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R language has gained traction in laboratory medicine for its statistical power and dynamic tools like RMarkdown and RShiny. However, there is limited literature summarizing R packages and functions tailored for laboratory medicine, making it difficult for clinical laboratory workers to access these tools. Additionally, varying algorithms across R packages can lead to inconsistencies in published reports. This review addresses these challenges by providing an overview of R’s evolution and its key features, followed by a summary of statistical methods implemented in R, including platform comparisons, precision verification, factor analysis, and the establishment of reference intervals (RIs). We also highlight the development and validation of predictive models using techniques such as linear and logistic regression, decision trees, random forests, support vector machines, naive Bayes, K-Nearest Neighbors, k-means clustering, and backpropagation neural networks – all implemented in R. To ensure transparency and reproducibility in research, a checklist is provided for authors publishing papers using R for data analysis in laboratory medicine. In the final section, the potential of R in big data analytics is explored, focusing on standardized reporting through RMarkdown and the creation of user-friendly data visualization platforms with RShiny. Moreover, the integration of large language models (LLMs), such as ChatGPT, is discussed for their benefits in enhancing R programming, automating reporting, and offering insights from data analysis, thus improving the efficiency and accuracy of laboratory data analysis.

Introduction To analyze the available evidence about the correlation between the presence of detectable amounts of clostebol metabolites in urine and the transdermal or transmucosal contact of clostebol. Content A systematic review was performed. A systematic search was conducted in PubMed/MEDLINE, Scopus, Web of Science and the Cochrane library databases. Criteria for including studies were clinical studies reporting: (i) adult subjects; (ii) detection of urine clostebol metabolites derived from transdermal or transmucosal contact of clostebol. Summary Seven papers pertinent to our questions were found: 3 case reports, one experimental study and 3 case reports with an experimental section for a total of 32 subjects. The median concentration of urine clostebol’s metabolite 4-chloro-androst-4-en-3α-ol-17-one, M1 was 0.5 ng/mL (range 0.086–4.000 ng/mL; 25%–75 % IQ: 0.5–0.9 ng/mL) and 8.1 ng/mL (range 1.0–36.6 ng/mL; 25%–75 % IQ: 2.8–22.0 ng/mL), in subjects with indirect and direct exposure of clostebol, respectively (p=0.005). Outlook We found consistent data that the detection of M1 in urine can be reconcilable with a transdermal or transmucosal contact of clostebol. In the cases of indirect exposure, the urine concentrations of M1 seem to be far lower than the concentrations found in case of direct exposure.

After the dissemination of a manifesto for the implementation of value-based laboratory medicine (VBLM) and a Strategic Conference dedicated to this issue, a novel initiative of the European Federation of Clinical Chemistry and Laboratory Medicine (EFLM) is to be initiated with the objective of developing a “value-score for clinical laboratories”. The initial proposition of this value score should be based on the following features: (1) traceability throughout the total testing process (TTP); (2) level of automation (number of manual procedures); (3) laboratory performance on quality indicators; (4) data management and quality of laboratory information; and (5) interaction with clinicians and multidisciplinary initiatives. This paper represents a first conceptualization of the value-based score, which should facilitate a more effective work of the new EFLM Committee (C-VS) to better define the characteristics that can add value to clinical laboratories and allow a benchmark based on effective indicators.

Laboratory medicine is faced with rapid developments in data exchange, secondary use of data and artificial intelligence. Safe exchange of laboratory data requires a suitable terminology standard. NPU, LOINC and SNOMED CT are increasingly used for this purpose, but none of these terminology standards can currently accommodate safe exchange across the full spectrum of conventional laboratory data. Furthermore, rapid technological advances in, amongst others, the ‘omics’ area will enforce a shift towards precision diagnostics. These emerging technologies demand an appropriate and future-proof terminology standard. Given the current and future challenges in laboratory terminologies, we here present a concept for digital metrology in laboratory medicine. Terminology standards used in laboratory medicine should be adjusted to the current state of science to allow safe data exchange and interpretation. Essential test information entails the full spectrum of pre-pre-analysis to post-post-analysis. Major improvements needed include sufficient coding detail for the molecular form of the measurand and information on metrological traceability. Furthermore, especially given the advances in precision diagnostics, it will become essential to indicate interrelationships between measurands. Herefore, integration with established taxonomies would allow improved identification of interrelationships between measurands and linkage with scientific information for multidisciplinary data science. Hence, laboratory data can further gain in specificity and value. The time has come to lay the basis for safe data exchange in the era of precision diagnostics, with a global focus. A consensus for digital metrology in laboratory medicine will be essential to move forward with health data exchange within Europe and beyond.

