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Loa loa is an arthropod-transmitted filarial nematode, and one of four pathologically prevalent blood microfilaria associated with human infection. This case report describes an instance of a 41-year-old male diagnosed with Loa loa by peripheral blood smear and subsequently also diagnosed with Onchocerca. Here we describe the clinical course, diagnostic evaluation and treatment considerations when managing potential nematode co-infections. This case also highlights laboratory diagnosis strategies, treatment challenges, and emphasizes a differential diagnosis of chronic infections with neglected tropical infectious agents. [ABSTRACT FROM AUTHOR]

We report a fatal case of Legionella feeleii endocarditis in a post–lung transplant patient. The diagnosis was delayed, as routine microbiological testing of nonrespiratory specimens does not account for extrapulmonary Legionella , and urine antigen testing only reliably detects Legionella pneumophila serogroup 1. This case also illustrates the utility of molecular sequencing for blood culture–negative endocarditis. [ABSTRACT FROM AUTHOR]

Background/Objectives: Adaptive hyperactivity characterized by increased activity levels and novelty-seeking traits without mood disorders is prevalent among older adults in Sardinia's "blue zone," an area with high longevity. This study aims to evaluate the adaptive nature of hyperactivity concerning quality of life, social rhythms, and mood symptoms in individuals from this region, particularly among elderly adults over 80. Methods: This observational cross-sectional study included adults and older adults over 80 from Sardinia's blue zone. This study included a sample of patients followed at the Center for Consultation Psychiatry and Psychosomatics for Bipolar Disorder of the University Hospital of Cagliari and a homogeneous comparison sample of patients without psychiatric pathologies, referred to the Dermatology Clinic of the same hospital, for a period of 6 months, from February to August 2024. The general sample, divided into two parts—cases, represented by patients with psychiatric pathology, and controls, patients without psychiatric pathology—was divided in turn into three sub-groups: "adults" (18–64 years), young elders (65–79), and old elders (over 80 years). The participants underwent psychiatric interviews and completed the Mood Disorder Questionnaire (MDQ), Patient Health Questionnaire (PHQ-9), SF-12, and Brief Social Rhythm Scale (BSRS). Data were compared with national and regional normative data. Results: Older adults in the blue zone demonstrated higher MDQ positivity (22.58%) compared to the national averages (0.87%), without corresponding increases in dysregulated rhythms, depressive symptoms, or reduced quality of life. Younger old persons (65–79 years) showed increased rhythm dysregulation (BSRS score: 20.64 ± 7.02) compared to adults (17.40 ± 6.09, p = 0.040), but this trend was not observed in the oldest group (80+ years). No significant differences were found in the CH3SH and (CH3)2S levels between groups. Conclusions: The hyperactivity observed in older adults from Sardinia's blue zone appears adaptive and not linked to social rhythm dysregulation, depressive symptoms, or a diminished quality of life, suggesting resilience factors which may contribute to longevity. These findings support the potential classification of such hyperactivity as beneficial rather than pathological, warranting further research into biomarkers and psychoeducational interventions to prevent the onset of bipolar disorders in predisposed individuals. [ABSTRACT FROM AUTHOR]

The ultimate goal of value-based laboratory medicine is maximizing the effectiveness of laboratory tests in improving patient outcomes, optimizing resources and minimizing unnecessary costs. This approach abandons the oversimplified notion of test volume and cost, in favor of emphasizing the clinical utility and quality of diagnostic tests in the clinical decision-making. Several key elements characterize value-based laboratory medicine, which can be summarized in some basic concepts, such as organization of in vitro diagnostics (including appropriateness, integrated diagnostics, networking, remote patient monitoring, disruptive innovations), translation of laboratory data into clinical information and measurable outcomes, sustainability, reimbursement, ethics (e.g., patient empowerment and safety, data protection, analysis of big data, scientific publishing). Education and training are also crucial, along with considerations for the future of the profession, which will be largely influenced by advances in automation, information technology, artificial intelligence, and regulations concerning in vitro diagnostics. This collective opinion paper, composed of summaries from presentations given at the two-day European Federation of Laboratory Medicine (EFLM) Strategic Conference "A vision to the future: value-based laboratory medicine" (Padova, Italy; September 23–24, 2024), aims to provide a comprehensive overview of value-based laboratory medicine, projecting the profession into a more clinically effective and sustainable future. [ABSTRACT FROM AUTHOR]

Background: Healthcare 4.0. refers to the integration of advanced technologies, such as artificial intelligence (AI) and big data analysis, into the healthcare sector. Recognizing the impact of Healthcare 4.0 technologies in laboratory medicine (LM), we seek to assess the overall awareness and implementation of Healthcare 4.0 among members of the Korean Society for Laboratory Medicine (KSLM). Methods: A web-based survey was conducted using an anonymous questionnaire. The survey comprised 36 questions covering demographic information (seven questions), big data (10 questions), and AI (19 questions). Results: In total, 182 (17.9%) of 1,017 KSLM members participated in the survey. Thirty-two percent of respondents considered AI to be the most important technology in LM in the era of Healthcare 4.0, closely followed by 31% who favored big data. Approximately 80% of respondents were familiar with big data but had not conducted research using it, and 71% were willing to participate in future big data research conducted by the KSLM. Respondents viewed AI as the most valuable tool in molecular genetics within various divisions. More than half of the respondents were open to the notion of using AI as assistance rather than a complete replacement for their roles. Conclusions: This survey highlighted KSLM members’ awareness of the potential applications and implications of big data and AI. We emphasize the complexity of AI integration in healthcare, citing technical and ethical challenges leading to diverse opinions on its impact on employment and training. This highlights the need for a holistic approach to adopting new technologies. [ABSTRACT FROM AUTHOR]

