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Objective: This scoping review protocol describes the strategy for a scoping review that aims to provide a comprehensive overview of published guidelines for the prescription of standard laboratory tests performed in intensive care unit (ICU) patients., Background: The use of clinical laboratories is constantly increasing. However, there is evidence of inappropriate use. Inappropriate laboratory testing has the potential to harm patients, increase costs, burden staff, and has an environmental impact. Effective management can be achieved through demand managing strategies, such as providing guidelines on performing the appropriate test, for the right patient, at the right time. Although national and international guidelines exist for individual tests, a comprehensive summary of available recommendations for laboratory testing in the ICU is currently unavailable., Inclusion Criteria: This scoping review will incorporate documents that provide explicit advice on which test to perform in ICU patients. We selected 34 tests routinely ordered in the ICU. This review will consider any document type that matches our concept and context. We will consider gray literature with appropriate adherence to guidelines methodology. We will not limit the review by geographical location, but will only include articles published in English., Search Strategy: Our scoping review will follow the Joanna Brigg Institute (JBI) methodology. We will search Medline (PubMed), Embase, Scopus, Google Scholar, and Google. Our search strategy adheres to the JBI 3-step construction approach for systematic reviews. We will search for keywords related to guidelines, laboratory testing, and the 34 selected tests. We will report our study using the S1 Checklist. Review registration number: osf.io/yfs9z., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Devis et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Equine piroplasmosis (EP) is a protozoal disease affecting equids, caused by Theileria equi and Babesia caballi . EP is conventionally diagnosed using microscopic, molecular, and/or serological methods, which are time-consuming. Consequently, there is a need for faster testing methods. In this study, we evaluated the application of the Sysmex XN-31 automated hematology analyzer, originally a rapid test for detecting malaria in humans, for the diagnosis of EP. The cultured parasites were measured using the XN-31 that had been customized for horse blood samples (XN-31m). The following parameters were evaluated: limit of detection (LoD), limit of quantification (LoQ), linearity, carryover, precision, and correlation with microscopic examination. The XN-31m detected infected red blood cells (RBCs) in approximately 1 minute. The LoD and LoQ for B. caballi were 4.54 infected RBCs/μL and 14.10 infected RBCs/μL, while those for T. equi were 5.80 infected RBCs/μL and 11.44 infected RBCs/μL, respectively. Linearity showed excellent correlation ( R 2 > 0.99), and carryover never exceeded 0.5%. The coefficient of variation was under 5%. The correlation between the results obtained using XN-31m and microscopic examination was high ( R 2 > 0.98). In conclusion, the XN-31 analyzer detected B. caballi and T. equi parasites in approximately 1 minute with high sensitivity. The results indicate the potential of the XN-31 analyzer as a fast and user-friendly diagnostic method for EP., Importance: In this study, we demonstrated that the automated hematology analyzer, XN-31, can detect red blood cells infected with Babesia caballi and Theileria equi in about 1 minute. We evaluated the diagnostic performance of the XN-31 analyzer for equine piroplasmosis, providing evidence of its potential as a diagnostic tool for this disease., Competing Interests: Yuji Toya, Mikako Sengoku, and Seiichiro Tsuchiya are employees of Sysmex corp.

Competing Interests: Declaration of Competing Interest The authors declare no conflicts of interest.

Background and Aims: Compensated advanced chronic liver disease (cACLD) identifies patients at risk for clinically significant portal hypertension (CSPH), and thus, for liver-related complications. The limited availability of liver stiffness measurements (LSM) impedes the identification of patients at risk for cACLD/CSPH outside of specialized clinics. We aimed to develop a blood-based algorithm to identify cACLD by fibrosis-4 (FIB-4) and CSPH by von Willebrand factor/platelet count ratio (VITRO)., Approach and Results: Patients with (suspected) compensated chronic liver disease undergoing FIB-4+LSM were included in the LSM/FIB-4 cohorts from Vienna and Salzburg. The HVPG/VITRO cohorts included patients undergoing HVPG-measurement + VITRO from Vienna and Bern.LSM/FIB-4-derivation-cohort: We included 6143 patients, of whom 211 (3.4%) developed hepatic decompensation. In all, 1724 (28.1%) had LSM ≥ 10 kPa, which corresponded to FIB-4 ≥ 1.75. Importantly, both LSM (AUROC:0.897 [95% CI:0.865-0.929]) and FIB-4 (AUROC:0.914 [95% CI:0.885-0.944]) were similarly accurate in predicting hepatic decompensation within 3 years. FIB-4 ≥ 1.75 identified patients at risk for first hepatic decompensation (5 y-cumulative incidence:7.6%), while in those <1.75, the risk was negligible (0.3%).HVPG/VITRO-derivation cohort: 247 patients of whom 202 had cACLD/FIB-4 ≥ 1.75 were included. VITRO exhibited an excellent diagnostic performance for CSPH (AUROC:0.889 [95% CI:0.844-0.934]), similar to LSM (AUROC:0.856 [95% CI:0.801-0.910], p = 0.351) and the ANTICIPATE model (AUROC:0.910 [95% CI:0.869-0.952], p = 0.498). VITRO < 1.0/ ≥ 2.5 ruled-out (sensitivity:100.0%)/ruled-in (specificity:92.4%) CSPH. The diagnostic performance was comparable to the Baveno-VII criteria.LSM/FIB-4-derivation cohort findings were externally validated in n = 1560 patients, while HVPG/VITRO-derivation-cohort findings were internally (n = 133) and externally (n = 55) validated., Conclusions: Simple, broadly available laboratory tests (FIB-4/VITRO) facilitate cACLD detection and CSPH risk stratification in patients with (suspected) liver disease. This blood-based approach is applicable outside of specialized clinics and may promote early intervention., (Copyright © 2024 American Association for the Study of Liver Diseases.)

Blood tests are vital to prevention, diagnosis, and management of chronic diseases. Despite this, it can be challenging to construct a comprehensive view of the clinical importance of blood testing because relevant literature is typically fragmented across different disease areas and patient populations. This lack of collated evidence can also make it difficult for primary care providers to adhere to best practices for blood testing across different diseases and guidelines. Thus, this review article synthesizes the recommendations for, and importance of, blood testing across several common chronic conditions encountered in primary care and internal medicine, including cardiovascular diseases, diabetes mellitus, chronic kidney disease, vitamin D deficiency, iron deficiency, and rheumatoid arthritis. Future research is needed to continue improving chronic disease management through clearer dissemination and awareness of clinical guidelines among providers, and better access to blood testing for patients (e.g., via pre-visit laboratory testing)., Competing Interests: Conflicts of Interest Imelda Cabalar received consulting fees from Becton, Dickinson and Company, was on the Advisory Board for Gilead Sciences in January 2020, and served as a Consultant for Cardinal Health in March 2020. Thu Le received consulting fees from Becton, Dickinson and Company and served on the Advisory Board for Mineralys in September 2023. Abigail Silber and Matthew O'Hara are employed by Trinity Life Sciences and received consulting fees from Becton, Dickinson and Company. Bilal Abdallah and Monisha Parikh are employed by Becton, Dickinson and Company. Robert Busch received consulting fees from Becton, Dickinson and Company, is on the Speaker Bureau for Novo Nordisk, Eli Lilly, Amgen, and AstraZeneca, provides research support for Novo Nordisk, Eli Lilly, and Corcept Pharmaceuticals, and is on the Advisory Board for Novo Nordisk., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

