A comprehensive survey of artificial intelligence adoption in European laboratory medicine: current utilization and prospects.

Background: As the healthcare sector evolves, Artificial Intelligence's (AI's) potential to enhance laboratory medicine is increasingly recognized. However, the adoption rates and attitudes towards AI across European laboratories have not been comprehensively analyzed. This study aims to fill this gap by surveying European laboratory professionals to assess their current use of AI, the digital infrastructure available, and their attitudes towards future implementations.

The biological variation of insulin resistance markers: data from the European Biological Variation Study (EuBIVAS).

Objectives: An insulin resistant state is characteristic of patients with type 2 diabetes, polycystic ovary syndrome, and metabolic syndrome. Identification of insulin resistance (IR) is most readily achievable using formulae combining plasma insulin and glucose results. In this study, we have used data from the European Biological Variation Study (EuBIVAS) to examine the biological variability (BV) of IR using the Homeostasis Model Assessment for Insulin Resistance (HOMA-IR) and the Quantitative Insulin sensitivity Check Index (QUICKI).

C-Reactive Protein and Brain Natriuretic Peptides Harmonization.

The harmonization of laboratory biomarkers is pivotal in ensuring consistent and reliable diagnostic outcomes across different clinical settings. This systematic review examines the harmonization of C-Reactive Protein (CRP) and N-Terminal Prohormone of Brain Natriuretic Peptide (NT-proBNP) measurements, both of which are jointly utilized in the diagnosis and management of cardiovascular diseases. To identify relevant studies, we searched the PubMed electronic database using specific medical subject headings and keywords such as C-Reactive Protein, CRP, high sensitivity C-Reactive Protein (hs-CRP), N-terminal pro B-type natriuretic peptide, and NT-proBNP, focusing on publications from June 1 to September 26, 2021.

A standard to report biological variation data studies - based on an expert opinion.

There is a need for standards for generation and reporting of Biological Variation (BV) reference data. The absence of standards affects the quality and transportability of BV data, compromising important clinical applications. To address this issue, international expert groups under the European Federation of Clinical Chemistry and Laboratory Medicine (EFLM) have developed an online resource (https://tinyurl.

A New Concept for Reference Change Values-Regression to the Population Mean.

Background: Reference change values (RCV) are used to indicate a change in analyte concentration that is unlikely to be due to random variation in the patient or the measurement. Current theory describes RCV relative to a first measurement result (X1). We investigate an alternative view predicting the starting point for RCV calculations from X1 and its location in the reference interval.

Biological Variation Estimates for Plasma Copeptin and Clinical Implications.

Background: Plasma copeptin measurement is useful for the differential diagnoses of polyuria-polydipsia syndrome. It has also been proposed as a prognostic marker for cardiovascular diseases. However, limited information is available about the within- (CVI) and between-subject (CVG) biological variation (BV).

Analytical performance specifications based on biological variation data - considerations, strengths and limitations.

Analytical performance specifications (APS) are typically established through one of three models: (i) outcome studies, (ii) biological variation (BV), or (iii) state-of-the-art. Presently, The APS can, for most measurands that have a stable concentration, be based on BV. BV based APS, defined for imprecision, bias, total allowable error and allowable measurement uncertainty, are applied to many different processes in the laboratory.

The European biological variation study (EuBIVAS): Biological variation data for testosterone, follicle stimulating hormone, prolactin, luteinizing hormone and dehydroepiandrosterone sulfate in men.

Background: Knowledge of biological variation (BV) of hormones is essential for interpretation of laboratory tests and for diagnostics of endocrinological and reproductive diseases. There is a lack of robust BV data for many hormones in men.

Methods: We used serum samples collected weekly over 10 weeks from the European Biological Variation Study (EuBIVAS) to determine BV of testosterone, follicle-stimulating hormone (FSH), prolactin, luteinizing hormone (LH) and dehydroepiandrosterone sulfate (DHEA-S) in 38 men.

Machine learning algorithms in sepsis.

Sepsis remains a significant global health challenge due to its high mortality and morbidity, compounded by the difficulty of early detection given its variable clinical manifestations. The integration of machine learning (ML) into laboratory medicine for timely sepsis identification and outcome forecasting is an emerging field of interest. This comprehensive review assesses the current body of research on ML applications for sepsis within the realm of laboratory diagnostics, detailing both their strengths and shortcomings.

Biological variation of inflammatory and iron metabolism markers in high-endurance recreational athletes; are these markers useful for athlete monitoring?

Objectives: To deliver biological variation (BV) data for serum hepcidin, soluble transferrin receptor (sTfR), erythropoietin (EPO) and interleukin 6 (IL-6) in a population of well-characterized high-endurance athletes, and to evaluate the potential influence of exercise and health-related factors on the BV.

Methods: Thirty triathletes (15 females) were sampled monthly (11 months). All samples were analyzed in duplicate and BV estimates were delivered by Bayesian and ANOVA methods.