The Joint Committee for Traceability in Laboratory Medicine (JCTLM) database represents a valuable resource for implementing metrological traceability in laboratory medicine. Three main database users can be identified: (a) in vitro diagnostic (IVD) manufacturers, using the database information for meeting ISO 17511:2020 requirements, (b) laboratory professionals, for defining the quality of their test results, and (c) providers of higher-order certified reference materials (CRM) and reference measurement procedures (RMP), to be helped in improving the suitability of their products, if needed, and assistance with prioritizing their future efforts. In this report, we focus on the utility of the information provided (or still not provided) by the JCTLM database on this last category of users. Two types of information are discussed: (a) the use of listed CRMs as common calibrators intended to transfer trueness from the top of the calibration hierarchy to commercial IVD calibrators, and (b) the measurement uncertainty (MU) of CRM certified values and the reproducibility characteristics of RMP measurements, considering their impact on the MU of clinical samples, when compared to maximum allowable MU (MAU). The discussion output is a recommendation for suppliers to respond urgently to the need to provide higher-order references (CRMs and/or RMPs) for a number of key analytes that are currently lacking or do not yet fully meet quality criteria related to: (a) commutability assessment, (b) contribution to MAU fulfilment, and (c) demonstration of the extent of equivalence to an already listed higher-order reference.

Amongst the main perspectives when evaluating the results of medical studies are statistical significance (following formal statistical testing) and clinical significance. While statistical significance shows that a factor’s observed effect on the study results is unlikely (for a given alpha) to be due to chance, effect size shows that the factor’s effect is substantial enough to be clinically useful. The essence of statistical significance is “negative” - that the effect of a factor under study probably did not happen by chance. In contrast, effect size and clinical significance evaluate whether a clinically “positive” effect of a factor is effective and cost-effective. Medical diagnoses and treatments should never be based on the results of a single study. Results from numerous well-designed studies performed in different circumstances are needed, focusing on the magnitude of the effects observed and their relevance to the medical matters being studied rather than on the p-values. This paper discusses statistical inference and its relevance to clinical importance of quantitative testing in clinical laboratories. To achieve this, we first pose questions focusing on fundamental statistical concepts and their relationship to clinical significance. The paper also aims to provide examples of using the methodological approaches of superiority, equivalence, non-inferiority, and inferiority studies in clinical laboratories, which can be used in evidence-based decision-making processes for laboratory professionals.

Objectives Many patients with sex chromosome abnormalities (SCAs) are diagnosed late in life or remain undiagnosed, leading to delayed or inadequate medical intervention and care. This study aimed to develop a reliable, rapid and cost-effective test for identifying SCAs using a blood sample – an essential step toward establishing a neonatal screening program. Methods A total of 360 blood samples (180 SCA patients, and 180 controls) were obtained from four cross-sectional studies of adult patients with SCAs and age-matched controls. Informed consent was collected, and all procedures followed the Declaration of Helsinki. Multiplex quantitative fluorescence polymerase chain reaction (QF-PCR) utilizing short tandem repeat (STR) and X-linked segmental duplication (SD) markers was performed. Results were analyzed using an automated algorithm. Deviant results were manually reviewed to differentiate errors in the PCR process from those in automated data analysis. Results Following automated data analysis of QF-PCR results, the method accurately identified 174 SCA patients (sensitivity: 96.7 %) and 171 controls (specificity: 95.0 %). Mosaic karyotypes were particularly challenging to diagnose. Manual reanalysis of the QF-PCR results corrected all false positives, achieving 100 % specificity. Conclusions This method is promising for reliable SCA detection in blood samples, offering cost-effectiveness and scalability. The specificity following automated data analysis was not satisfactory. The underlying PCR technique, however, demonstrated 100 % specificity, indicating that refining the automated analysis algorithm would significantly reduce false positive results. With further refinements, we believe this test would be highly suitable for further evaluation in a newborn screening setting.