Reference ranges are invaluable in laboratory medicine, as these are indispensable tools for the interpretation of laboratory test results. When assessing measurements on a single analyte, univariate reference intervals are required. In many cases, however, measurements on several analytes are needed by medical practitioners to diagnose more complicated conditions such as kidney function or liver function. For such cases, it is recommended to use multivariate reference regions, which account for the cross-correlations among the analytes. Traditionally, multivariate reference regions (MRRs) have been constructed as ellipsoidal regions. The disadvantage of such regions is that they are unable to detect component-wise outlying measurements. Because of this, rectangular reference regions have recently been put forward in the literature. In this study, we develop methodologies to compute rectangular MRRs that incorporate covariate information, which are often necessary in evaluating laboratory test results. We construct the reference region using tolerance-based criteria so that the resulting region possesses the multiple use property. Results show that the proposed regions yield coverage probabilities that are accurate and are robust to the sample size. Finally, we apply the proposed procedures to a real-life example on the computation of an MRR for three components of the insulin-like growth factor system. [ABSTRACT FROM AUTHOR]

In the last decades, clinical laboratories have significantly advanced their technological capabilities, through the use of interconnected systems and advanced software. Laboratory Information Systems (LIS), introduced in the 1970s, have transformed into sophisticated information technology (IT) components that integrate with various digital tools, enhancing data retrieval and exchange. However, the current capabilities of LIS are not sufficient to rapidly save the extensive data, generated during the total testing process (TTP), beyond just test results. This opinion paper discusses qualitative types of TTP data, proposing how to divide laboratory-generated information into two categories, namely metadata and peridata. Being both metadata and peridata information derived from the testing process, it is proposed that the first is useful to describe the characteristics of data, while the second is for interpretation of test results. Together with standardizing preanalytical coding, the subdivision of laboratory-generated information into metadata or peridata might enhance ML studies, also by facilitating the adherence of laboratory-derived data to the Findability, Accessibility, Interoperability, and Reusability (FAIR) principles. Finally, integrating metadata and peridata into LIS can improve data usability, support clinical utility, and advance AI model development in healthcare, emphasizing the need for standardized data management practices. [ABSTRACT FROM AUTHOR]

The multifaceted potential of ChatGPT in the medical domain remains underexplored, particularly regarding its application in software development by individuals with a medical background but limited information technology expertise. This study investigates ChatGPT's utility in creating a laboratory medicine application. Despite minimal programming skills, the authors successfully developed an automated intra-assay, inter-device precision test for immunophenotyping with a shiny user interface, facilitated by ChatGPT. While the coding process was expedited, meticulous oversight and error correction by the authors were imperative. These findings highlight the value of large language models such as ChatGPT in code-based application development for automating work processes in a medical context. Particularly noteworthy is the facilitation of these tasks for non-technically trained medical professionals and its potential for digital medical education. [ABSTRACT FROM AUTHOR]

Objectives: Urinary tract infections (UTIs) are common infections within the Emergency Department (ED), causing increased laboratory workloads and unnecessary antibiotics prescriptions. The aim of this study was to improve UTI diagnostics in clinical practice by application of machine learning (ML) models for real-time UTI prediction. Methods: In a retrospective study, patient information and outcomes from Emergency Department patients, with positive and negative culture results, were used to design models – ‘Random Forest’ and ‘Neural Network’ – for the prediction of UTIs. The performance of these predictive models was validated in a cross-sectional study. In a quasi-experimental study, the impact of UTI risk assessment was investigated by evaluating changes in the behaviour of clinicians, measuring changes in antibiotic prescriptions and urine culture requests. Results: First, we trained and tested two different predictive models with 8692 cases. Second, we investigated the performance of the predictive models in clinical practice with 962 cases (Area under the curve was between 0.81 to 0.88). The best performance was the combination of both models. Finally, the assessment of the risk for UTIs was implemented into clinical practice and allowed for the reduction of unnecessary urine cultures and antibiotic prescriptions for patients with a low risk of UTI, as well as targeted diagnostics and treatment for patients with a high risk of UTI. Conclusion: The combination of modern urinalysis diagnostic technologies with digital health solutions can help to further improve UTI diagnostics with positive impact on laboratory workloads and antimicrobial stewardship.

The healthcare systems are a prime target for cyber-attacks due to the sensitive nature of the information combined with the essential need for continuity of care. Medical laboratories are particularly vulnerable to cyber-attacks for a number of reasons, including the high level of information technology (IT), computerization and digitization. Based on reliable and widespread evidence that medical laboratories may be inadequately prepared for cyber-terrorism, a panel of experts of the Task Force Preparation of Labs for Emergencies (TF-PLE) of the European Federation of Clinical Chemistry and Laboratory Medicine (EFLM) has recognized the need to provide some general guidance that could help medical laboratories to be less vulnerable and better prepared for the dramatic circumstance of a disruptive cyber-attack, issuing a number of consensus recommendations, which are summarized and described in this opinion paper. [ABSTRACT FROM AUTHOR]

To develop two ethical checklists to evaluate (i) management of ethical concerns in research projects and (ii) awareness of ethical conduct of healthcare laboratory professionals. Comprehensive discussion among the members of IFCC Task Force on Ethics based on pertinent literature. This Checklist for Clinical Research Projects should be useful to evaluate research proposals from an ethical perspective before submitting it to an IRB or its equivalent, thereby diminishing rejection rates and resulting in more time-effective projects. The checklist designed to evaluate the ethical conduct in laboratory medicine could be useful for self evaluation (internal audits) and for certification/accreditation processes performed by third parties. These checklists are simple but powerful tools useful to guide professionals to adhere to ethical principles in their practice, especially in developing countries where accredited ethics committees may be difficult to find. [ABSTRACT FROM AUTHOR]