Backgrounds: During the Coronavirus Disease 2019 (COVID-19) epidemic, the massive spread of the disease has placed an enormous burden on the world's healthcare and economy. The early risk assessment system based on a variety of machine learning (ML) algorithms may be able to provide more accurate advice on the classification of COVID-19 patients, offering predictive, preventive, and personalized medicine (PPPM) solutions in the future., Methods: In this retrospective study, we divided a portion of the data into training and validation cohorts in a 7:3 ratio and established a model based on a combination of two ML algorithms first. Then, we used another portion of the data as an independent testing cohort to determine the most accurate and stable model and compared it with other scoring systems. Finally, patients were categorized according to risk scores and then the correlation between their clinical data and risk scores was studied., Results: The elderly accounted for the majority of hospitalized patients with COVID-19. The C-index of the model constructed by combining the stepcox[both] and survivalSVM algorithms was 0.840 in the training cohort and 0.815 in the validation cohort, which was calculated to have the highest C-index in the testing cohort compared to the other 119 ML model combinations. Compared with current scoring systems, including the CURB-65 and several reported prognosis models previously, our model had the highest AUC value of 0.778, representing an even higher predictive performance. In addition, the model's AUC values for specific time intervals, including days 7,14 and 28, demonstrate excellent predictive performance. Most importantly, we stratified patients according to the model's risk score and demonstrated a difference in survival status between the high-risk, median-risk, and low-risk groups, which means a new and stable risk assessment system was built. Finally, we found that COVID-19 patients with a history of cerebral infarction had a significantly higher risk of death., Conclusion: This novel risk assessment system is highly accurate in predicting the prognosis of patients with COVID-19, especially elderly patients with COVID-19, and can be well applied within the PPPM framework. Our ML model facilitates stratified patient management, meanwhile promoting the optimal use of healthcare resources., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Qin, Li, Zhu, Yu, Peng, Wu, Xu, Gu and Guo.)

Background: Malaria control depends primarily on rapid and accurate diagnosis followed by successful treatment. Light microscopy is still used as a gold standard method for the diagnosis of malaria. The Sysmex hematology analyzer is a novel method for malaria detection. Therefore, the aim of this review was to investigate the diagnostic accuracy of the Sysmex hematology analyzer for malaria diagnosis., Methods: Electronic databases like PubMed, PubMed Central, Science Direct databases, Google Scholar, and Scopus were used to find relevant articles from April to June 14, 2023. The studies' methodological quality was assessed using the Quality Assessment of Diagnostic Accuracy Studies-2 tool. Using Review Manager 5.4.1, the estimates of sensitivity and specificity, as well as their 95% confidence intervals, were shown in forest plots. Midas software in Stata 14.0 was utilized to calculate the summary estimates of sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, and diagnostic odds ratio. Heterogeneity was assessed by using I2 statistics. In addition, publication bias was assessed using a funnel plot and Deeks' test. Sub-group and meta- regression analysis were also performed., Results: A total of 15 studies were assessed for diagnostic accuracy. The sensitivity and specificity of Sysmex hematology analyzer for studies ranged from 46% to 100% and 81% to 100%, respectively. The summary estimate of sensitivity and specificity of Sysmex hematology analyzer were 95% (95% CI: 85%-99%) and 99% (95% CI: 97%-100%), respectively. It had excellent diagnostic accuracy. There were significant heterogeneity among the studies included in this meta-analysis. The summary estimate of sensitivity and specificity of Sysmex hematology analyzer using polymerase chain reaction as the gold standard was 97.6% (95% CI: 83.2, 99.7) and 99.4% (98.5, 99.8), respectively., Conclusion: In this review, Sysmex hematology analyzer had excellent diagnostic accuracy. Therefore, it could be used as an alternate diagnostic tool for malaria diagnosis in the hospital and health center., Trial Registration: Systematic review registration PROSPERO (2023: CRD42023427713). https://www.crd.york.ac.uk/prospero/display&#95;record.php?ID=CRD42023427713., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Mulatie et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Objective: The purpose of this study is to evaluate the accuracy of Sysmex XN-9000 hematology analyzer (XN-9000) in detecting nucleated cell classifications in serous effusion and to further evaluate whether it can be used for screening malignant serous effusion., Methods: The consistency between XN-9000 and manual microscopy in the classification of nucleated cells was evaluated using Passing-Bablok regression and Bland-Altman plot. ROC analysis was applied to evaluate the value of HF-BF% in screening malignant specimens., Results: In the serous effusion of the group with nucleated cell count of (0-150) ×10 6 /μL, high consistency between XN-9000 and manual microscopy was found in detecting NE-BF% and LY-BF%. In the group with nucleated cell count >150×10 6 /μL, there was high consistency in detecting NE-BF%, LY-BF%, and HF-BF%. ROC analysis showed that HF-BF% can be used for screening malignant serous effusion, with an area under the curve (AUC) of 0.572 (95%CI=0.504~0.639)., Conclusion: If XN-9000 detection results are mainly NE-BF% and LY-BF%, the classification can be effectively referred to and reported regardless of the number of nucleated cells in the serous effusion. HF-BF% has certain value in screening malignant serous effusion with a nuclear cell count >150×10 6 /μL. The optimal cut-off value is 13.15%., (© 2024 by the Association of Clinical Scientists, Inc.)

Pancytopenia is an uncommon abnormality detected on a full blood count. Features of presentation tend to be non-specific, and are due to impaired functions of the cell lines involved. These can include fatigue, infection and bleeding. However, the aetiology of pancytopenia is extensive. This narrative review aims to provide a minimally invasive diagnostic algorithm for generalist clinicians to approach pancytopenia, including investigations into the underlying aetiology, and when a referral to the haematologist is warranted for further investigations such as bone marrow aspiration and trephine biopsy., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Background: Predicting an individual's risk of death from COVID-19 is essential for planning and optimising resources. However, since the real-world mortality rate is relatively low, particularly in places like Hong Kong, this makes building an accurate prediction model difficult due to the imbalanced nature of the dataset. This study introduces an innovative application of graph convolutional networks (GCNs) to predict COVID-19 patient survival using a highly imbalanced dataset. Unlike traditional models, GCNs leverage structural relationships within the data, enhancing predictive accuracy and robustness. By integrating demographic and laboratory data into a GCN framework, our approach addresses class imbalance and demonstrates significant improvements in prediction accuracy., Methods: The cohort included all consecutive positive COVID-19 patients fulfilling study criteria admitted to 42 public hospitals in Hong Kong between January 23 and December 31, 2020 (n = 7,606). We proposed the population-based graph convolutional neural network (GCN) model which took blood test results, age and sex as inputs to predict the survival outcomes. Furthermore, we compared our proposed model to the Cox Proportional Hazard (CPH) model, conventional machine learning models, and oversampling machine learning models. Additionally, a subgroup analysis was performed on the test set in order to acquire a deeper understanding of the relationship between each patient node and its neighbours, revealing possible underlying causes of the inaccurate predictions., Results: The GCN model was the top-performing model, with an AUC of 0.944, considerably outperforming all other models (p < 0.05), including the oversampled CPH model (0.708), linear regression (0.877), Linear Discriminant Analysis (0.860), K-nearest neighbours (0.834), Gaussian predictor (0.745) and support vector machine (0.847). With Kaplan-Meier estimates, the GCN model demonstrated good discriminability between low- and high-risk individuals (p < 0.0001). Based on subanalysis using the weighted-in score, although the GCN model was able to discriminate well between different predicted groups, the separation was inadequate between false negative (FN) and true negative (TN) groups., Conclusion: The GCN model considerably outperformed all other machine learning methods and baseline CPH models. Thus, when applied to this imbalanced COVID survival dataset, adopting a population graph representation may be an approach to achieving good prediction., (© 2024. The Author(s).)

