Diagnostic value of routine blood tests in differentiating between SARS-CoV-2, influenza A, and RSV infections in hospitalized children: a retrospective study.

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.

Evaluation of new haematology analyser, XN-31, for malaria detection in blood donors: A single-centre study from India.

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.

Suspect Screening Analysis of Pooled Human Serum Samples Using GC × GC/TOF-MS.

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.

Establishment and Validation of a Blood Test-based Nomogram to Diagnose Patients with AFP-negative HCC.

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.

Accurate correction model of blood potassium concentration in hemolytic specimens.

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 (R2 = 0.9749) in linear regression model which had high correlation in ΔK and HI, and the correction formula was Kcorrection = Khemolysis-0.003 × HI + 0.03. Average rate of potassium change (αaverage) was 0.003 ± 0.0002 mmol/L in curve fitting model, and correction formula was Kcorrection = Khemolysis-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.

Consumers Can Now Buy a Blood Test to Evaluate Their Alzheimer Disease Risk, but Should They?

This Medical News feature discusses a Quest Diagnostics blood biomarkers test that is supposed to help consumers assess their Alzheimer disease risk.

Hematologic tests and their association with the severity of COVID-19 and periodontitis in hospitalized patients: a case-control study.

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.

A dual paper-based nucleic acid extraction method from blood in under ten minutes for point-of-care diagnostics.

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.

Multiparameter mobile blood analysis for complete blood count using contrast-enhanced defocusing imaging and machine vision.

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.

Evaluation of interference from 16 hemoglobin variants on hemoglobin A1c measurement by five methods.

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.

Developments of Conventional and Microfluidic Flow Cytometry Enabling High-Throughput Characterization of Single Cells.

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.

Noninvasive Hemoglobin Monitoring for Postoperative Pediatric Orthopaedic Patients: A Preliminary Study.

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.

Analysis of red blood cells from peripheral blood smear images for anemia detection: a methodological review.

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.

The Stability of Intact Parathyroid Hormone (PTH) in Different Types of Blood Collection Tubes.

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.

A Hemolysis Image Detection Method Based on GAN-CNN-ELM.

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%.