Objectives The insulin-like growth factors (IGFs) regulate growth in humans. IGF-I and IGF binding protein (IGFBP)-3 are biomarkers in children with growth disorders. We investigate a targeted proteomics method for absolute quantitation of eight IGF protein family members in human serum, including the peptide hormones IGF-I and -II, and the six binding proteins IGFBP-2, -3, -4, -5, -6 and acid labile subunit (ALS). Methods Serum preparation was optimized for targeted proteomics of IGF related proteins on a clinical LC-MS/MS platform (UHPLC coupled with Triple-Q MS). We created quality controls, standards and internal standards and 289 serum samples from healthy children and adolescents were measured in ten batches over two months. The method was compared to WHO reference standards, clinical and research immunoassays, and relative proteomics profiling. Results The sensitivity and reproducibility were sufficient for most but not all IGF protein family members. Targeted proteomics correlated well with clinical immunoassays for IGF-I (R 2 =0.88) and for IGFBP-3 (R 2 =0.46), (p<0.001). The correlation between targeted proteomics and non-clinical immunoassays for IGF-II, IGFBP-2, -4, -5, -6 and ALS varied between proteins. Conclusions We present a method for parallel quantification of IGF-I, IGFBP-3, 5 and ALS for clinical verification studies, whereas targeted proteomics of the five remaining IGF related proteins (IGF-II, IGFBP-2, -4, and -6) require further examination. The sensitivity of our new IGF-I method suggests a possible diagnostic role for targeted proteomics of IGF-I in the management of children with extremely low levels of circulating IGF-I.

Objectives Urine albumin is a key biomarker utilized for diagnosis and monitoring progression of chronic kidney disease (CKD). These characteristics highlight the importance urine albumin serves in patient management. However, laboratory results are confounded by a lack of standardization where results may exceed 40 % difference between diagnostic platforms. This presents serious issues since current guideline clinical decision points are fixed values and misclassification may occur between laboratory methods. Therefore, standardization is needed for urine albumin measurements. Methods A liquid chromatography tandem mass spectrometry (LC-MS/MS) reference measurement procedure (RMP) was developed. This RMP employed proteolysis using trypsin and examined six peptides specific to human serum albumin. The National Institute of Standards and Technology 2925 reference material was used to value assign calibrators. To improve imprecision and accuracy, all samples were run in quadruplicate. Urine from 98 patient specimens was analyzed. Results RMP final results consisted of averaging four peptide transitions, yielding a 20-day coefficient of variation (CV) of <3.0 %. Factors considered in assigning RMP overall uncertainty included specimen and internal standard pipetting, calibration material, and LC-MS/MS imprecision. This RMP was compared to the Roche Cobas and Siemens Dimension Vista urine albumin assays and was found to have a −9.9 and 20.1 % bias, respectively. This RMP was found to have equivalent results to two other RMPs in a previous study. Conclusions This RMP demonstrated excellent imprecision, achieving an overall CV of 2.8 % and meeting the CV ≤6.2 % performance specification required for standardizing urine albumin measurements in clinical laboratories.

Objectives Patient risk management is an essential subject for clinical laboratory which is now central in main international laboratory quality standards (e.g., ISO 15989:2022; ISO 22367:2020 and CLSI EP23 2nd ). Risk analysis is a necessary part of risk management which requires categorizing the severity of patient harm from a laboratory failure. However, this subjective task is not currently the subject of any recommendation and little literature about this topic. To remedy that, we conducted an international survey of medical biology professionals, asking them to rate a panel of 20 analytes the harm potentially induced by an erroneous reported result. Methods The survey was published by Bio-Rad ® to their customers base and the public with a dedicated webpage. The survey proposes to assign for the submitted analytes the amount of harm among five pre-defined categories of harm: negligible, minor, serious, critical, and catastrophic. Participants were also asked to specify their demographic characteristics. Results The questionnaires of 267 respondents coming from 43 countries were analyzed to allocate for each analyte a specific harm category. We highlight that almost all parameters (19/20) were categorized with at least a serious harm category and that none were associated with the negligible category. Conclusions This study constitutes the first international attempt to investigate how the laboratory community thinks about patient harm from an erroneous reported result. These results provide support to document the laboratory risk management policy which must now be centered on patient risk.