Public health spatial data are often recorded at different spatial scales (or geographic regions/divisions) and over different correlated variables. Motivated by data from the Dartmouth Atlas Project, we consider jointly analyzing average annual percentages of diabetic Medicare enrollees who have taken the hemoglobin A1c and blood lipid tests, observed at the hospital service area (HSA) and county levels, respectively. Capitalizing on bivariate relationships between these two scales is not immediate as counties are not nested within HSAs. It is well known that one can improve predictions by leveraging correlations across both variables and scales. There are very few methods available that simultaneously model multivariate and multiscale correlations. We propose three new hierarchical Bayesian models for bivariate multiscale spatial data, extending spatial random effects, multivariate conditional autoregressive (MCAR), and ordered hierarchical models through a multiscale spatial approach. We simulated data from each of the three models and compared the corresponding predictions, and found the computationally intensive multiscale MCAR model is more robust to model misspecification. In an analysis of 2015 Texas Dartmouth Atlas Project data, we produced finer resolution predictions (partitioning of HSAs and counties) than univariate analyses, determined that the novel multiscale MCAR and OH models were preferable via out-of-sample metrics, and determined the HSA with the highest within-HSA variability of hemoglobin A1c blood testing. Additionally, we compare the univariate multiscale models to the bivariate multiscale models and see clear improvements in prediction over univariate analyses., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Background: Errors associated with failures in filing, actioning and communicating blood test results can lead to delayed and missed diagnoses and patient harm. This study aimed to audit how blood tests in primary care are filed, actioned and communicated in primary care, to identify areas for patient safety improvements., Methods: UK primary care clinicians were recruited through the Primary Care Academic CollaboraTive (PACT). PACT members audited 50 recent sets of blood tests from their practice and retrospectively extracted data on blood test result coding, actioning and communication. PACT members received a practice report, showing their own results, benchmarked against other participating practices., Results: PACT members from 57 general practices across all four UK nations collected data on 2572 patients who had blood tests in April 2021. In 89.9% (n=2311) they agreed with the initial clinician's actioning of blood tests; 10.1% disagreed, either partially (7.1%) or fully (3.0%).In 44% of patients (n=1132) an action (eg, 'make an appointment') was specified by the filing clinician. This action was carried out in 89.7% (n=1015/1132) of cases; in 6.8% (n=77) the action was not carried out, in 3.5% (n=40) it was unclear. In the 117 cases where the test result had not been actioned 38% (n=45) were felt to be at low risk of harm, 1.7% (n=2) were at high risk of harm, 0.85% (n=1) came to harm.Overall, in 47% (n=1210) of patients there was no evidence in the electronic health records that results had been communicated. Out of 1176 patients with one or more abnormal results there was no evidence of test communication in 30.6% (n=360). There were large variations between practices in rates of actioning and communicating tests., Conclusion: This research demonstrates variation in the way blood test results are actioned and communicated, with important patient safety implications., Competing Interests: Competing interests: PD, IBB, SH, SWDM, and SW were members of the PACT committee during the conduct of this study, as well as being co-investigators. JW is current Chair of the PACT committee., (© Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Introduction: Abnormal results in common blood tests may occur several months before lung cancer (LC) and colorectal cancer (CRC) diagnosis. Identifying early blood markers of cancer and distinct blood test signatures could support earlier diagnosis in general practice., Methods: Using linked Australian primary care and hospital cancer registry data, we conducted a cohort study of 855 LC and 399 CRC patients diagnosed between 2001 and 2021. Requests and results from general practice blood tests (six acute phase reactants [APR] and six red blood cell indices [RBCI]) were examined in the 2 years before cancer diagnosis. Poisson regression models were used to estimate monthly incidence rates and examine pre-diagnostic trends in blood test use and abnormal results prior to cancer diagnosis, comparing patterns in LC and CRC patients., Results: General practice blood test requests increase from 7 months before CRC and 6 months before LC diagnosis. Abnormalities in many APR and RBCI tests increase several months before cancer diagnosis, often occur prior to or in the absence of anaemia (in 51% of CRC and 81% of LC patients with abnormalities), and are different in LC and CRC patients., Conclusions: This study demonstrates an increase in diagnostic activity in Australian general practice several months before LC and CRC diagnosis, indicating potential opportunities for earlier diagnosis. It identifies blood test abnormalities and distinct signatures that are early markers of LC and CRC. If combined with other pre-diagnostic information, these blood tests have potential to support GPs in prioritising patients for cancer investigation of different sites to expedite diagnosis., (© 2024 The Author(s). Cancer Medicine published by John Wiley & Sons Ltd.)

The need for the identification of risk factors associated to COVID-19 disease severity remains urgent. Patients' care and resource allocation can be potentially different and are defined based on the current classification of disease severity. This classification is based on the analysis of clinical parameters and routine blood tests, which are not standardized across the globe. Some laboratory test alterations have been associated to COVID-19 severity, although these data are conflicting partly due to the different methodologies used across different studies. This study aimed to construct and validate a disease severity prediction model using machine learning (ML). Seventy-two patients admitted to a Brazilian hospital and diagnosed with COVID-19 through RT-PCR and/or ELISA, and with varying degrees of disease severity, were included in the study. Their electronic medical records and the results from daily blood tests were used to develop a ML model to predict disease severity. Using the above data set, a combination of five laboratorial biomarkers was identified as accurate predictors of COVID-19 severe disease with a ROC-AUC of 0.80 ​±​ 0.13. Those biomarkers included prothrombin activity, ferritin, serum iron, ATTP and monocytes. The application of the devised ML model may help rationalize clinical decision and care.

Background: Diagnostic blood tests have the potential to identify lung cancer in people at high risk. We assessed the cost-effectiveness of a lung cancer screening intervention, using the EarlyCDT ® -Lung Test (ECLS) with subsequent X-ray and low-dose chest CT scans (LDCT) for patients with a positive test result, compared to both usual care and LDCT screening for the target population., Methods: We conducted a model-based lifetime analysis from a UK NHS and personal social services perspective. We estimated incremental net monetary benefit (NMB) for the ECLS intervention compared to no screening and to LDCT screening., Results: The incremental NMB of ECLS intervention compared to no screening was GBP 33,179 (95% CI: -GBP 81,396, GBP 147,180) and GBP 140,609 (95% CI: -GBP 36,255, GBP 316,612), respectively, for a cost-effectiveness threshold of GBP 20,000 and GBP 30,000 per quality-adjusted life year. The same figures compared with LDCT screening were GBP 162,095 (95% CI: GBP 52,698, GBP 271,735) and GBP 52,185 (95% CI: -GBP 115,152, GBP 219,711)., Conclusions: The ECLS intervention is the most cost-effective screening alternative, with the highest probability of being cost-effective, when compared to no screening or LDCT screening. This result may change with modifications of the parameters, suggesting that the three alternatives considered in the main analysis are potentially cost-effective., Competing Interests: All authors report grants from Oncimmune Ltd., and grants from the Scottish Government Health & Social Care Directorate of the Chief Scientist Office (CSO), during the conduct of the study.