With Industry 4.0, big data and artificial intelligence have become paramount in the field of medicine. Electronic health records, the primary source of medical data, are not collected for research purposes but represent real-world data; therefore, they have various constraints. Although structured, laboratory data often contain unstandardized terminology or missing information. The major challenge lies in the lack of standardization of test results in terms of metrology, which complicates comparisons across laboratories. In this review, we delve into the essential components necessary for integrating real-world laboratory data into high-quality big data, including the standardization of terminology, data formats, equations, and the harmonization and standardization of results. Moreover, we address the transference and adjustment of laboratory results, along with the certification for quality of laboratory data. By discussing these critical aspects, we seek to shed light on the challenges and opportunities inherent to utilizing real-world laboratory data within the framework of healthcare big data and artificial intelligence. [ABSTRACT FROM AUTHOR]

Machine learning (ML) is currently being widely studied and applied in data analysis and prediction in various fields, including laboratory medicine. To comprehensively evaluate the application of ML in laboratory medicine, we reviewed the literature on ML applications in laboratory medicine published between February 2014 and March 2024. A PubMed search using a search string yielded 779 articles on the topic, among which 144 articles were selected for this review. These articles were analyzed to extract and categorize related fields within laboratory medicine, research objectives, specimen types, data types, ML models, evaluation metrics, and sample sizes. Sankey diagrams and pie charts were used to illustrate the relationships between categories and the proportions within each category. We found that most studies involving the application of ML in laboratory medicine were designed to improve efficiency through automation or expand the roles of clinical laboratories. The most common ML models used are convolutional neural networks, multilayer perceptrons, and tree-based models, which are primarily selected based on the type of input data. Our findings suggest that, as the technology evolves, ML will rise in prominence in laboratory medicine as a tool for expanding research activities. Nonetheless, expertise in ML applications should be improved to effectively utilize this technology. [ABSTRACT FROM AUTHOR]

Laboratory medicine has undergone a deep and multifaceted revolution in the course of human history, in both organizational and technical terms. Over the past century, there has been a growing recognition of the need to centralize numerous diagnostic activities, often similar or identical but located in different clinical departments, into a common environment (i.e., the medical laboratory service), followed by a progressive centralization of tests from smaller laboratories into larger diagnostic facilities. Nevertheless, the numerous technological advances that emerged at the beginning of the new millennium have helped to create a new testing culture characterized by a countervailing trend of decentralization of some tests closer to patients and caregivers. The forces that have driven this (centripetal) counter-revolution essentially include a few key concepts, namely "home testing", "portable or even wearable devices" and "remote patient monitoring". By their very nature, laboratory medical services and remote patient testing/monitoring are not contradictory, but may well coexist, with the choice of one or the other depending on the demographic and clinical characteristics of the patient, the type of analytical procedure and the logistics and local organization of the care system. Therefore, this article aims to provide a general overview of patient self-testing, with a particular focus on portable and wearable (including implantable) devices. [ABSTRACT FROM AUTHOR]

Metabolomics aims for comprehensive characterization and measurement of small molecule metabolites (<1700 Da) in complex biological matrices. This study sought to assess the current understanding and usage of metabolomics in laboratory medicine globally and evaluate the perception of its promise and future implementation. A survey was conducted by the IFCC metabolomics working group that queried 400 professionals from 79 countries. Participants provided insights into their experience levels, knowledge, and usage of metabolomics approaches, along with detailing the applications and methodologies employed. Findings revealed a varying level of experience among respondents, with varying degrees of familiarity and utilization of metabolomics techniques. Targeted approaches dominated the field, particularly liquid chromatography coupled to a triple quadrupole mass spectrometer, with untargeted methods also receiving significant usage. Applications spanned clinical research, epidemiological studies, clinical diagnostics, patient monitoring, and prognostics across various medical domains, including metabolic diseases, endocrinology, oncology, cardiometabolic risk, neurodegeneration and clinical toxicology. Despite optimism for the future of clinical metabolomics, challenges such as technical complexity, standardization issues, and financial constraints remain significant hurdles. The study underscores the promising yet intricate landscape of metabolomics in clinical practice, emphasizing the need for continued efforts to overcome barriers and realize its full potential in patient care and precision medicine. [ABSTRACT FROM AUTHOR]

The Health Technology Assessment (HTA) Working Group of the Emerging Technology Division of International Federation of Clinical Chemistry and Laboratory Medicine (IFCC) aims to develop a methodological approach for producing structured HTA information for laboratory medicine technologies. This approach seeks to support decision-making processes at the country, regional, and/or hospital levels regarding the introduction of specific technologies. The focus of this model will primarily be on defining assessment elements within the domains of 'organizational aspects' and 'costs and economic evaluations', potentially differentiated by the type of diagnostic technology (e.g., genetic tests, molecular tests). To achieve this project's goal, a literature review and examination of websites of international HTA agencies have been conducted. The research aims to identify multidisciplinary methodological approaches used to assess laboratory diagnostic technologies and to pinpoint the domains and assessment elements utilized. We found 7 methodological articles describing methodological approaches adopted to assess laboratory diagnostic technologies. Among the HTA organizations considered, 23 reports were found, of which 7 were produced by the European Network of HTA (EUnetHTA), 4 by the National Institute for Health and Care Excellence Diagnostic Assessment Program (NICE DAP), and 12 by other HTA agencies. The EUnetHTA reports were rapid collaborative assessments covering various domains, while the NICE DAP reports focused on diagnostic guidances, including descriptions of technologies, clinical need and practice, diagnostic tests, accuracy, effectiveness, and cost-effectiveness. Finally, a survey targeting laboratory professionals will be conducted to introduce assessment elements, differentiated by the type of diagnostic technology, primarily for organizational and economic domains. [ABSTRACT FROM AUTHOR]