Objectives We examined the magnitude of transcription errors in lipid variables in the VIPVIZA study and assessed whether education among the research personnel reduced the error frequency at follow-up. We also examined how the errors affected the SCORE2 risk prediction algorithm for cardiovascular disease, which includes lipid parameters, as this could lead to an incorrect treatment decision. Methods The VIPVIZA study includes assessment of lipid parameters, where results for total cholesterol, triglycerides, HDL cholesterol, and calculated LDL cholesterol are transcribed into the research database by research nurses. Transcription errors were identified by recalculating LDL cholesterol, and a difference>0.15 indicated a transcription error in any of the four lipid parameters. To assess the presence of risk category misclassification, we compared the individual’s SCORE2 risk category based on incorrect lipid levels to the SCORE2 categories based on the correct lipid levels. Results The transcription error frequency was 0.55 % in the 2019 VIPVIZA research database and halved after the educational intervention to 0.25 % in 2023. Of the 39 individuals who had a transcription error in total or HDL cholesterol (with the possibility of affecting the SCORE2 risk category based on non-HDL cholesterol), six individuals (15 %) received an incorrect risk category due to the error. Conclusions Transcription errors persist despite digitalisation improvements. It is essential to minimise transcriptions in fields outside the laboratory environment, as we observed that critical decisions also rely on accurate information such as the SCORE2-risk algorithm, which is dependent on lab results but not necessarily reported by the laboratory.

Objectives To compare clinical laboratory workflows for the assessment of androgens in men, focusing on total testosterone (T), sex hormone-binding globulin (SHBG) and free T, in clinical laboratories throughout Europe. Methods An internet-based survey that included questions related to pre-analytical, analytical and post-analytical phases of androgen measurements was distributed between December 2022 and December 2023 by clinical laboratory/chemistry and endocrine societies. A total of 124 unique records from clinical laboratories in 27 European countries were analyzed. Results Pre-analytical requirements for total T are subject to improvement as less than half of clinical laboratories recommended adequate morning sampling time and/or sampling in a fasting state. Total T was predominantly quantified using enzyme-linked immunoassay (IA) on automated platforms, with only one in four centers using mass spectrometry (MS), while SHBG was exclusively measured by IA. Additionally, free T was used by a majority of clinical laboratories, mainly reported as approximation by calculation of free T (cFT) using the Vermeulen formula. Generally, age-stratification was the preferred means of reporting reference ranges for total T, SHBG and cFT. However, considerate variability was observed in reported lower and upper limits, leading to the necessity of interpreting test results against assay-specific reference ranges, thereby hindering comparability of results between clinical laboratories. Conclusions Our survey highlights significant inter-laboratory variability for the assessment of androgen status in men, implying non-commutability of clinical test results between different centers. In addition, we observed poor adherence to pre-analytical recommendations. These findings advocate for continued harmonization efforts of measurement procedures for SHBG and total/free T.

Objectives The identification of reliable quality indicators (QIs) in the total testing process (TTP) is a pivotal step in quantifying laboratory service quality. This study comprehensively evaluated the performance quality and explored the factors affecting laboratory quality in Guangdong Province, China, by analyzing the results of QIs. Methods The Guangdong Clinical Laboratory Center organized an external quality assessment program for QIs, and the Clinet-EQA system was used to distribute questionnaires and collect data. The results of the QIs are expressed as percentages, sigma, or minutes. The optimum, desirable, and minimum quality specifications (QSs) were defined based on the percentiles of the QIs. Furthermore, the QIs were evaluated in different disciplines and hospital grades. Results A total of 335 laboratories in Guangdong Province reported complete data from 2020 to 2023, and QI performance progressively improved over the years. The performance of 11 QIs attained the minimum acceptable standard (sigma value ≥3), and most QIs across the diverse disciplines and hospital grades exhibited statistically significant differences. Compared to the QSs published by the International Federation of Clinical Chemistry and Laboratory Medicine (IFCC) Working Group on Laboratory Errors and Patient Safety (WG-LEPS), the QSs for the 15 QIs in Guangdong Province in 2023 were stricter or roughly equivalent, except for the percentage of intra-laboratory turnaround time for emergency potassium tests. Conclusions From 2020 to 2023, the QIs in the post-analytical phase achieved the best performance. It is essential for laboratories to reinforce the construction of their information infrastructure, thereby guaranteeing the accurate collection of reliable data and enabling effective long-term monitoring.