Background and Objectives: Malaria continues to be a significant public health concern in India, with several regions experiencing endemicity and sporadic outbreaks. The prevalence of malaria in blood donors, in India, varies between 0.02% and 0.07%. Common techniques to screen for malaria, in blood donors and patients, include microscopic smear examination and rapid diagnostic tests (RDTs) based on antigen detection. The aim of this study was to evaluate a new fully automated analyser, XN-31, for malaria detection, as compared with current practice of using RDT., Materials and Methods: Cross-sectional analytical study was conducted to evaluate clinical sensitivity and specificity of new automated analyser XN-31 among blood donors' samples and clinical samples (patients with suspicion of malaria) from outpatient clinic collected over between July 2021 and October 2022. No additional sample was drawn from blood donor or patient. All blood donors and patients' samples were processed by malaria rapid diagnostic test, thick-smear microscopy (MIC) and the haematology analyser XN-31. Any donor blood unit incriminated for malaria was discarded. Laboratory diagnosis using MIC was considered the 'gold standard' in the present study. Clinical sensitivity and specificity of XN-31 were compared with the gold standard., Results: Fife thousand and five donor samples and 82 diagnostic samples were evaluated. While the clinical sensitivity and specificity for donor samples were 100%, they were 72.7% and 100% for diagnostic samples., Conclusion: Automated haematology analysers represent a promising solution, as they can deliver speedy and sensitive donor malaria screening assessments. This method also has the potential to be used for pre-transfusion malaria screening along with haemoglobin estimation., (© 2024 International Society of Blood Transfusion.)

Background: Reference intervals are essential for the interpretation of clinical laboratory tests and patient management. This study aims to determine age and gender reference intervals of complete blood count (CBC) in the Moroccan population by using the indirect approach., Methods: The study used data of ostensibly healthy adults collected retrospectively using the laboratory information system (LIS) of the Laboratory for Research and Medical Analysis of the Fraternal Royal Gendarmerie in Rabat (Morocco), between January 2018 and February 2020. The study included 5,898 men and 10,172 women ranging in age from 18 to 90 years. The lower and upper reference limits of CBC parameters were calculated using the nonparametric technique, as suggested by the Clinical and Laboratory Standards Institute (CLSI)., Results: All hematological parameters showed no clinically significant gender-related differences, except small differences in the values of hemoglobin (HB), mean corpuscular volume (MCV), mean corpuscular hemoglobin (MCH) and mean corpuscular hemoglobin concentration (MCHC). There were also no clinically significant agerelated differences for median values of all hematology analytes in both genders, except for platelet count (PLT) that continued to decline with increasing age in men and women, and Red blood cell count (RBC), Hematocrit (HCT), and hemoglobin (HB) that tended to increase with age but decrease in older age groups in men while they tended to increase with age in women., Conclusions: The indirect method can be used to establish reference intervals for CBC, with appropriate selection criteria and statistical tools. Our findings differed from the reference ranges provided in the textbook and also in other countries' reports.

Aim: Accurate diagnosis of complicated appendicitis is of importance to ensure that patients receive early and effective treatment, minimizing the risk of postoperative complications to promote successful recovery. Biochemical markers are a promising tool to identify complicated appendicitis. We aimed to evaluate the potential role of novel parameters related with neutrophil activation, known as "Extended Inflammation Parameters" (EIP), included in blood cell count reported by Sysmex XN-Series analyzers, compared to other canonical biomarkers in identifying complicated appendicitis., Method: Prospective observational study including patients with confirmed diagnosis of acute appendicitis. C-reactive protein (CRP), procalcitonin, cell blood count, including white blood cell (WBC), absolute neutrophil (ANC) and immature granulocyte (IG) count and EIP (neutrophil reactivity [NEUT-RI] and granularity intensity [NEUT-GI]) were analyzed before surgery. Their accuracy to diagnose complicated appendicitis was tested in an ROC curve analysis., Results: Our population study included 119 patients, and appendicitis was complicated in 58 (48.7%). NLR, CRP and procalcitonin levels, ANC and IG count and NEUT-RI and NEUT-GI were higher in patients with complicated appendicitis. Regarding accuracy for complicated appendicitis, CRP was the biomarker with the highest performance (ROC AUC: 0.829), with an optimal cutoff of 73.1 mg/L (sensitivity: 63.8%, specificity: 88.5%). NEUT-RI and NEUT-GI achieved both significant but poor accuracy, with ROC AUC of 0.606 and 0.637, respectively., Conclusions: Novel laboratory tests reported by Sysmex XN-Series analyzers have poor accuracy for identifying complicated appendicitis. In this study, CRP was the biomarker with the highest performance and may be useful as predictor of the severity of acute appendicitis., (Copyright © 2024 AEC. Published by Elsevier España, S.L.U. All rights reserved.)

Objectives: Even in the current era of hematology analyzer automation and peripheral equipment, quality control sample measurement remains a manual task, leading to variability in quality control data and increased workload. In this study, we evaluated the performance of quality control measurement using the BT-50 Transportation Unit (BT-50, Sysmex, Kobe, Japan), equipped with a scheduled automatic quality control function, to ensure measurement accuracy and streamline the workflow of hematology testing., Methods: We evaluated the automatic measurement performance of quality control samples using the BT-50 for six representative blood test parameters: WBC (white blood cell), RBC (red blood cell), HGB (hemoglobin), HCT (hematocrit), PLT (platelet), and RET% (reticulocyte percent). We evaluated the equivalence and compared measurement accuracy between the BT-50 and the manual method. We then compared the variability to other laboratories and confirmed the stability of quality control samples. We also evaluated changes in workflow and staff resources before and after the introduction of the BT-50., Results: The quality control measurement results for the BT-50 and the manual method were found to be equivalent for all six parameters. The variability measured by the BT-50 was lower for some parameters compared to the manual method. Furthermore, the workflow was streamlined by reducing manual processes, resulting in increased efficiency., Conclusions: We confirmed the performance of quality control measurements using the schedule function of the BT-50. Introducing the BT-50 reduced the operator's workload, improved operational efficiency, and promoted the standardization of quality control measurements., (© 2024 the author(s), published by De Gruyter, Berlin/Boston.)

Background: The Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), influenza A, and respiratory syncytial virus (RSV) infections have similar modes of transmission and clinical symptoms. There is a need to identify simple diagnostic indicators to distinguish these three infections, particularly for community hospitals and low- and middle-income countries that lack nucleic acid detection kits. This study used clinical data to assess the diagnostic value of routine blood tests in differentiating between SARS-CoV-2, influenza A, and RSV infections in children., Methods: A total of 1420 children treated at the Hangzhou Children's Hospital between December 2022 and June 2023 were enrolled in this study, of whom 351 had SARS-CoV-2, 671 had influenza, and 398 had RSV. In addition, 243 healthy children were also collected. The blood test results of SARS-CoV-2 patients were compared to those of patients with influenza A and RSV and the healthy controls. The area under the receiver operating characteristic curve (AUC-ROC) was employed to evaluate each blood parameter's diagnostic value., Results: Children with SARS-CoV-2 exhibited notably elevated levels of white blood cell (WBC) count, platelet (PLT) count, neutrophil count, and neutrophil-to-lymphocyte ratio (NLR) compared to influenza A patients (P < 0.05). In contrast, SARS-CoV-2 patients exhibited a decrease in the mean platelet volume to platelet count ratio (MPV/PLT) and the lymphocyte-to-monocyte ratio (LMR) when compared to other individuals (P < 0.05). These parameters had an AUC between 0.5 and 0.7. Compared to patients with RSV, SARS-CoV-2 patients had significantly higher MPV/PLT and significantly lower WBC, lymphocyte, PLT, LMR, and lymphocyte multiplied by platelet (LYM*PLT) values (P < 0.05). However, only LYM*PLT had an acceptable diagnostic value above 0.7 for all age groups. Compared to healthy children, children with COVID-19 exhibited elevated NLR and MPV/PLT levels, alongside decreased lymphocyte, PLT, LMR, and LYM*PLT values. (P < 0.05). The AUC of the LMR, LYM*PLT, and PLT were above 0.7 in all age groups, indicating promising diagnostic values., Conclusions: The routine blood parameters among patients with COVID-19, influenza A, and RSV differ significantly early in the disease and could be used by clinicians to discriminate between the 3 types of infection., (© 2024. The Author(s).)

