scholarly journals Averrhoa bilimbi Extract as an Alternative Anticoagulant for Manual Complete Blood Count

2019 ◽  
Vol 5 (1) ◽  
pp. 6
Author(s):  
Arvyl Jan L. Andaya ◽  
Prince Duncan C. Maylas ◽  
Ma. Estrella H. Sales
Keyword(s):  
Blood Cell ◽  
White Blood Cell ◽  
Red Blood Cell ◽  
Blood Count ◽  
Clinical Laboratory ◽  
Complete Blood Count ◽  
Ethylenediaminetetraacetic Acid ◽  
Wbc Count ◽  
Edta Anticoagulated Blood ◽  
Rbc Count

This study was designed to determine whether Averroha bilimbi extract can be used as an alternative anticoagulant for manual complete blood count (CBC) in the hematology clinical laboratory instead of Ethylenediaminetetraacetic acid (EDTA), the recommended anticoagulant for CBC. Blood from 15 volunteers was extracted and placed in EDTA-anticoagulated tubes and tubes with Averrhoa bilimbi extract. Samples from both tubes were tested for CBC. Using independent t-test the study revealed that there is no difference in the red blood cell (RBC) count, white blood cell (WBC) count, hemoglobin, hematocrit, and a 3-part differential of EDTA anticoagulated blood and blood with Averrhoa bilimbi extract as anticoagulant. The morphology of lymphocytes and monocytes were not affected, however, the granulocytes showed cytoplasmic distortion and vacuolation in the Averrhoa bilimbi extract.

scholarly journals Surgical Treatment of Sialolithiasis Leads to Improvement in the Complete Blood Count

Biology ◽  
2021 ◽  
Vol 10 (5) ◽  
pp. 414
Author(s):  
Gal Avishai ◽  
Idan Rabinovich ◽  
Hanna Gilat ◽  
Gavriel Chaushu ◽  
Liat Chaushu
Keyword(s):  
Surgical Treatment ◽  
Blood Cell ◽  
Red Blood Cell ◽  
Blood Count ◽  
Complete Blood Count ◽  
Blood Cell Count ◽  
Blood Profile ◽  
Post Procedure ◽  
Red Blood Cell Count ◽  
Anemia Of Inflammation

Sialolithiasis is a chronic disease in which a sialolith (salivary stone) causes recurrent inflammation of the affected salivary gland. Anemia of inflammation is a well-described pathology in which a chronic inflammatory disease leads to a reduction in the red blood cell count, hemoglobin and hematocrit values. In this retrospective cohort study, we aim to find whether removal of the sialolith and alleviation of the inflammation affect the complete blood count results. We examined data regarding forty-nine patients who underwent surgery for the removal of a submandibular gland sialolith using the duct-stretching technique. Complete blood counts two years before and after the surgical procedure were collected. The average pre-procedure and post-procedure values were calculated for each patient to establish the average blood profile. The pre- and post-procedure values were compared to evaluate the effect of the surgical treatment on the blood profile. We found that the average blood count values for patients with sialolithiasis were towards the lower end of the normal range. Post-surgery, a significant increase in hematocrit, hemoglobin and red blood cell count was observed, which was more pronounced in the older age group and in patients with co-morbidities. We conclude that sialolith removal surgery is associated with significant improvement in the complete blood count values, especially in the elderly and in patients and with co-morbidities. The speculated pathogenesis is relative anemia of inflammation.

scholarly journals A Novel Parameter for Predicting Therapeutic Response in Iron Deficiency Anemia: Red Blood Cell Distribution Width

2019 ◽  
Vol 8 (3) ◽  
pp. 107-112
Author(s):  
Aslı Korur ◽  
Didar Yanardag Acik ◽  
Soner Solmaz ◽  
Cigdem Gereklioglu ◽  
Suheyl Asma ◽  
...  
Keyword(s):  
Blood Cell ◽  
Red Blood Cell ◽  
Blood Count ◽  
Complete Blood Count ◽  
Reticulocyte Count ◽  
Iron Therapy ◽  
Deficiency Anemia ◽  
Cell Distribution ◽  
Distribution Width ◽  
Red Blood Cell Distribution

Aim: Anemia is a public health problem worldwide. Cost effectiveness and efficient use of resources are vitally important. Red blood cell distribution width, which can be obtained from a standard complete blood count, is a measure of the variability in size of circulating erythrocytes. The present study was performed to investigate whether red blood cell distribution width can be used to predict response to iron therapy. Methods: This study was conducted in 50 patients admitted to hematology and family medicine clinics. Complete blood count and reticulocyte count were determined on day 5; complete blood count was examined 1 month after commencement of therapy. Results: Statistically significant differences were detected between hemoglobin levels and red blood cell distribution width values at the time of diagnosis and on day 5 and after 1 month of therapy. A significant positive correlation was found between the increase in red blood cell distribution width and the increase in hemoglobin. Conclusion: Red blood cell distribution width may be used in place of reticulocyte count to predict response to iron therapy. Red blood cell distribution width is the best biomarker for this purpose as a component of complete blood count, and therefore it may be accepted as superior to reticulocyte count.

scholarly journals A Novel Automated Slide-Based Technology for Visualization, Counting, and Characterization of the Formed Elements of Blood: A Proof of Concept Study

2017 ◽  
Vol 141 (8) ◽  
pp. 1107-1112 ◽  
Author(s):  
James W. Winkelman ◽  
Milenko J. Tanasijevic ◽  
David J. Zahniser
Keyword(s):  
Image Analysis ◽  
Blood Cell ◽  
White Blood Cell ◽  
Blood Count ◽  
Complete Blood Count ◽  
Differential Count ◽  
Preparation Technique ◽  
Proof Of Concept ◽  
New Instrument ◽  
Prototype Instrument