Objectives Evaluate the stability of 32 biochemical analytes in venous blood samples stored at 18–25 °C under different time delays prior to centrifugation. Methods A prospective study was conducted involving 33 healthy volunteers. Four venous blood samples were collected from each participant. One sample was designated as baseline and processed immediately according to the tube manufacturer’s guidelines for centrifugation and analysis. The remaining three samples were stored under predefined conditions and centrifuged at different time intervals before undergoing analysis. Results Acceptable stability over the maximum storage time of 8 h was observed for 25 of the analytes tested in this study. However, direct bilirubin became unstable at 6 h and triglycerides at 8 h of storage prior to centrifugation. Calcium, gamma-glutamyl transferase, glucose, inorganic phosphate and potassium were found to be unstable in serum after 4 h of delayed centrifugation. Conclusions A delay in centrifugation of samples affected the stability of several analytes evaluated in the study, resulting in changes in their concentration or integrity. The analytical results for these analytes cannot be considered reliable as they do not meet the standards required for clinical validation. This underscores the importance of following stringent pre-analytical protocols to maintain the accuracy and reliability of laboratory diagnostic results.

Objectives The Apollo study was designed to support the clinical performance verification of the adjusted cutoffs of the Elecsys ® β-Amyloid(1–42) (Aβ 42 ) cerebrospinal fluid (CSF) II, β-Amyloid(1–40) (Aβ 40 ) CSF, Phospho-Tau (181P) (pTau) CSF and Total-Tau (tTau) CSF immunoassays (Roche Diagnostics International Ltd) for measuring fresh CSF samples, and assess the concordance of the Elecsys CSF pTau/Aβ 42 , tTau/Aβ 42 and Aβ 42 /Aβ 40 ratios, as well as Aβ 42 alone, with amyloid positron emission tomography (PET) visual read status. Methods The primary study endpoint was to assess the concordance of the Elecsys CSF ratios and Aβ 42 alone with amyloid PET visual read status using fresh CSF samples collected from individuals with subjective cognitive decline or mild cognitive impairment, handled with a new routine-use pre-analytical procedure and measured with the Elecsys CSF immunoassays. The sample stability after 1- to 13-week storage at −20 °C was also investigated in an exploratory analysis. Results Of 108 screened individuals, 91 met the eligibility criteria, of whom 44.0 % were amyloid PET-positive and 56.0 % amyloid PET-negative. Positive percent agreement (PPA) and negative percent agreement, respectively, were 0.800 and 0.882 for pTau/Aβ 42 , 0.775 and 0.902 for tTau/Aβ 42 , and 0.950 and 0.824 for Aβ 42 /Aβ 40 . For Aβ 42 , PPA was 0.975 and negative likelihood ratio was 0.039. Overall, 33 samples (36.3 %) were frozen at −20 °C for 1–13 weeks. All concentration recoveries were within 100 ± 10 % when stored at −20 °C for ≤8 weeks. Conclusions Elecsys CSF ratios and Aβ 42 alone may be reliable alternatives to amyloid PET for identifying amyloid positivity in clinical practice.

Objectives Human tear analysis holds promise for biomarker discovery, but its clinical utility is hindered by the lack of standardized reference values, limiting interindividual comparisons. This study aimed at developing a protocol for normalizing metabolomic data from human tears, enhancing its potential for biomarker identification. Methods Tear metabolomic profiling was conducted on 103 donors (64 females, 39 males, aged 18–82 years) without ocular pathology, using the AbsoluteIDQ™ p180 Kit for targeted metabolomics. A predictive normalization model incorporating age, sex, and fasting time was developed to correct for interindividual variability. Key metabolites from six compound families (amino acids, biogenic amines, acylcarnitines, lysophosphatidylcholines, phosphatidylcholines, and sphingomyelins) were identified as normalization references. The approach was validated using Linear Discriminant Analysis (LDA) to test its ability to classify donor sex based on metabolite concentrations. Results Metabolite concentrations exhibited significant interindividual variability. The normalization model, which predicted metabolite concentrations based on a reference “concomitant” metabolite from each compound family, successfully reduced this variability. Using the ratio of observed-to-predicted concentrations, the model enabled robust comparisons across individuals. LDA classification of donor sex using acylcarnitine C4 achieved 78 % accuracy, correctly identifying 92 % of female donors. This approach outperformed traditional statistical and machine learning methods (Lasso logistic regression and Random Forest classification) in sex discrimination based on tear metabolomics. Conclusions This novel normalization protocol significantly improves the reliability of tear metabolomics by enabling standardized interindividual comparisons. The approach facilitates biomarker discovery by mitigating variability in metabolite concentrations and may be extended to other biological fluids, enhancing its applicability in precision medicine.