Background and Aims: The results of blood potassium can be seriously affected by specimen hemolysis which may interfere with clinicians' interpretation of test results. Redrawing blood and retesting may delay treatment time and it is not feasible for critically ill patients with difficulty in specimen collection. Therefore, it is significant to establish a mathematical model that can quickly correct the blood potassium concentration of hemolytic specimens., Materials and Methods: The residual blood samples from 107 patients at Peking University Third Hospital were collected to establish potassium correction model. Samples with different hemolysis indexes were obtained by ultrasonic crushing method. Blood potassium correction models of hemolysis specimens were established by linear regression and curve fitting using SPSS and MATLAB, respectively. In addition, blood samples from another 85 patients were used to verify the accuracy of the models and determine the optimal model., Results: Variation of potassium (ΔK) was 0.003HI-0.03 (R 2  = 0.9749) in linear regression model which had high correlation in ΔK and HI, and the correction formula was K correction  = K hemolysis -0.003 × HI + 0.03. Average rate of potassium change (α average ) was 0.003 ± 0.0002 mmol/L in curve fitting model, and correction formula was K correction  = K hemolysis -0.003 × HI, and both men and women can use the same correction model. The accuracy of linear regression model was 96.5 %, and there was statistical difference between the verification results and the measured values (p < 0.05), while the accuracy of curve fitting model was 100 %, and there was no statistical difference between the verification results and the measured values (p = 0.552). The model was validated in an independent set of samples and all were within the TEa of 6 % and the accuracy of 100 %., Conclusions: Both linear regression and curve fitting models of potassium correction had high accuracy, and can effectively correct the potassium concentration of hemolytic specimens, while the curve fitting model have superior accuracy., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Author(s). Published by Elsevier B.V. All rights reserved.)

Humans interact with thousands of chemicals. This study aims to identify substances of emerging concern and in need of human health risk evaluations. Sixteen pooled human serum samples were constructed from 25 individual samples each from the National Institute of Environmental Health Sciences' Clinical Research Unit. Samples were analyzed using gas chromatography (GC) × GC/time-of-flight (TOF)-mass spectrometry (MS) in a suspect screening analysis, with follow-up confirmation analysis of 19 substances. A standard reference material blood sample was also analyzed through the confirmation process for comparison. The pools were stratified by sex (female and male) and by age (≤45 and >45). Publicly available information on potential exposure sources was aggregated to annotate presence in serum as either endogenous, food/nutrient, drug, commerce, or contaminant. Of the 544 unique substances tentatively identified by spectral matching, 472 were identified in females, while only 271 were identified in males. Surprisingly, 273 of the identified substances were found only in females. It is known that behavior and near-field environments can drive exposures, and this work demonstrates the existence of exposure sources uniquely relevant to females.

This study investigates the effectiveness of data augmentation to improve dementia risk prediction using deep neural networks (DNNs). Previous research has shown that basic blood test data were cost-effective and crucial in predicting cognitive function, as indicated by mini-mental state examination (MMSE) scores. However, creating models that can accommodate various conditions is a significant challenge due to constraints related to blood test and MMSE results, such as high costs, limited sample size, and missing data from specific tests not conducted in certain facilities. Periodontal examinations have also emerged as a cost-effective tool for mass screening. To address these issues, this study explores the use of generative adversarial networks (GANs) for generating synthesised data from blood test and periodontal examination results. We used DNNs with four hidden layers to compare prediction accuracy between real and GAN-synthesised data from 108 participants at Nihon University Itabashi Hospital. The GAN-synthesised DNNs achieved a mean absolute error (MAE) of 1.91 ± 0.30 compared to 2.04 ± 0.37 for real data, indicating improved accuracy with synthesised data. Importantly, synthesised data showcased enhanced robustness against missing important variables including age information, and better managed data imbalances. Considering the difficulties in amassing extensive medical data, the augmentation approach is promising in refining dementia risk prediction., (© 2024. Oxygen Transport to Tissue International.)

Background: Recently, a method using deep learning has been developed to estimate the risk of developing dementia. This method uses general blood test data from routine health examinations that reveal lifestyle-related diseases, which can lead to vascular cognitive impairment via arteriosclerosis, as well as systemic metabolic disorders that are unrelated to lifestyle, such as nutritional disorders. In this study, we investigated the differences in the accuracy of estimating the risk of dementia based on the presence or the absence of blood test parameters reflecting nutritional disorders while focusing on the association between malnutrition and the risk of dementia in frail, elderly individuals., Objectives: The objective of this study was to evaluate the impact of including or excluding serum albumin, which reflects nutritional status, on the accuracy of predicting cognitive function in older adults using blood test data., Methods: We estimated cognitive function, as measured by the Mini-Mental State Examination (MMSE), using the deep learning model (DLM). The estimation was performed based on general blood test data, including complete blood tests and basic metabolic panels, obtained from a selection of 1287 patients admitted to Osaka Medical and Pharmaceutical University Hospital. The data were divided into two groups: individuals aged 65 and above and those aged below 65. The impact of including or excluding serum albumin on the predictive performance of MMSE was examined within each group., Results: In those aged below 65, the mean squared error (MSE) of the DLM was 5.33 without albumin and 4.62 with albumin, showing a -0.71 improvement with albumin. In those aged 65 and above, the MSE of the DLM was 6.38 without albumin and 6.28 with albumin, showing a -0.1 improvement with albumin., Discussion: The present study demonstrated that including serum albumin in the input data resulted in lower estimation errors for MMSE across all applied algorithms in the group aged 65 and above. This is consistent with previously reported studies that have shown the adverse effects of malnutrition on cognitive function in older adults., Conclusions: This study highlighted the significance of serum albumin, which reflects nutritional status, as an important assessment variable for estimating MMSE from blood test data, particularly in individuals aged 65 and above., (© 2024. Oxygen Transport to Tissue International.)

Background: Hepatocellular carcinoma (HCC) is the fourth leading cause of cancer death worldwide. Alpha-protein (AFP) is the most widely used blood biomarker for HCC. However, elevated serum AFP is only observed in part of HCC., Aims: This study aimed to develop an efficient nomogram model to distinguish patients with alpha- protein-negative HCC and liver cirrhosis., Objectives: A total of 1130 patients (508 HCC patients + 622 cirrhosis patients) were enrolled in the training cohort. A total of 244 HCC patients and 246 cirrhosis patients were enrolled in the validation cohort., Methods: A total of 41 parameters about blood tests were analyzed with logistic regression. The nomogram was based on independent factors and validated both internally and externally., Results: Independent factors were eosinophils %, hemoglobin concentration distribution width, fibrinogen, platelet counts, total bile acid, and mitochondria aspartate aminotransferase. The calibration curve for the probability of HCC showed good agreement between prediction by nomogram and actual observation. The concordance index was 0.851. In the validation cohort, the nomogram distinguished HCC from liver cirrhosis with an area under the curve of receiver operating characteristic of 0.754., Conclusion: This proposed nomogram was an accurate and useful method to distinguish patients with AFP-negative HCC from liver cirrhosis., (Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.net.)

