early risk stratification and patient management.

Objectives Antigen excess (AE) or high dose hook-effect can seriously affect the reported concentration of an analyte, which may impact clinical decisions. This study analyze to what extent the Roche Elecsys ® Myoglobin assay is affected by antigen excess and how this can affect the reported myoglobin concentration. Methods A dilution series experiment was conducted on a patient sample with a very high myoglobin concentration (>150,000 μg/L). Based on this, an AE mitigation procedure based on sample dilutions was developed and implemented. A retrospective analysis of reported patient results was performed to assess the potential frequency of samples that could be affected by AE. Results In the dilution experiment the Roche Elecsys ® Myoglobin assay was susceptive to AE, where samples with concentrations >115,000 μg/L may be reported as <3,000 μg/L. Dilution series from patient samples (n=20) subjected to the AE mitigation procedure showed the same pattern as the dilution experiment. The percentage of samples >115,000 µ/L increased significantly after the AE mitigation procedure had been implemented. After implementation of the AE mitigation procedure, the maximum myoglobin concentration observed was 780,000 μg/L. Conclusions If the Roche Elecsys ® Myoglobin assay is used according to the manufacturer, extremely high myoglobin samples risk being reported as only mildly elevated or near normal. This may affect clinical decisions. Thus, we suggest an AE mitigation procedure with automatic dilution of samples where myoglobin concentrations exceed 500 μg/L to mitigate this risk. Roche needs to take further actions to eliminate the consequences of the AE interference.

Objectives In clinical practice, glycated albumin (GA), as a key biomarker reflecting the level of blood glucose control in the short and medium term, has been widely used in the diagnosis and efficacy monitoring of diabetes. However, the consistency of GA results between different detection systems remains one of the current challenges in laboratory medicine. we evaluated the commutability of 10 evaluated samples to identify candidate EQA materials for GA measurement. Methods According to the Clinical and Laboratory Standards Institute (CLSI) document EP14-A3 and the International Federation of Clinical Chemistry and Laboratory Medicine (IFCC) commutability evaluation program, we used the established isotope dilution liquid chromatography-tandem mass spectrometry (ID LC-MS/MS) method for serum glycated albumin determination as the comparative method, and six different commercial kits used enzyme assay as the evaluating method. A total of 40 clinical sample serums, 9 pregnancy sample serums, and 10 evaluated samples were analyzed. Results For the CLSI approach, pooled serum samples (cRM1-3) at medium concentrations (cRM2) are commutable in 5/6 kits. For the IFCC approach, none of samples commutable. Conclusions The commutability evaluation results of the two approaches were different, and the cRM2 has commutability in most enzymatic kits. It can be a commutable material for the EQA project.

Objectives Heavy metals (HMs) concentrations vary with living environments, diet, and personal habits. This study aims to establish health-related reference intervals (RIs) for selected HMs in healthy, non-occupationally exposed young adults living in an urban environment. Methods The Uni4Me study enrolled 154 healthy university volunteers (median age: 23 years) to assess the concentrations of seven HMs (lead, nickel, cadmium, zinc, chromium, cobalt, and mercury) using inductively coupled plasma-mass spectrometry (ICP-MS) and inductively coupled plasma-optical emission spectroscopy (ICP-EOS). CLSI guidelines were followed to estimate the 2.5th and 97.5th percentiles as RIs. Results Most metals were detected at low concentrations. Zinc showed consistent physiological levels in all participants. Mercury and chromium were the most frequently detected, indicating potential environmental or dietary exposure. Conclusions This study defines baseline values for HMs in an urban, healthy, young adult population. These results may support future biomonitoring efforts and public health initiatives targeting subclinical exposure in non-occupationally exposed populations.

Objectives Coagulation test results may be affected by hemolysis, icterus and/or lipemia (HIL). Detailed guidelines for HIL-management are missing, both for manual and automatic HIL-checks. The aim of this survey was to provide an overview of the practical procedures for the detection and handling of HIL-samples used by laboratories in Europe in the context of coagulation testing. Methods A SurveyMonkey questionnaire was sent from the Haemostasis Working Group in the European Organisation for External Quality Assurance Providers in Laboratory Medicine (EQALM) to European external quality assurance organizers, who in turn forwarded the link to their participating laboratories. Questions were asked regarding detection and handling of HIL-samples, comment- and reject-levels, and the guidance used by the laboratories. Results A written procedure for HIL-management was available in 55–67 % of laboratories, and each sample was checked for HIL in 73–83 % (lowest percentage for icterus, highest for hemolysis). Manual visual inspection as the only method to detect HIL was used by up to 38 % of laboratories, with most relying on personal experience for HIL-level classification. All other laboratories used some type of automated HIL-detection, alone or in combination with visual check. The terms used for classification and the HIL comment- and reject-levels varied widely, even among laboratories using the same manufacturer. Most laboratories state that they use the manufacturer’s guidance. Conclusions There is wide heterogeneity in HIL-detection, handling and reporting among European laboratories, which calls for an urgent collaboration among laboratories and manufacturers to harmonize the HIL-management in coagulation testing.