Objectives Medical biology is essential for diagnosing and monitoring cardio-reno-metabolic diseases. The EPI-CKD1 study utilizes data from Biogroup ® French laboratories to examine the burden of chronic kidney disease (CKD) and the effect of heart failure, and diabetes in an outpatient setting in order to address gaps in national databases that lack biological data. Methods All adults (≥18 years) with at least one blood creatinine test between January 1st of 2021, and June 30th of 2022 were included. Key biomarkers measured included serum creatinine, estimated glomerular filtration rate (eGFR), hemoglobin A 1c , B-type natriuretic peptide (BNP), NT-Pro BNP, and urinary albumin/creatinine ratio (uACR). Results Among a total of 4,061,208 adults with at least one blood creatinine test, 465,225 (11.5 %) had altered kidney function. Their mean age was 57.9 years (SD 18.8), with 56.7 % women. Diabetes was present in 8.3 %, and heart failure in 1.4 %. Altered kidney function standardized prevalence was estimated to 8.06 %, with an incidence of 5.10 %. Patients with end-stage CKD had an average of 7.9 eGFR measurements, compared to 2 for those with eGFR >60 mL/min/1.73 m 2 . Older age, diabetes, and heart failure were associated with an increased risk of eGFR <60 mL/min/1.73 m 2 . Conclusions The EPI-CKD1 study demonstrates the utility of Biogroup ® data for large-scale observational studies, offering precise, medically relevant insights on patients at cardio-renal risk. Future studies should focus on data enrichment and long-term follow-up to deepen understanding.

Objectives The stability of plasma samples for basic coagulation tests, prothrombin time (PT) and activated partial thromboplastin time (aPTT), has been widely studied. Recently, the Clinical and Laboratory Standards Institute (CLSI) updated its recommendations, extending the acceptable time frame for aPTT. These guidelines are based on experimental studies, which define limits according to different maximum permissible error (MPE) criteria. This study compiles raw data from 43 studies published over the last 30 years to develop a consensus instability equation that describes degradation independently of specific study parameters. Methods A critical literature review was performed by collecting studies that included experimental stability data for PT, aPTT and the main procoagulant factors. The raw data of percentage deviation (PD%), time, and seven classification variables related to sample collection and handling were analysed. A regression model through the origin was applied to derive global instability equations and to assess influencing variables. Results In frozen samples, PT and aPTT showed similar stability, with an average prolongation of 0.8 % per month. In non-frozen samples, tube handling affected stability more than storage temperature. The consensus equation for PT showed a linear average deterioration of 2.9 % per day, but model strength was limited. For aPTT, the consensus equation fitted better to a logarithmic decay model and predicted prolongations of 6.1 and 10 % at 6 and 24 h, respectively. Conclusions The consensus instability equations obtained in this review provide a robust model for assessing coagulation tests stability, aligning with expert recommendations. These equations improve the understanding of sample degradation and systematic error quantification.