Background: The presence of comorbidities, especially those with a chronic inflammatory nature such as periodontitis, can facilitate COVID-19 progression toward more severe forms. Both of these diseases can affect systemic health and alter hematological test results. In this study, we decided to investigate COVID-19 and periodontitis' possible interaction with these alterations., Methods: Hospitalized patients with a definitive diagnosis of COVID-19 were included. Controls had mild to moderate COVID-19, while cases had severe to critical COVID-19. Periodontal examination was done for each patient. Relevant medical and hematological data were extracted from patient's hospital files., Results: A total of 122 patients entered the final analysis. The minimum white blood cell counts were associated with the severity of periodontitis. The interaction between periodontitis and COVID-19 was associated with increased minimum white blood cell counts and decreased platelet counts. COVID-19 severity was associated with increased venous oxygen saturation, prothrombin time, the maximum partial thromboplastin time, the maximum and average urea, the maximum creatinine, the maximum potassium, and lactate dehydrogenase, and decreased sodium levels., Conclusions: Results of this study showed that several blood parameters were associated with periodontitis, COVID-19, or the interaction between them., (© 2023. The Author(s).)

Nucleic acid extraction (NAE) plays a crucial role for diagnostic testing procedures. For decades, dried blood spots (DBS) have been used for serology, drug monitoring, and molecular studies. However, extracting nucleic acids from DBS remains a significant challenge, especially when attempting to implement these applications to the point-of-care (POC). To address this issue, we have developed a paper-based NAE method using cellulose filter papers (DBSFP) that operates without the need for electricity (at room temperature). Our method allows for NAE in less than 7 min, and it involves grade 3 filter paper pre-treated with 8% (v/v) igepal surfactant, 1 min washing step with 1× PBS, and 5 min incubation at room temperature in 1× TE buffer. The performance of the methodology was assessed with loop-mediated isothermal amplification (LAMP), targeting the human reference gene beta-actin and the kelch 13 gene from P. falciparum . The developed method was evaluated against FTA cards and magnetic bead-based purification, using time-to-positive (min) for comparative analysis. Furthermore, we optimised our approach to take advantage of the dual functionality of the paper-based extraction, allowing for elution ( eluted disk ) as well as direct placement of the disk in the LAMP reaction ( in situ disk ). This flexibility extends to eukaryotic cells, bacterial cells, and viral particles. We successfully validated the method for RNA/DNA detection and demonstrated its compatibility with whole blood stored in anticoagulants. Additionally, we studied the compatibility of DBSFP with colorimetric and lateral flow detection, showcasing its potential for POC applications. Across various tested matrices, targets, and experimental conditions, our results were comparable to those obtained using gold standard methods, highlighting the versatility of our methodology. In summary, this manuscript presents a cost-effective solution for NAE from DBS, enabling molecular testing in virtually any POC setting. When combined with LAMP, our approach provides sample-to-result detection in under 35 minutes.

Blood analysis through complete blood count is the most basic medical test for disease diagnosis. Conventional blood analysis requires bulky and expensive laboratory facilities and skilled technicians, limiting the universal medical use of blood analysis outside well-equipped laboratory environments. Here, we propose a multiparameter mobile blood analyzer combined with label-free contrast-enhanced defocusing imaging (CEDI) and machine vision for instant and on-site diagnostic applications. We designed a low-cost and high-resolution miniature microscope (size: 105 mm × 77 mm × 64 mm, weight: 314 g) that comprises a pair of miniature aspheric lenses and a 415 nm LED for blood image acquisition. The analyzer, adopting CEDI, can obtain both the refractive index distributions of the white blood cell (WBC) and hemoglobin spectrophotometric information, enabling the analyzer to supply rich blood parameters, including the five-part WBC differential count, red blood cell (RBC) count, and mean corpuscular hemoglobin (MCH) quantification with machine vision algorithms and the Lambert-Beer law. We have shown that our assay can analyze a blood sample within 10 minutes without complex staining, and measurements (30 samples) from the analyzer have a strong linear correlation with clinical reference values (significance level of 0.0001). This study provides a miniature, light weight, low-cost, and easy-to-use blood analysis technique that overcomes the challenge of simultaneously realizing FWD count, RBC count, and MCH analysis using a mobile device and has great potential for integrated surveillance of various epidemic diseases, including coronavirus infection, invermination, and anemia, especially in low- and middle-income countries.

Hb variants prevalent in China are different from those in other countries. We aimed to assess the interference from Hb variants found in China on HbA1c measurement. All Hb variants were confirmed using Sanger sequencing. HbA1c was measured using a capillary electrophoresis method (Capillarys 3 OCTA), two cation-exchange high-performance liquid chromatography methods (ADAMS HA-8180V and HLC-723 G8 standard mode), an immunoassay (Cobas c501), and a boronate affinity chromatography method (Premier Hb9210). Premier Hb9210 was used as a comparative method. A total of 16 species of Hb variants were identified in 102 variant carriers. The most common variant was Hb E, followed by Hb Q-Thailand, Hb New York and Hb J-Bangkok. Clinically significant interference was observed for the Capillarys 3 OCTA (two Hb variants), ADAMS HA-8180V (seven Hb variants), HLC-723 G8 (14 Hb variants), and Cobas c501 (two Hb variants). The proportion of unacceptable HbA1c results was 13.7% for Capillarys 3 OCTA, 52.9% for HA-8180V, 83.3% for HLC-723 G8, and 3.9% for Cobas c501. Hb variants in China severely affect the accuracy of some commonly used HbA1c methods.

Background: Hemoglobin (Hgb) levels are frequently checked through venipuncture [invasive hemoglobin (iHgb)] in pediatric orthopaedic patients after high blood loss procedures. This needlestick may causes further anxiety and fear in hospitalized children. Noninvasive hemoglobin (nHgb) monitoring has been effectively utilized in the adult intensive care and postoperative total joint arthroplasty setting. nHgb monitoring has not yet been validated in children for routine postoperative Hgb assessment in pediatric orthopaedics., Methods: In this prospective study, 46 pediatric orthopaedic patients were enrolled who were undergoing surgery and postoperative standard of care iHgb testing. On postoperative day 1, Hgb levels were obtained through venipuncture and nHgb monitor (Pronto-7; Masimo) within a 2-hour period. Patient preferences, iHgb and nHgb values, time to result, and provider preferences were recorded. Cost data were estimated based on the standard Medicare payment rates for lab services versus the cost of nHgb probe., Results: nHgb results were obtained after 1 attempt in 38 patients (83%), after multiple attempts in 7 patients (15%), and could not be obtained in 1 patient. The mean time to obtain nHgb value was significantly shorter than that to obtain iHgb results (1.3±1.5 vs. 40±18.1 min; P <0.0001). The mean nHgb value was significantly higher than the mean iHgb value (11.7±1.5 vs. 10.6±1.1 g/dL, P <0.0001). nHgb exceeded iHgb by 2 g/dL or more in 12 (26%) patients (2.64±0.9 vs. 0.54±0.84 g/dL; P <0.0001). The concordance correlation coefficient between the 2 Hgb methods was 0.59, indicating moderate agreement. Forty-three (93%) of our patients and 34 (74%) of the care providers preferred nHgb over iHgb if results were equivalent. At our institution, the cost per iHgb monitoring is approximately $28 per blood draw as compared with $5 for nHgb monitoring. Interestingly, no patients required postoperative transfusion during the study period, as asymptomatic patients with no cardiac disease are typically observed unless the Hgb is <6., Conclusions: nHgb monitoring in postoperative pediatric patients overestimated Hgb levels compared with the standard of care methods; however, nHgb had high patient and provider satisfaction and had moderate agreement with iHgb. As no patients required transfusion, postoperative Hgb checks could likely be discontinued in some portion of our population., Level of Evidence: Level Ib-Diagnostic study., Competing Interests: Outside of the study, T.A.M. reports consulting activities with Orthopediatrics, Medtronic, Zimmer, and stock ownership in Viking Scientific. A.N.L. reports consulting activities with Orthopediatrics, Medtronic, Zimmer, and Globus. The remaining authors declare no conflicts of interest., (Copyright © 2022 Wolters Kluwer Health, Inc. All rights reserved.)