Rising adoption of artificial intelligence in scientific publishing: evaluating the role, risks, and ethical implications in paper drafting and review process.

Background: In the rapid evolving landscape of artificial intelligence (AI), scientific publishing is experiencing significant transformations. AI tools, while offering unparalleled efficiencies in paper drafting and peer review, also introduce notable ethical concerns.

Content: This study delineates AI's dual role in scientific publishing: as a co-creator in the writing and review of scientific papers and as an ethical challenge.

Sex-related differences in within-subject biological variation estimates for 22 essential and non-essential amino acids.

Background: Measurement of serum amino acid (AA) concentrations is important in particular for the diagnosis and monitoring of inborn errors of AA metabolism. To ensure optimal clinical interpretation of AAs, reliable biological variation (BV) data are essential. In the present study, we derived BV data for 22 non-essential, conditionally essential, and essential AAs and assessed differences in BV of AAs related to sex.

Biological variation estimates for serum neurofilament light chain in healthy subjects.

Objectives: Neurofilament light chain (NfL) is an emerging biomarker of neurodegeneration disorders. Knowledge of the biological variation (BV) can facilitate proper interpretation between serial measurements. Here BV estimates for serum NfL (sNfL) are provided.

Safety of Subcutaneous Daratumumab in Anti-CD38 Monoclonal Antibody-Naïve Patients with Plasma Cell Disorders: A Multicenter Real-Life Experience.

Background: Daratumumab, an anti-CD38 monoclonal antibody, is used for treatment of multiple myeloma (MM) and light chain amyloidosis at an intravenous dosage of 16 mg/kg or at a subcutaneous fixed dose of 1800 mg. However, the subcutaneous formulation has only recently been approved in Europe, and real-life data on its safety are still few.

Objective: In this multicenter retrospective real-life experience, we provided evidence for the safety of subcutaneous daratumumab in plasma cell disorders.

Review on adherence of the literature to official recommendations on albuminuria harmonization and standardization.

Albuminuria standardization is a key issue to produce reliable and equivalent results between laboratories. We investigated whether official recommendations on albuminuria harmonization are followed in the literature. The PubMed database was searched from June 1 to September 26, 2021.

Potentials and pitfalls of ChatGPT and natural-language artificial intelligence models for the understanding of laboratory medicine test results. An assessment by the European Federation of Clinical Chemistry and Laboratory Medicine (EFLM) Working Group on Artificial Intelligence (WG-AI).

Objectives: ChatGPT, a tool based on natural language processing (NLP), is on everyone's mind, and several potential applications in healthcare have been already proposed. However, since the ability of this tool to interpret laboratory test results has not yet been tested, the EFLM Working group on Artificial Intelligence (WG-AI) has set itself the task of closing this gap with a systematic approach.

Methods: WG-AI members generated 10 simulated laboratory reports of common parameters, which were then passed to ChatGPT for interpretation, according to reference intervals (RI) and units, using an optimized prompt.

Analytical performance specifications for the measurement uncertainty of 24,25-dihydroxyvitamin D examinations.

Objectives: The exploration of the metabolites in the degradation pathways of vitamin D (VTD) has gained importance in recent years and simultaneous quantitation of twenty-five-hydroxy vitamin D (25(OH)D) mass concentration together with 24,25-dihydroxyvitamin D (24,25(OH)2D) has been proposed as a newer approach to define VTD deficiency. Yet, no data are available on 24,25(OH)2D biological variation (BV). In this study, we evaluated 24,25(OH)2D's BV on the European Biological Variation Study (EuBIVAS) cohort samples to determine if analytical performance specifications (APS) for 24,25(OH)2D could be generated.

The European Register of Specialists in Clinical Chemistry and Laboratory Medicine: code of conduct, version 3 - 2023.

Whilst version 2 focussed on the professional conduct expected of a Specialist in Laboratory Medicine, version 3 builds on the responsibilities for ethical conduct from point of planning to point of care. Particular responsibilities that are outlined include: - The need for evidence when planning a new service, providing assurance that a new test does not do harm - Maintaining respect for patient confidentiality, their religious/ethnic beliefs, the need for informed consent to test, agreement on retrospective use of samples as part of governance envelopes in the pre-analytical phase - Ensuring respect for patient autonomy in the response to untoward results generated in the analytical phase - Supporting the safety of patients in the post-analytical phase through knowledge-based interpretation and presentation of results - The duty of candour to disclose and respond to error across the total testing process - Leading initiatives to harmonise and standardise pre-analytical, analytical and post-analytical phases to ensure more consistent clinical decision making with utilisation of demand management to ensure more equitable access to scarce resources - Working with emerging healthcare providers beyond the laboratory to ensure consistent application of high standards of clinical care In identifying opportunities for wider contributions to resolving ethical challenges across healthcare the need is also highlighted for more external quality assurance schemes and ethics-based quality indicators that span the total testing process.