Objectives Atypical or malignant urothelial cells may be identified with a research parameter of atypical cells (Atyp.C) using a fully automated urine particle analyzer in routine urinalysis. This study aimed to determine whether Atyp.C can serve as an effective screening tool for female bladder cancer (BC) and to observe the impact of pyuria and bacteriuria on Atyp.C concentrations. Methods Patients were classified into six groups: primary BC, recurrent BC, post-treatment monitoring of BC, other urological tumors, pyuria and bacteriuria, and controls. Atyp.C concentrations were compared across these groups, and its diagnostic performance for BC or pyuria and bacteriuria was analyzed. Logistic regression determined whether Atyp.C was an independent risk factor for BC or pyuria and bacteriuria. Subsequently, key factors contributing to abnormal Atyp.C elevations were investigated. Results The median Atyp.C concentrations were significantly elevated in both primary (2.9/µL) and recurrent BC cases (4.0/µL) compared to patients with pyuria and bacteriuria (2.0/µL) and controls (1.7/µL) (p<0.01). Diagnostic performance of Atyp.C to detect primary female BC reached an area under curve of 0.818 when combined with age and urine conductivity. Multivariate analysis confirmed Atyp.C as an independent risk factor for BC in women. Falsely increased Atyp.C concentrations were caused by WBC clumps, clue cells covered by bacteria, and macrophages. Conclusions Atyp.C did not reach sufficient specificity for screening of BC in women with existing pyuria or bacteriuria. WBC clumps, macrophages and clue cells contributed to falsely positive Atyp.C counts.

Objectives Cardiac troponins (cTn) are used to detect and quantify acute cardiomyocyte injury. In patients presenting with symptoms that could indicate myocarditis, elevated cTn concentrations typically mandate cardiac catheterization and heart muscle biopsy or cardiac magnetic resonance imaging (CMR). Accordingly, increased cTn levels due to macrotroponin – a complex between patient anti-troponin autoantibodies and cTn – could lead to unnecessary and potentially harmful interventions. In athletes, ensuring cardiac health after infection like COVID-19 is critical, but the occurrence of false-positive cTn levels post-COVID-19 remains unknown. Methods This observational study prospectively included 35 healthy athletes (aged 16–75 years; 19 females, 16 males) who underwent post-COVID check-ups during 2022–2023. Athletes’ cTn levels were measured using four different hs-cTn routine immunoassays. If discrepancies were noted between assays, further testing for macrotroponin was conducted using protein G column, sucrose gradient ultracentrifugation and anti-troponin autoantibody immunoassay. Results Seventeen athletes had normal cTn levels across all assays, while 18 (51 %) had elevated cTn, mostly cTnI. Despite elevated cTn levels, no signs of myocarditis or other cardiac conditions were found on electrocardiography, echocardiography, or CMR. Macrotroponin was confirmed among 16 of these 18 athletes. Further, IgG anti-troponin autoantibodies correlated significantly with the levels of the two most-commonly affected assays: hs-cTnI-Siemens Atellica and hs-cTnI-Abbott Alinity. Conclusions Post-COVID-19, nearly half of athletes showed elevated cTnI levels due to interference from macrotroponin. Awareness among physicians and laboratorians of this analytical confounder can avoid unnecessary invasive or costly diagnostic tests in athletes with false-positive cTnI levels after COVID-19.

Objectives Type 1 diabetes (T1D) is a chronic autoimmune disease causing β-cell destruction, hyperglycemia, and lifelong insulin dependence that can lead to severe complications like ketoacidosis, with a 1 % mortality rate in newly diagnosed patients. A significant breakthrough in T1D research was the identification of a long presymptomatic phase, characterized by disease-specific autoantibodies despite the absence of clinical symptoms. The aim of our study was to compare the results of different commercial assays for detecting anti-GAD, -IA-2, -ZnT8 antibodies and IAA to evaluate the state of the art of the current methods in a routine clinical laboratory setting. Methods We have analyzed 87 consecutive samples from patients screened for T1D and evaluated the agreement among four commercial assays (two chemiluminescence immunoassays and two immunoenzymatic assays) for detecting anti-GAD, -IA-2, -ZnT8 antibodies and IAA. Results The agreement among methods for all disease-specific antibodies measured by Cohen’s kappa ranged from 0.514 to 1.000. The highest agreement was found for anti-GAD antibodies (0.923–0.963) and the lowest agreement for IAA (0.514–0.550). The average agreement was 0.796 (SD: 0.170) and it was statistically significant at p<0.001 for all comparisons. Conclusions Even though some differences exist among methods, our findings provide valuable insights into the use of new technologies for T1D diagnosis, demonstrating an overall consistent agreement among assays tested for all antibodies but IAA.