Objectives To improve the accuracy of lymphocyte subsets counts, a traceable dual-platform extended PanLeucogating method (DPP) of absolute cell counts of lymphocyte subsets was introduced, and consistency was evaluated by comparing conventional single/dual-platform method with DPP. Methods The DPP for absolute lymphocyte subsets counts was established by multiplying the percentage of lymphocyte subsets in total white blood cells (WBC) measured by flow cytometer with the total WBC counts. DPP-R was defined as the use of the total WBC counts measured in reference laboratory that was traceable to reference method recommended by International Council for Standardization in Hematology (ICSH). When the total WBC counts measured in clinical laboratory were utilized, it was designated as DDP-C. The comparability of conventional single/dual-platform method and DPP-R was assessed using a total of 566 peripheral blood samples. Additionally, the inter-laboratory precision of the single-platform and the dual-platform method was compared based on data from China National External Quality AssessmentScheme (China NEQAS). Results The results of the DPP-R exhibited a robust linear correlation with conventional single/dual-platform method (r=0.9909 to 0.9973). However, notable proportional differences existed. The mean biases between DPP-R and conventional single/dual-platform method ranged from −0.0116 to 0.0714 (×10 9 /L). According to China NEQAS data, the robust coefficient of variations in dual-platform group were comparable to, or even marginally lower than, that of the single-platform groups. Conclusions The DPP-R was valuable for achieving the traceability of absolute enumeration of lymphocyte subsets, exhibited a strong correlation with conventional single/dual-platform method and could serve as a reference standard for assessing the accuracy of such detection. However, there existed bias between DPP-R and conventional single/dual-platform method, thus manufacturers should provide explicit statements for traceability of beads and standardize beads gating procedures or aspired sample volume.

Objectives We determined the efficacy of a high sensitivity cardiac troponin I (hs-cTnI) assay for newly derived 0 h and 0/2-h rule-out concentrations for myocardial infarction and determined the safety of incremental changes at low concentrations. Methods Consecutive, emergency department patients undergoing serial hs-cTnI testing on clinical indication were studied in the ‘Mindray hs-cTnI Assay Analytical and Clinical Evaluation for the Diagnosis and RIsk Assessment of Myocardial InfarctIon’ (MERITnI) trial. Primary safety outcome was the composite of cardiac death and MI at 30 days. Results In 1,556 patients (60.7 % male, 43.3 % White, 45.8 % Black. 34.8 % chest pain), 26.9 % patients had at least one hs-cTnI >99th percentile. 2.7 % had type 1 MI, 2.7 % type 2 MI, and 21.5 % non-MI myocardial injury. Single-sample MI rule-out using a normal ECG plus hs-cTnI of <2 ng/L (rounded) ruled out 13.8 % of patients, including early (<2 h) presenters. A 2-h delta of <2 ng/L ruled out an additional 39 % of patients. Based on European Society of Cardiology guidance, derived 0 h<15 ng/L and derived delta of <5 ng/L ruled out 42 % of patients. The Mindray assay showed incremental (non-rounded) analysis discriminated rule out from baseline of <0.1 ng/L at 1.2 % to 2.0 ng/L at 17.0 %. There were no missed adverse outcomes at 30-day assessment for composite of MI and cardiac death. Conclusions The novel Mindray hs-cTnI assay enabled safe and early rule out of MI and cardiac death at very low concentrations in a diverse, cohort utilizing both single sample and 0/2-h rule out protocols, including early presenters.

Objectives Traditional biomarkers used for sepsis diagnosis have limited sensitivity and specificity and, so far, are not recommended for sepsis diagnosis. We aimed to evaluate diagnostic accuracy of XN-9000 ® hematology analyzer derived cell population data (CPD) for sepsis. Methods We conducted a cross-sectional cohort study on patients admitted to an emergency department (ED) with a suspicion of infection, having a complete blood count with differential (CBC-Diff). CBC-Diff were performed on XN-9000 ® analyzer (Sysmex, Kobe, Japan). CPD were measured routinely for each CBC-Diff ordered by ED physician. They include: neutrophils-related - Neut-GI and Neut-RI; monocytes-related - Mono-X, Mono-Z, Re-Mono and Mono-Y; IG referring to immature granulocytes; and lymphocytes-related - As-lymp and Re-lymp. Intensive care infection (ICIS) and neutrophile and monocyte (NEMO) scores were calculated using several CPD parameters. Diagnostic performance of each biomarker was computed together with receiver operating characteristic curves for sepsis diagnosis (according to Sepsis-3 definition). Results A total of 1,155 patients with a suspicion of infection were included and 230 had sepsis. Median age was 64 years and 49 % were female. Except for lymphocyte count with an area under the receiver operating characteristic (AUROC) of 0.67 (95 % confidential interval 0.63–0.70), the other CPD exhibited modest performances with AUROC under 0.65. The ICIS and NEMO scores had a modest performance with AUROC of 0.56 (0.52–0.61) and 0.55 (0.51–0.59) respectively. Conclusions None of the biomarkers and scores tested demonstrated sufficient diagnostic accuracy to be recommended for routine sepsis screening in the ED.