Lupus nephritis (LN) is one of the most severe clinical manifestations of systemic lupus erythematosus (SLE). Notably, the clinical manifestations of LN are not always consistent with the histopathological findings. Therefore, the diagnosis and activity monitoring of this disease are challenging and largely depend on invasive renal biopsy. Renal biopsy has side effects and is associated with the risk of bleeding and infection. There is a growing interest in the development of novel noninvasive biomarkers for LN. In this review, we summarize most of the LN biomarkers discovered so far by correlating current knowledge with future perspectives. These biomarkers fundamentally reflect the biological processes of kidney damage and repair during disease. Furthermore, this review highlights the role of urinary cell phenotype detection in the diagnosis, monitoring, and treatment of LN and summarizes the limitations and countermeasures of this test. [ABSTRACT FROM AUTHOR]

Background Despite stewardship efforts, laboratory testing overuse persists across medicine. Objectives To understand laboratory stewardship perceptions and testing patterns at a tertiary care pediatric hospital so that we could identify potential improvement opportunities. Methods An electronic survey exploring laboratory stewardship was sent to all pediatric medicine resident and staff physicians. Laboratory testing data were also assessed for patterns of testing and overuse. Results The survey response rate was 54% (43/80). The results indicated good familiarity with stewardship but poor familiarity with testing specifics (eg, cost). A mobile reference application was the most preferred quality improvement intervention, and online modules were the least desired. Overuse was apparent, with as many as 53% of laboratory tests being repeated within 7 days and only half of repeated tests subsequently yielding abnormal results. Conclusions Altogether, the data we collated demonstrated poor understanding of laboratory stewardship and substantial repeat testing with few abnormal results. These study findings suggest that laboratory stewardship is lacking at our center, and that multiple improvement opportunities exist. [ABSTRACT FROM AUTHOR]

Medical microbiology laboratories play an essential role in patient care—appertaining to infectious diseases diagnostics and treatment, infection prevention, and antimicrobial stewardship. Collaboration between clinicians and the microbiology laboratory can promote and enhance the safety, quality, and efficiency of patient care. We review practical, evidence-informed core concepts to explicate how effective partnership between clinicians and the microbiology laboratory improves patient outcomes. [ABSTRACT FROM AUTHOR]

The role of Laboratory Medicine in patient care has evolved in the last decades. The same has occurred to the laboratory model, which has evolved from a traditional model where the laboratory is merely involved in clinical decision-making to a leading model where the laboratory is not only involved but also determines decision-making. The advent of new technologies and automation of processes have enabled laboratory professionals to focus on the first and last phase of the analytical process namely, test ordering and decision-making based on laboratory results. These phases are more error-prone than the analytical phase, and where action must be taken to improve the quality of patient care. We share our experience in the design and establishment of laboratory test demand management interventions that facilitated diagnosis of occult disease, improved adherence to clinical guidelines, and optimized patient safety. A description is provided of key points in the management of laboratory test over/underutilization. The objective of this review is to promote the involvement of laboratory professionals in the design and implementation of demand management interventions and in the development of the new Leader Laboratory model. [ABSTRACT FROM AUTHOR]

Introduction: A molecular diagnostic laboratory is the cornerstone of Coronavirus Disease-2019 (COVID-19) disease diagnosis, as the patient’s treatment and management protocol depend on molecular results. Therefore, the laboratory conducting these tests must adhere to quality management process to increase the accuracy and validity of the generated reports. Rajiv Gandhi Super Speciality Hospital established its molecular diagnostic set-up at the beginning of the pandemic. Hence, this study aims to generate quality management data to help improve weak points. Aim: To assess the quality management system for COVID-19 diagnosis. Materials and Methods: This retrospective observational study was conducted at Rajiv Gandhi Super Speciality Hospital in Delhi, India. A total of 14,561 samples were collected over six months, from February 2021 to July 2021. Data from all samples received during this period for COVID-19 Reverse-Transcriptase Polymerase Chain Reaction (RT-PCR) testing were included. Data were retrospectively collected from the electronic Laboratory Information Management System (LIMS). Quality variables were analysed over six months from July to December 2021 and classified into preanalytical, analytical, and postanalytical variables. Quality Indicators (QIs) were selected from a common model of QIs set by the International Federation of Clinical Chemistry and Laboratory Medicine. The results were presented in percentages, and descriptive statistics were analysed using Statistical Package for Social Sciences (SPSS) software. Results: During the six-month study period, the molecular laboratory received 14,561 samples. Among the preanalytical variables, sample leakage was the most common cause of sample rejection (134 samples, 0.92%), followed by the non generation of Specimen Referral Form (SRF) identification (76 samples, 0.52%), and non compliance with triple packaging (44 samples, 0.3%). Other preanalytical aspects assessed included incomplete patient identification (17 samples, 0.11%), insufficient sample quantity (12 samples, 0.08%), missing forms/samples (7 samples, 0.04%), samples in the wrong vials/empty Viral Transport Media (VTM) tubes (5 samples, 0.03%), and incomplete LIMS entry (2 samples, 0.01%). Internal Quality Control (QC) was not obtained in 55 samples (0.37%), and two incidents of cross-contamination resulted in false-positive results. Among the postanalytical factors, 11 samples (0.07%) could not be dispatched within the stipulated time frame. Conclusion: The assessment of the quality management system revealed some areas for improvement, emphasising the importance of adhering to QC processes for the smooth operation of diagnostic laboratories, especially those involved in critical reporting. The assessment of QIs helped monitor laboratory parameters effectively.