Anemia is a blood disorder which is caused due to inadequate red blood cells and hemoglobin concentration. It occurs in all phases of life cycle but is more dominant in pregnant women and infants. According to the survey conducted by the World Health Organization (WHO) (McLean et al., Public Health Nutr 12(4):444-454, 2009), anemia affects 1.62 billion people constituting 24.8% of the population and is considered the world's second leading cause of illness. The Peripheral Blood Smear (PBS) examination plays an important role in evaluating hematological disorders. Anemia is diagnosed using PBS. Being the most powerful analytical tool, manual analysis approach is still in use even though it is tedious, prone to errors, time-consuming and requires qualified laboratorians. It is evident that there is a need for an inexpensive, automatic and robust technique to detect RBC disorders from PBS. Automation of PBS analysis is very active field of research that motivated many research groups to develop methods using image processing. In this paper, we present a review of the methods used to analyze the characteristics of RBC from PBS images using image processing techniques. We have categorized these methods into three groups based on approaches such as RBC segmentation, RBC classification and detection of anemia, and classification of anemia. The outcome of this review has been presented as a list of observations., (© 2022. The Author(s).)

This article first reviews scientific meanings of single-cell analysis by highlighting two key scientific problems: landscape reconstruction of cellular identities during dynamic immune processes and mechanisms of tumor origin and evolution. Secondly, the article reviews clinical demands of single-cell analysis, which are complete blood counting enabled by optoelectronic flow cytometry and diagnosis of hematologic malignancies enabled by multicolor fluorescent flow cytometry. Then, this article focuses on the developments of optoelectronic flow cytometry for the complete blood counting by comparing conventional counterparts of hematology analyzers (e.g., DxH 900 of Beckman Coulter, XN-1000 of Sysmex, ADVIA 2120i of Siemens, and CELL-DYN Ruby of Abbott) and microfluidic counterparts (e.g., microfluidic impedance and imaging flow cytometry). Future directions of optoelectronic flow cytometry are indicated where intrinsic rather than dependent biophysical parameters of blood cells must be measured, and they can replace blood smears as the gold standard of blood analysis in the near future.

Background: Over past decades, the instability of parathyroid hormone (PTH) causes great interference for the clinical laboratory. Contradictory results were reported in many reports about storage conditions and suitable blood collection tubes to ensure PTH stability in the pretreatment phase., Methods: This study recruited 30 participants including 10 healthy persons, 10 hemodialysis, and 10 hyperparathyroidism patients. Five types of blood collection tubes (EDTA-K3 tube, coagulant tube, heparin anticoagulant tube, gel separating tube, and plain tube) were included to determine whether they were suitable as blood-collecting vessels. The time points and conditions for testing samples included less than 2 hours, 4 hours, and 8 hours at room temperature, and, in parallel, 24 hours, 48 hours, and 72 hours in refrigeration. Two different judgement criteria were used to compare the stability of PTH in different blood vessels., Results: Purely statistical analysis showed that 4 types of blood collection tubes could not perform the same storage ability as EDTA-K3 tube at "T0" time point. Plain tube had the largest drop among all types of blood collection tubes. Compared by pairwise t-test, EDTA-K3 tube could maintain intact PTH for 8 hours (p = 0.998) at room temperature and 24 hours (p = 0.053) in refrigeration. When comparing the total change limit (TCL = 18.8%), at room temperature, EDTA-K3 tube (7.0%), heparin tube (12.7%), coagulant tube (16.2%), and plain tube (17.6%) could maintain intact PTH for 8 hours, and GST can preserve PTH for 4 hours (18.2%). In refrigeration, EDTA-K3 tube could maintain PTH for 72 hours (7.5%) and heparin tube could maintain 24 hours (18.4%). The other three blood collection tubes could not preserve PTH in refrigeration (GST = 22.1%, coagulant tube = 20.3%, plain tube = 20.8%)., Conclusions: PTH seems more stable in the EDTA-K3 tube than any other blood collection tubes and is followed next by the heparin anticoagulant tube. Plain tube and GST have faster degradation than other tubes and are not suggested to preserve intact PTH.

The investigation of conventional complete blood-count (CBC) data for classifying the SARS-CoV-2 infection status became a topic of interest, particularly as a complementary laboratory tool in developing and third-world countries that financially struggled to test their population. Although hematological parameters in COVID-19-affected individuals from Asian and USA populations are available, there are no descriptions of comparative analyses of CBC findings between COVID-19 positive and negative cases from Latin American countries. In this sense, machine learning techniques have been employed to examine CBC data and aid in screening patients suspected of SARS-CoV-2 infection. In this work, we used machine learning to compare CBC data between two highly genetically distinguished Latin American countries: Brazil and Ecuador. We notice a clear distribution pattern of positive and negative cases between the two countries. Interestingly, almost all red blood cell count parameters were divergent. For males, neutrophils and lymphocytes are distinct between Brazil and Ecuador, while eosinophils are distinguished for females. Finally, neutrophils, lymphocytes, and monocytes displayed a particular distribution for both genders. Therefore, our findings demonstrate that the same set of CBC features relevant to one population is unlikely to apply to another. This is the first study to compare CBC data from two genetically distinct Latin American countries., (Copyright © 2022 The Authors. Published by Elsevier B.V. All rights reserved.)

Patients on anticoagulant treatment are constantly increasing, with an estimated prevalence in Italy of 2% of the total population. About a quarter of the anticoagulated patients require temporary cessation of direct oral anticoagulants (DOACs) or vitamin K antagonists for a planned intervention within 2 years from anticoagulation inception. Several clinical issues about DOAC interruption remain unanswered: many questions are tentatively addressed daily by thousands of physicians worldwide through an experience-based balancing of thrombotic and bleeding risks. Among possible valuable answers, the Italian Federation of Centers for the diagnosis of thrombotic disorders and the Surveillance of the Antithrombotic therapies (FCSA) proposes some experience-based suggestions and expert opinions. In particular, FCSA provides practical guidance on the following issues: (1) multiparametric assessment of thrombotic and bleeding risks based on patients' individual and surgical risk factor, (2) testing of prothrombin time, activated partial thromboplastin time, and DOAC plasma levels before surgery or invasive procedure, (3) use of heparin, (4) restarting of full-dose DOAC after high risk bleeding surgery, (5) practical nonpharmacological suggestions to manage patients perioperatively. Finally, FCSA suggests creating a multidisciplinary "anticoagulation team" with the aim to define the optimal perioperative management of anticoagulation., Competing Interests: A.S.: Honoraria for lectures, manuscript writing, and/or participation on advisory board from Daiichi Sankyo, Bayer, Pfizer, Bristol-Myers Squibb, Sanofi, Werfen, Alexion, and Roche. D.P.: Honoraria for a webinar from Daiichi Sankyo. D.B.: Honoraria for lectures from Aspen and Werfen. A.C.: Honoraria for lectures from Bayer. E.G.: Honoraria for lectures from Sanofi and Italfarmaco, and for participation on advisory board from Roche, Sanofi Genzyme, and Novo Nordisk. C.M.: None. M.M.: Honoraria for lectures and manuscript writing from Daiichi-Sankyo. V.T.: Honoraria for lectures from Bayer and Novo Nordisk. A.T.: Honoraria for lectures from Werfen, Stago, and Roche; support for attending meetings from Novo Nordisk; honoraria for participation on advisory board from Bayer and Novo Nordisk. S.T.: Honoraria for lectures and for participation on advisory board from Werfen, Stago, Italfarmaco, Pfizer, Bristol-Myers Squibb, and Sanofi., (The Author(s). This is an open access article published by Thieme under the terms of the Creative Commons Attribution-NonDerivative-NonCommercial License, permitting copying and reproduction so long as the original work is given appropriate credit. Contents may not be used for commercial purposes, or adapted, remixed, transformed or built upon. (https://creativecommons.org/licenses/by-nc-nd/4.0/).)

