Clinical chemistry and laboratory medicine最新文献

The first part of this Inter-Society Document describes the mechanisms involved in the development of cardiovascular diseases, particularly arterial hypertension, in adults and the elderly. It will also examine how consistent physical exercise during adolescence and adulthood can help maintain blood pressure levels and prevent progression to symptomatic heart failure. The discussion will include experimental and clinical evidence on the use of specific exercise programs for preventing and controlling cardiovascular diseases in adults and the elderly. In the second part, the clinical relevance of cardiac-specific biomarkers in assessing cardiovascular risk in the general adult population will be examined, with a focus on individuals engaged in sports activities. This section will review recent studies that suggest a significant role of biomarkers in assessing cardiovascular risk, particularly the presence of cardiac damage, in athletes who participate in high-intensity sports. Finally, the document will discuss the potential of using cardiac-specific biomarkers to monitor the effectiveness of personalized physical activity programs (Adapted Physical Activity, APA). These programs are prescribed for specific situations, such as chronic diseases or physical disabilities, including cardiovascular diseases. The purposes of this Inter-Society Document are the following: 1) to discuss the close pathophysiological relationship between physical activity levels (ranging from sedentary behavior to competitive sports), age categories (from adolescence to elderly age), and the development of cardiovascular diseases; 2) to review in detail the experimental and clinical evidences supporting the role of cardiac biomarkers in identifying athletes and individuals of general population at higher cardiovascular risk; 3) to stimulate scientific societies and organizations to develop specific multicenter studies that may take into account the role of cardiac biomarkers in subjects who follow specific exercise programs in order to monitor their cardiovascular risk.

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.

Objectives: This study investigates the application of 15 Quality Indicators (QIs) in clinical laboratories in Fujian Province, China, from 2018 to 2023. It identifies the main causes of laboratory errors and explores issues in the application of QIs, providing a reference for establishing provincial state-of-the-art and operational quality specifications (QSs).

Methods: All clinical laboratories in Fujian Province were organized to submit general information and original QIs data through the online External Quality Assessment (EQA) system of the National Clinical Laboratory Center (NCCL) for a survey of 15 QIs. Data from 2018 to 2023 were downloaded for statistical analysis, and the current QSs for the 15 QIs in Fujian Province were compared and analyzed with those published by the International Federation of Clinical Chemistry and Laboratory Medicine (IFCC) Working Group on Laboratory Errors and Patient Safety (WG-LEPS).

Results: QIs data from 542 clinical laboratories were collected. The survey on data sources showed that the number of laboratories recording QIs data using Laboratory Information Systems (LIS) increased annually, but the growth was modest and the proportion was less than 50 %. Among the laboratories using LIS to record QIs data, 133 continuously participated in this survey for six years, reporting different QIs. Over the six years, all reported QIs showed significant improvement or at least remained stable. The best median Sigma (σ) metrics were for the percentage of critical values notification and timely critical values notification, reaching 6σ, followed by the percentage of incorrect laboratory reports, with σ metrics ranging from 4.9σ to 5.1σ. In contrast, the percentage of tests covered by internal quality control (IQC) (1.5σ-1.7σ) and inter-laboratory comparison (0.1σ) remained consistently low. Compared to the QSs published by IFCC WG-LEPS, the QSs for the 15 QIs in Fujian Province in 2023 were stricter or roughly equivalent, except for the percentage of incorrect laboratory reports (Fujian Province: 0-0.221, IFCC WG-LEPS: 0-0.03).

Conclusions: 1. The application of QIs has significantly improved the quality of testing in clinical laboratories in Fujian Province, but the percentage of tests covered by IQC and inter-laboratory comparison remain low; 2. Effective application of QIs requires the establishment of comprehensive LIS, unified calculation standards, and other supporting measures.

Objectives: Fecal calprotectin (FC) serves as a non-invasive marker for the assessment of gut inflammation in patients with inflammatory bowel disease (IBD). Laboratory measurements are usually performed with immunologic methods like enzyme-linked immunosorbent assay. Recently, quantitative home tests based on the lateral flow technology with smartphones as read-out devices have been developed. We compared the quantitative and qualitative performance of the quantitative lateral flow home test Preventis SmarTest^® Calprotectin Home and the immunological test used in our laboratory (Eurospital Calprest^® Turbo).

Methods: Fourty-five routine samples were analyzed in parallel with both tests according to the manufacturer's instructions. The read-out of the home test was performed with two smartphones (Apple iPhone 14 Pro and Samsung Galaxy XCover 5). The qualitative interpretation (positive, negative, borderline) was conducted using the cut-offs provided by the manufacturers.

Results: Statistically significant correlations with the laboratory standard method were observed for both smartphones (Spearman's rho 0.703 and 0.715, all p<0.005). The home test showed systematically higher concentrations compared to the routine assay. We found minimal qualitative agreement between the two tests (Cohen's kappas (κ)=0.323 and 0.300; p=0.003 and 0.005) showing a lower rate of positives with the home test. Both used smartphones showed good quantitative and qualitative agreement.

Conclusions: The tests are quantitatively not interchangeable. However, the home test may be applicable for the serial follow-up management of patients with IBD. The higher rate of samples classified as negative with the home test may lead to an underestimation of affected patients.

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).

Methods: Ninety EuBIVAS non-diabetic subjects (52F, 38M) from five countries had fasting HOMA-IR and QUICKI calculated from plasma glucose and insulin samples collected concurrently on 10 weekly occasions. The within-subject (CV_I) and between-subject (CV_G) BV estimates with 95 % CIs were obtained by CV-ANOVA after analysis of trends, variance homogeneity and outlier removal.

Results: The CV_I of HOMA-IR was 26.7 % (95 % CI 25.5-28.3), driven largely by variability in plasma insulin and the CV_I for QUICKI was 4.1 % (95 % CI 3.9-4.3), reflecting this formula's logarithmic transformation of glucose and insulin values. No differences in values or BV components were observed between subgroups of men or women below and above 50 years.

Conclusions: The EuBIVAS, by utilising a rigorous experimental protocol, has produced robust BV estimates for two of the most commonly used markers of insulin resistance in non-diabetic subjects. This has shown that HOMA-IR, in particular, is highly variable in the same individual which limits the value of single measurements.