Clinical Decision Support Systems (CDSS) have been implemented in almost all healthcare settings. Laboratory medicine (LM), is one of the most important structured health data stores, but efforts are still needed to clarify the use and scope of these tools, especially in the laboratory setting. The aim is to clarify CDSS concept in LM, in the last decade. There is no consensus on the definition of CDSS in LM. A theoretical definition of CDSS in LM should capture the aim of driving significant improvements in LM mission, prevention, diagnosis, monitoring, and disease treatment. We identified the types, workflow and data sources of CDSS. The main applications of CDSS in LM were diagnostic support and clinical management, patient safety, workflow improvements, and cost containment. Laboratory professionals, with their expertise in quality improvement and quality assurance, have a chance to be leaders in CDSS. [ABSTRACT FROM AUTHOR]

Severe hypo- and hypercalcemia are common and urgent treatment is recommended. Free calcium (fCa) is the gold standard but needs blood gas tests with challenging preanalytics. Total calcium (tCa) and calculated adjusted calcium (aCa) are readily available, but their interpretation is hampered by identical tCa and aCa cutoffs, laborious local aCa calculation and difficult comparability of calcium biomarkers. Laboratory results from University Medicine Leipzig were evaluated over a five-year period (236,274 patients). A local aCa equation was derived by linear least squares regression, the agreement between fCa, tCa and aCa assessed with Cohen's κ and decision thresholds derived by this indirect method. The local aCa equation was created from data of 9,756 patients, each with one paired measurement of tCa, fCa and albumin. Derived aCa cutoffs (1.95/3.15 mmol/L) differ markedly from derived tCa cutoffs (1.6/2.9 mmol/L) and severe hypo- and hypercalcemia can be more accurately assessed by aCa (κ=0.489, 0.812) than by tCa (κ=0.445, 0.744). Comparing our approach to standard care (tCa, literature cutoff), a total 3,250 of 3,680 (88.3 %) misclassified measurements were correctly classified when using aCa with evidence-based cutoffs. Optimized cutoffs for aCa and tCa hold great potential for improved patient care. Locally derived aCa equations differ mostly in the chosen mean normal calcium and provide minimal overall improvement, but entail a close examination of the used cutoffs before application. [ABSTRACT FROM AUTHOR]

Background: The CELTIC ranges project aims to deliver a comprehensive range of reference intervals for commonly ordered laboratory investigations suitable for use in an Irish population as well as enabling comparison with relevant international studies. In this paper, we describe our methodology used throughout the entire project and present paediatric reference intervals for renal profile tests in plasma (sodium, potassium, urea and creatinine). Methods: 1023 children aged up to 17 years were recruited from our hospital's general practitioner paediatric phlebotomy clinic. Clinical chemistry analyses were performed on the Roche modular system and statistical analysis was completed in line with CLSI guideline EP28-A3c. Results: The plasma reference interval for sodium for ages 0.45–16.99 years was 137–143 mmol/L in 1000 subjects (combined genders). For plasma potassium, the corresponding ranges between 1 and 16.99 years (combined genders) were 3.6–4.8 mmol/L. Apart from neonates and in keeping with other studies, age partitioning for electrolytes was not required. Data for plasma creatinine (enzymatic methodology) and urea is also presented and, as anticipated, required partitioning for both age and gender. Conclusions: Our renal profile findings are broadly consistent with those of international studies, for example, CALIPER, HAPPI, NORDIC, PRINCE and KiGGs. Moreover, the CELTIC ranges study is also based on over 1000 subjects whose samples were analysed on the widely used Roche modular analytics system. We also expect the findings will improve knowledge of children's metabolic health in Ireland. [ABSTRACT FROM AUTHOR]

Background To remain effective in the dynamic health care landscape, the laboratory must embrace the continuous improvement mindset to support a culture of change, and leadership must facilitate the change process, mitigating perceived barriers of change readiness in followers. Methods This quantitative study was designed to determine whether there is an association between leadership style (Multifactor Leadership Questionnaire [MLQ]) and change readiness (3-component model [TCM] commitment to change/Employee Commitment Survey, and whether leadership style predicts change readiness. Laboratory professionals (n = 718) were recruited through national societies to complete a combined MLQ-TCM survey instrument. Multivariate analysis of variance, Pearson correlations, and multiple regression analyses were performed. Results A significant correlation between leadership style and change readiness (transformational leadership [TL] and affective commitment to change, r (716) =.12, P =.002; passive-avoidant behavior and continuance commitment to change, r (716) =.25, P <.001) and between leadership style and leadership outcomes (TL and effectiveness, r (716) =.90, P <.001) was identified. Transformational leadership was a significant predictor of change readiness (β =.17, P <.05). Conclusion It is recommended that laboratory leaders use transformational leadership or situational leadership to improve followers' affective commitment to change and reduce followers' continuance commitment to change, thus improving commitment to continuous improvement. Leaders should also limit passive-avoidant behavior. [ABSTRACT FROM AUTHOR]

Neurodegenerative disorders (NDs) represent a group of different diseases characterized by the progressive degeneration and death of the nervous system's cells. The diagnosis is challenging, especially in the early stages, due to no specific clinical signs and symptoms. In this context, laboratory medicine could support clinicians in detecting and differentiating NDs. Indeed, biomarkers could indicate the pathological mechanisms underpinning NDs. The ideal biofluid for detecting the biomarkers of NDs is cerebrospinal fluid (CSF), which has limitations, hampering its widespread use in clinical practice. However, intensive efforts are underway to introduce high-sensitivity analytical methods to detect ND biomarkers in alternative nonivasive biofluid, such as blood or saliva. This study presents an overview of the ND molecular biomarkers currently used in clinical practice. For some diseases, such as Alzheimer's disease or multiple sclerosis, biomarkers are well established and recommended by guidelines. However, for most NDs, intensive research is ongoing to identify reliable and specific biomarkers, and no consensus has yet been achieved. [ABSTRACT FROM AUTHOR]