Evans syndrome presents as concurrent autoimmune hemolytic anemia (AIHA) and immune thrombocytopenia (ITP). Systemic lupus erythematosus (SLE) is the most frequent autoimmune disorder associated with Evans syndrome. We herein report a case of new-onset Evans syndrome associated with SLE after BNT162b2 mRNA coronavirus disease 2019 (COVID-19) vaccination in a 53-year-old woman. Blood examination at diagnosis showed hemolytic anemia with a positive Coombs test and thrombocytopenia. Hypocomplementemia and the presence of lupus anticoagulant indicated a strong association with SLE. Prednisolone administration rapidly restored hemoglobin level and platelet count. This case suggests that mRNA COVID-19 vaccination may cause an autoimmune disorder. Physicians should be aware of this adverse reaction by mRNA COVID-19 vaccination and should consider the benefits and risks of vaccination for each recipient., (© 2021. Japanese Society of Hematology.)

Since manual hemolysis test methods are given priority with practical experience and its cost is high, the characteristics of hemolysis images are studied. A hemolysis image detection method based on generative adversarial networks (GANs) and convolutional neural networks (CNNs) with extreme learning machine (ELM) is proposed. First, the image enhancement and data enhancement are performed on a sample set, and GAN is used to expand the sample data volume. Second, CNN is used to extract the feature vectors of the processed images and label eigenvectors with one-hot encoding. Third, the feature matrix is input to the map in the ELM network to minimize the error and obtain the optimal weight by training. Finally, the image to be detected is input to the trained model, and the image with the greatest probability is selected as the final category. Through model comparison experiments, the results show that the hemolysis image detection method based on the GAN-CNN-ELM model is better than GAN-CNN, GAN-ELM, GAN-ELM-L1, GAN-SVM, GAN-CNN-SVM, and CNN-ELM in accuracy and speed, and the accuracy rate is 98.91%., Competing Interests: The authors declare that they have no conflicts of interest., (Copyright © 2022 Xiaonan Shi et al.)

Choosing Wisely is a medical stewardship and quality-improvement initiative led by the American Board of Internal Medicine Foundation in collaboration with leading medical societies in the United States. The American Society of Hematology (ASH) has been an active participant in the Choosing Wisely project. In 2019, ASH and the American Society of Pediatric Hematology/Oncology (ASPHO) formed a joint task force to solicit, evaluate, and select items for a pediatric-focused Choosing Wisely list. By using an iterative process and an evidence-based method, the ASH-ASPHO Task Force identified 5 hematologic tests and treatments that health care providers and patients should question because they are not supported by evidence, and/or they involve risks of medical and financial costs with low likelihood of benefit. The ASH-ASPHO Choosing Wisely recommendations are as follows: (1) avoid routine preoperative hemostatic testing in an otherwise healthy child with no previous personal or family history of bleeding, (2) avoid platelet transfusion in asymptomatic children with a platelet count >10 × 103/μL unless an invasive procedure is planned, (3) avoid thrombophilia testing in children with venous access-associated thrombosis and no positive family history, (4) avoid packed red blood cells transfusion for asymptomatic children with iron deficiency anemia and no active bleeding, and (5) avoid routine administration of granulocyte colony-stimulating factor for prophylaxis of children with asymptomatic autoimmune neutropenia and no history of recurrent or severe infections. We recommend that health care providers carefully consider the anticipated risks and benefits of these identified tests and treatments before performing them., (© 2022 by The American Society of Hematology. Licensed under Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0), permitting only noncommercial, nonderivative use with attribution. All other rights reserved.)

The aim of this study was to compare the clinical characteristics of patients with tubo-ovarian abscess (TOA) who responded to medical treatment and those who underwent surgical intervention due to medical treatment failure. Electronic medical records were evaluated retrospectively to identify patients who were diagnosed with TOA. Demographic, clinical, and laboratory data including white blood cell (WBC) count, erythrocyte sedimentation rate (ESR), and C-reactive protein (CRP) were compared between the medical treatment group and the surgical intervention group. Patient age, TOA diameter, WBC count, CRP, and ESR were significantly different between the groups. On multiple regression analysis, significant correlations were identified between age ( p  = .001), ESR ( p  = .045), and failure of medical treatment. TOA diameter ( p  = .065) showed a borderline association with surgical intervention. The risk of needing surgical intervention in TOA patients can be predicted using ESR in addition to age and TOA size as risk factors.IMPACT STATEMENT What is already known on this subject? For patients diagnosed with a tubo-ovarian abscess (TOA), the size of TOA and the patient's age are helpful for early identification of patients who are likely to need surgical treatment. Inflammatory markers such as C-reactive protein and white blood cell are also associated with the risk of surgical intervention. What do the results of this study add? Erythrocyte sedimentation rate (ESR) in addition to the size of TOA and the patient's age is a useful marker in determining whether to undergo surgery in patients with TOA. What are the implications of these findings for clinical practice and/or further research? ESR combined with the patient's age and the size of TOA is clinically useful in predicting the need for early surgical intervention in patients with TOA. Large prospective controlled studies are required to establish relationship between inflammatory markers and the risk of surgical intervention.

Background/aim: Coronavirus 2019 disease (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is a pandemic infectious disease that causes morbidity and mortality. As a result of high mortality rate among the severe COVID-19 patients, the early detection of the disease stage and early effective interventions are very important in reducing mortality. Hence, it is important to differentiate severe and nonsevere cases from each other. To date, there are no proven diagnostic or prognostic parameters that can be used in this manner. Due to the expensive and not easily accessible tests that are performed for COVID-19, researchers are investigating some parameters that can be easily used. In some recent studies, hematological parameters have been evaluated to see if they can be used as predictive parameters., Materials and Methods: In the current study, almost all hematological parameters were used, including the neutrophil/lymphocyte ratio, platelet/lymphocyte ratio, monocyte/lymphocyte ratio, mean platelet volume to lymphocyte ratio, mean platelet volume to platelet ratio, plateletcrit, and D-dimer/fibrinogen ratio, neutrophil/lymphocyte/platelet scoring system, and systemic immune-inflammation index. A total of 750 patients, who were admitted to Ankara City Hospital due to COVID-19, were evaluated in this study. The patients were classified into 2 groups according to their diagnosis (confirmed or probable) and into 2 groups according to the stage of the disease (nonsevere or severe)., Results: The values of the combinations of inflammatory markers and other hematological parameters in all of the patients with severe COVID-19 were calculated, and the predicted values of these parameters were compared. According to results of the study, nearly all of the hematological parameters could be used as potential diagnostic biomarkers for subsequent analysis, because the area under the curve (AUC) was higher than 0.50, especially for the DFR and NLR, which had the highest AUC among the parameters., Conclusion: Our findings indicate that, the parameters those enhanced from complete blood count, which is a simple laboratory test, can help to identify and classify COVID-19 patients into non-severe to severe groups., Competing Interests: The authors have no conflict of interest to declare., (This work is licensed under a Creative Commons Attribution 4.0 International License.)