Introduction: A molecular diagnostic laboratory is the cornerstone of Coronavirus Disease-2019 (COVID-19) disease diagnosis, as the patient's treatment and management protocol depend on molecular results. Therefore, the laboratory conducting these tests must adhere to quality management process to increase the accuracy and validity of the generated reports. Rajiv Gandhi Super Speciality Hospital established its molecular diagnostic set-up at the beginning of the pandemic. Hence, this study aims to generate quality management data to help improve weak points. Aim: To assess the quality management system for COVID-19 diagnosis. Materials and Methods: This retrospective observational study was conducted at Rajiv Gandhi Super Speciality Hospital in Delhi, India. A total of 14,561 samples were collected over six months, from February 2021 to July 2021. Data from all samples received during this period for COVID-19 Reverse-Transcriptase Polymerase Chain Reaction (RT-PCR) testing were included. Data were retrospectively collected from the electronic Laboratory Information Management System (LIMS). Quality variables were analysed over six months from July to December 2021 and classified into preanalytical, analytical, and postanalytical variables. Quality Indicators (QIs) were selected from a common model of QIs set by the International Federation of Clinical Chemistry and Laboratory Medicine. The results were presented in percentages, and descriptive statistics were analysed using Statistical Package for Social Sciences (SPSS) software. Results: During the six-month study period, the molecular laboratory received 14,561 samples. Among the preanalytical variables, sample leakage was the most common cause of sample rejection (134 samples, 0.92%), followed by the non generation of Specimen Referral Form (SRF) identification (76 samples, 0.52%), and non compliance with triple packaging (44 samples, 0.3%). Other preanalytical aspects assessed included incomplete patient identification (17 samples, 0.11%), insufficient sample quantity (12 samples, 0.08%), missing forms/samples (7 samples, 0.04%), samples in the wrong vials/empty Viral Transport Media (VTM) tubes (5 samples, 0.03%), and incomplete LIMS entry (2 samples, 0.01%). Internal Quality Control (QC) was not obtained in 55 samples (0.37%), and two incidents of cross-contamination resulted in false-positive results. Among the postanalytical factors, 11 samples (0.07%) could not be dispatched within the stipulated time frame. Conclusion: The assessment of the quality management system revealed some areas for improvement, emphasising the importance of adhering to QC processes for the smooth operation of diagnostic laboratories, especially those involved in critical reporting. The assessment of QIs helped monitor laboratory parameters effectively. [ABSTRACT FROM AUTHOR]

A mass spectrometry (LC‒MS/MS)-based interlaboratory comparison study was performed for nine steroid analytes with five participating laboratories. The sample set contained 40 pooled samples of human serum generated from preanalyzed leftovers. To obtain a well-balanced distribution across reference intervals of each steroid, the leftovers first underwent a targeted mixing step. All participants measured a sample set once using their own multianalyte protocols and calibrators. Four participants used in-house developed measurement platforms, including IVD-CE certified calibrators, which were used by three participants; the 5th lab used the whole LC‒MS kit from an IVD manufacturer. All labs reported results for 17-hydroxyprogesterone, androstenedione, cortisol, and testosterone, and four labs reported results for 11-deoxycortisol, corticosterone, cortisone, dehydroepiandrosterone sulfate (DHEAS), and progesterone. Good or acceptable overall comparability was found in Bland‒Altman and Passing‒Bablok analyses. Mean bias against the overall mean remained less than ±10 % except for DHEAS, androstenedione, and progesterone at one site and for cortisol and corticosterone at two sites (max. −18.9 % for androstenedione). The main analytical problems unraveled by this study included a bias not previously identified in proficiency testing, operator errors, non-supported matrix types and higher inaccuracy and imprecision at lower ends of measuring intervals. This study shows that intermethod comparison is essential for monitoring the validity of an assay and should serve as an example of how external quality assessment could work in addition to organized proficiency testing schemes. [ABSTRACT FROM AUTHOR]

Background: On Friday 14 May 2021, the Health Service Executive (HSE) was subjected to a serious cyberattack on their information technology (IT) infrastructure. Healthcare workers lost access to HSE-provided clinical and non-clinical IT systems, including laboratory systems. Aim: The aim of this national survey was to capture Laboratory Medicine's response across the Republic of Ireland during the HSE cyberattack. Method: An electronic survey developed using Microsoft Forms® was emailed on 24 September 2021 to 58 local representatives of the PeriAnalytic and Laboratory Medicine Society (PALMSoc). Results: The survey was sent to 43 clinical laboratories across the Republic of Ireland. A total of 41 responses from 43 laboratories across all laboratory disciplines were received (95% response rate). From these, 55% did not have access to a functioning LIS, with 56% of these not having access to a LIS for greater than 2 weeks. A decrease in specimen requests received during this period was reported by 74% of laboratories, with 32% experiencing a reduction that lasted in excess of one month. Over half of the laboratories (55%) experienced a reduction of > 30% in requests, indicating that clinicians stopped investigating patients (87% reduction in primary care), further escalating the disruption to healthcare. Conclusion: The cyberattack burdened the HSE and laboratories at a time when healthcare staffs were coming to terms with the impact of the COVID-19 pandemic. Despite this, the survey confirms the agility of laboratory staff in meeting the demands placed on it during this time. [ABSTRACT FROM AUTHOR]

The document discusses the impact of a ransomware cyber-attack on the University Hospital Centre Zagreb in Croatia, which resulted in the shutdown of all hospital IT systems, including laboratory services. The laboratory staff had to quickly implement emergency protocols to ensure uninterrupted service, such as accepting handwritten requests and prioritizing critical samples. It took over a month to fully recover from the cyber-attack, prompting the institution to enhance its emergency response protocols and cyber-security measures. The experience serves as a reminder of the importance of preparedness planning and cyber-security in medical laboratories. [Extracted from the article]

Serological detection of hepatitis B virus markers plays a vital role in the diagnosis, treatment, prognosis, and therapeutic surveillance of hepatitis B. To compare the diagnostic performance of Autolumo A2000Plus and Abbott Architect i2000 systems in the detection of hepatitis B infection markers. A total of 6 HBV seroconversion panels and 743 participants were enrolled in this study, including 383 HBV-infected patients and 360 healthy adults. Clinical diagnostic information, laboratory results, and HBV genotyping were collected to evaluate the diagnostic performance of the A2000Plus and i2000 systems in detecting HBV infection markers. The results showed that the total percent agreement of HBV markers was all >90 % in both detection systems among the six seroconversion panels and 743 serum samples from the population. The χ2 values of the Chi-square test among hepatitis B virus serological markers in both analyzers were between 550.7 and 743.0, p

The International Federation of Clinical Chemistry and Laboratory Medicine (IFCC) has formed the Emerging Technologies Division (ETD) to guide the implementation of emerging technologies (ETs) in laboratory medicine. The IFCC-ETD has developed committees and working groups to implement projects in three areas: clinical need, technology forecasting and readiness, and implementation processes. This special issue of Clinical Chemistry and Laboratory Medicine showcases the work of the IFCC-ETD over the past six years, with articles focusing on clinical need, technology advancements, and implementation management. Moving forward, the IFCC-ETD aims to define clinical needs, establish infrastructure, integrate quality programs, and promote global collaboration to effectively address unmet clinical needs and improve patient outcomes. [Extracted from the article]

The article discusses the use of generative artificial intelligence (AI) in reporting the performance of laboratory biomarkers. The authors highlight the increasing use of AI in healthcare and laboratory medicine but also raise concerns about its integration into clinical reasoning based on laboratory data. The authors conducted a study to assess the state-of-the-art of commonly used generative AI tools for providing up-to-date results on the diagnostic performance of three biomarkers. The results showed a large heterogeneity in the responses provided by the AI tools, indicating that the use of generative AI for laboratory experts, clinicians, and patients seeking information on the accuracy of laboratory tests is still questionable. [Extracted from the article]

Copyright of Journal of Modern Laboratory Medicine is the property of Journal of Modern Laboratory Medicine Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Benign paroxysmal positional vertigo (BPPV) represents the most frequent cause of peripheral vertigo. In most cases, it is successfully treated using the canalith repositioning procedure, but it is often followed by continuous lightheadedness in the absence of vertigo or nystagmus (residual dizziness, RD). Our aim is to describe the clinical effectiveness and the urine metabolomics profile of treating these patients with polyphenol compound supplementation. We enrolled 30 patients reporting RD after BPPV of the posterior semicircular canal (PSC) successfully treated using the Semont maneuver. Supplementation with a polyphenol compound was administered for 60 days, and patients were evaluated after 30 and 60 days of treatment using self-administered questionnaires (Visual Analog Scales for Dizziness and Nausea, Dizziness Handicap Inventory, DHI) and urine metabolomics analysis performed using 1H-NMR spectroscopy and multivariate followed by univariate analysis. Most patients reported excellent or good efficacy in the treatment of RD with a significant decrease in VAS and DHI values. The metabolomics analysis identified six significant metabolites related to the treatment, namely 1-methylnicotinamide, anserine, hippurate, lysine, methyl succinate and urea, indicating the inflammatory activities and antioxidant properties of the polyphenol compound. These preliminary data suggest that supplementation with a polyphenol compound could induce some metabolic changes that can help in recovery from RD. However, future steps will require confirmation with a more significant cohort of patients and an extension of the metabolomics evaluation to other problems concerning the different clinical aspects of BPPV, such as the high rate of relapse. [ABSTRACT FROM AUTHOR]

Background and Aims: Artificial intelligence (AI) has emerged as a transformative force in laboratory medicine, promising significant advancements in healthcare delivery. This study explores the potential impact of AI on diagnostics and patient management within the context of laboratory medicine, with a particular focus on low‐ and middle‐income countries (LMICs). Methods: In writing this article, we conducted a thorough search of databases such as PubMed, ResearchGate, Web of Science, Scopus, and Google Scholar within 20 years. The study examines AI's capabilities, including learning, reasoning, and decision‐making, mirroring human cognitive processes. It highlights AI's adeptness at processing vast data sets, identifying patterns, and expediting the extraction of actionable insights, particularly in medical imaging interpretation and laboratory test data analysis. The research emphasizes the potential benefits of AI in early disease detection, therapeutic interventions, and personalized treatment strategies. Results: In the realm of laboratory medicine, AI demonstrates remarkable precision in interpreting medical images such as radiography, computed tomography, and magnetic resonance imaging. Its predictive analytical capabilities extend to forecasting patient trajectories and informing personalized treatment strategies using comprehensive data sets comprising clinical outcomes, patient records, and laboratory results. The study underscores the significance of AI in addressing healthcare challenges, especially in resource‐constrained LMICs. Conclusion: While acknowledging the profound impact of AI on laboratory medicine in LMICs, the study recognizes challenges such as inadequate data availability, digital infrastructure deficiencies, and ethical considerations. Successful implementation necessitates substantial investments in digital infrastructure, the establishment of data‐sharing networks, and the formulation of regulatory frameworks. The study concludes that collaborative efforts among stakeholders, including international organizations, governments, and nongovernmental entities, are crucial for overcoming obstacles and responsibly integrating AI into laboratory medicine in LMICs. A comprehensive, coordinated approach is essential for realizing AI's transformative potential and advancing health care in LMICs. [ABSTRACT FROM AUTHOR]

Objectives: Although diversity has been demonstrated to benefit research groups, women remain underrepresented in most scientific disciplines, including Laboratory Medicine and Clinical Chemistry. In order to promote diversity and equality in scientific communities, understanding the gender distribution of authorship is crucial. Methods: This study included a total of 30,268 Web of Science-listed Clinical Chemistry and Laboratory Medicine publications from the United States of America, Canada, and the member countries of the European Federation of Clinical Chemistry and Laboratory Medicine from 2005 to 2022. In addition to the publication productivity of female and male authors over time, gender-specific publication characteristics and country-specific gender distributions of authorships were examined. Results: Overall, publications with female first authors increased by 49 % between 2005 and 2022, averaging 42 % female first authors. Eastern Europe (60 %) and Southern Europe (51 %) had particularly high proportions of female first authors. While female last authorship was the most predictive of female first authorship, with an odds ratio of 2.01 (95 % CI: 1.91–2.12, p

This paper provides information on the significance of environmental sustainability and the potential benefits of implementing green laboratory processes. Sustainability is a broad concept that includes goals such as conservation of natural resources, energy efficiency, waste management, and reducing environmental footprints. Green laboratories strive to minimise environmental footprints by embedding sustainability principles into their everyday practices. This involves improvements in energy consumption, water usage, chemical waste reduction, and recycling, ultimately, as well as lower waste disposal costs. Implementing green laboratory approaches provides many benefits, such as a smaller environmental footprint, increased energy efficiency, water conservation, and cost savings. Moreover, a rational test ordering process can effectively contribute to reducing environmental impacts in medical laboratories. Rational test ordering provides cost-effectiveness and reduces the carbon footprint. Establishing a green and sustainable laboratory culture in medical laboratories requires a permanent organisation in where all personnel participate. Training of the hospital management teams, clinicians, and laboratory professionals is a vital point. Methodology and quality indicators should be defined by international and national laboratory associations within the framework of a green and sustainable laboratory plan, and data should be collected. In conclusion, adopting green laboratory practices reduces environmental impacts, saves costs, and accelerates innovation processes. Setting quality targets and rational test ordering practices are also essential for sustainability. Applying sustainability principles in laboratory workplaces is an important step towards protecting the environment and leaving a more liveable world for future generations.

Abstract Background Medical educators seek innovative ways to engage learners efficiently and effectively. Gamification has been explored as one way to accomplish this feat; however, questions remain about which contexts gamification would be most useful. Time constraints and student interest present major barriers for teaching laboratory medicine to students. This study aims to compare two versions of an interactive online module, one gamified and one not, for teaching laboratory medicine concepts to pre-clinical medical students. Methods First-year medical students reviewed either a gamified or non-gamified version of an interactive online module in preparation for an in-person flipped classroom session on Laboratory Medicine. Learning theory guided the design of the modules and both contained identical content, objectives, and structure. The “gamified” module included the additional elements of personalization, progress meters, points, badges, and story/role play. After reviewing the module, students completed an anonymous knowledge check and optional survey. Results One hundred seventy-one students completed the post module knowledge check as assigned (82 gamified, 89 non-gamified). Knowledge check scores were higher for the students who reviewed the gamified module (p

Liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS) has become a routine clinical application, allowing for the measurement of various analytes such as drugs, hormones, and newborn screening. However, there are still challenges in implementing LC-MS/MS in clinical laboratories, including limited throughput, manual post-analytical processing, lack of 24/7 service support, and the need for specialized training. Roche Diagnostics is working on incorporating automated LC-MS/MS into their Serum Work Area, which would allow for random access testing and potentially replace immunoassay as the first-tier testing principle for certain applications. This development has the potential to greatly impact the clinical management of epilepsy and other conditions. [Extracted from the article]

The article discusses the clinical assessment of the Ortho VITROS SARS-CoV-2 antigen chemiluminescence immunoassay for the diagnosis of COVID-19. The study evaluated the performance of the immunoassay in detecting the SARS-CoV-2 virus in patients with suspected COVID-19. The results showed that the immunoassay had good diagnostic accuracy and sensitivity, especially in patients with high viral load. The study suggests that the immunoassay could be a fast, efficient, and relatively inexpensive method for identifying individuals with COVID-19. [Extracted from the article]

Laboratory medicine has undergone a deep and multifaceted revolution in the course of human history, in both organizational and technical terms. Over the past century, there has been a growing recognition of the need to centralize numerous diagnostic activities, often similar or identical but located in different clinical departments, into a common environment (i.e., the medical laboratory service), followed by a progressive centralization of tests from smaller laboratories into larger diagnostic facilities. Nevertheless, the numerous technological advances that emerged at the beginning of the new millennium have helped to create a new testing culture characterized by a countervailing trend of decentralization of some tests closer to patients and caregivers. The forces that have driven this (centripetal) counter-revolution essentially include a few key concepts, namely “home testing”, “portable or even wearable devices” and “remote patient monitoring”. By their very nature, laboratory medical services and remote patient testing/monitoring are not contradictory, but may well coexist, with the choice of one or the other depending on the demographic and clinical characteristics of the patient, the type of analytical procedure and the logistics and local organization of the care system. Therefore, this article aims to provide a general overview of patient self-testing, with a particular focus on portable and wearable (including implantable) devices.

The Welsh Transplantation and Immunogenetics Laboratory (WTAIL) is responsible for managing patient work-up for haematopoietic stem cell transplantation (HSCT), the only potentially curative option for many haematological and non-haematological conditions. Work-up requires regular communication between WTAIL and the transplanting clinicians, facilitated by weekly multidisciplinary team (MDT) meetings, to agree decisions and proceed through each work-up stage. Effective communication and minimising error are critical, as transplanting cells from a suboptimal donor could have severe or fatal consequences for the patient. We reviewed our HSCT patient management and identified issues including staff dissatisfaction with the inefficiency of the current (paper-based) system and concern about the potential for incidents caused by errors in manual transcription of patient information and tracking clinical decisions. Another driver for change was the COVID-19 pandemic, which prevented the usual face-to-face MDT meetings in which staff would show clinicians the paper records and reports; the shift to online MDT required new ways of sharing data. In this project we developed a new central reference point for our patient management data along with electronic patient summary sheets, designed with an eye to improving safety and efficiency. Over several improvement cycles we tested and refined the summary sheets with staff and clinicians and experimented with videoconferencing to facilitate data sharing. We conducted interviews with staff from which we concluded that the new process successfully reduced transcription and duplication and improved communication with the clinicians during the pandemic. Despite an increase in workload due to build-up of active patient work-up cases during the pandemic, staff reported that the new summaries enabled them to cope well. A key initiative was creation of a Task and Finish group that helped establish continual improvement culture and identified additional areas for improvement which have been followed up in further improvement projects.