Context.— A novel automated slide-based approach to the complete blood count and white blood cell differential count is introduced. Objective.— To present proof of concept for an image-based approach to complete blood count, based on a new slide preparation technique. A preliminary data comparison with the current flow-based technology is shown. Design.— A prototype instrument uses a proprietary method and technology to deposit a precise volume of undiluted peripheral whole blood in a monolayer onto a glass microscope slide so that every cell can be distinguished, counted, and imaged. The slide is stained, and then multispectral image analysis is used to measure the complete blood count parameters. Images from a 600-cell white blood cell differential count, as well as 5000 red blood cells and a variable number of platelets, that are present in 600 high-power fields are made available for a technologist to view on a computer screen. An initial comparison of the basic complete blood count parameters was performed, comparing 1857 specimens on both the new instrument and a flow-based hematology analyzer. Results.— Excellent correlations were obtained between the prototype instrument and a flow-based system. The primary parameters of white blood cell, red blood cell, and platelet counts resulted in correlation coefficients (r) of 0.99, 0.99, and 0.98, respectively. Other indices included hemoglobin (r = 0.99), hematocrit (r = 0.99), mean cellular volume (r = 0.90), mean corpuscular hemoglobin (r = 0.97), and mean platelet volume (r = 0.87). For the automated white blood cell differential counts, r values were calculated for neutrophils (r = 0.98), lymphocytes (r = 0.97), monocytes (r = 0.76), eosinophils (r = 0.96), and basophils (r = 0.63). Conclusions.— Quantitative results for components of the complete blood count and automated white blood cell differential count can be developed by image analysis of a monolayer preparation of a known volume of peripheral blood.

scholarly journals Establishing Classifiers With Clinical Laboratory Indicators to Distinguish COVID-19 From Community-Acquired Pneumonia: Retrospective Cohort Study

10.2196/23390 ◽  
2021 ◽  
Vol 23 (2) ◽  
pp. e23390
Author(s):  
Wanfa Dai ◽  
Pei-Feng Ke ◽  
Zhen-Zhen Li ◽  
Qi-Zhen Zhuang ◽  
Wei Huang ◽  
...  
Keyword(s):  
Uric Acid ◽  
Blood Cell ◽  
Neutrophil Count ◽  
High Performance ◽  
Clinical Laboratory ◽  
Recall Rate ◽  
Community Acquired Pneumonia ◽  
Data Set ◽  
Wbc Count ◽  
Rbc Count

Background The initial symptoms of patients with COVID-19 are very much like those of patients with community-acquired pneumonia (CAP); it is difficult to distinguish COVID-19 from CAP with clinical symptoms and imaging examination. Objective The objective of our study was to construct an effective model for the early identification of COVID-19 that would also distinguish it from CAP. Methods The clinical laboratory indicators (CLIs) of 61 COVID-19 patients and 60 CAP patients were analyzed retrospectively. Random combinations of various CLIs (ie, CLI combinations) were utilized to establish COVID-19 versus CAP classifiers with machine learning algorithms, including random forest classifier (RFC), logistic regression classifier, and gradient boosting classifier (GBC). The performance of the classifiers was assessed by calculating the area under the receiver operating characteristic curve (AUROC) and recall rate in COVID-19 prediction using the test data set. Results The classifiers that were constructed with three algorithms from 43 CLI combinations showed high performance (recall rate >0.9 and AUROC >0.85) in COVID-19 prediction for the test data set. Among the high-performance classifiers, several CLIs showed a high usage rate; these included procalcitonin (PCT), mean corpuscular hemoglobin concentration (MCHC), uric acid, albumin, albumin to globulin ratio (AGR), neutrophil count, red blood cell (RBC) count, monocyte count, basophil count, and white blood cell (WBC) count. They also had high feature importance except for basophil count. The feature combination (FC) of PCT, AGR, uric acid, WBC count, neutrophil count, basophil count, RBC count, and MCHC was the representative one among the nine FCs used to construct the classifiers with an AUROC equal to 1.0 when using the RFC or GBC algorithms. Replacing any CLI in these FCs would lead to a significant reduction in the performance of the classifiers that were built with them. Conclusions The classifiers constructed with only a few specific CLIs could efficiently distinguish COVID-19 from CAP, which could help clinicians perform early isolation and centralized management of COVID-19 patients.

scholarly journals Evaluation Of Complete Blood Count Parameters To Predict Ovarian Torsion In Women With Adnexal Mass

2017 ◽  
pp. 1 ◽  
Author(s):  
Ahter T. Tayyar ◽  
Enis Özkaya ◽  
Çiğdem Abide Yayla ◽  
Mehmet Baki Şentürk ◽  
Selçuk Selçuk ◽  
...  
Keyword(s):  
Blood Cell ◽  
White Blood Cell ◽  
Neutrophil Count ◽  
Ovarian Cyst ◽  
Blood Count ◽  
Complete Blood Count ◽  
Adnexal Mass ◽  
Ovarian Torsion ◽  
Adnexal Torsion ◽  
Neutrophil Lymphocyte Ratio

<p><strong>Objective:</strong> The aim of this study was to evaluate complete blood count parameters to predict ovarian torsion in cases presented with ovarian mass.</p><p><strong>Study Design:</strong> Pre-operative demographic data and complete blood count parameters of 72 patients, who were operated on preliminary adnexal torsion and diagnosed as adnexal torsion with a benign ovarian cyst (Study group) were retrospectively compared with those of 77 patients who were operated with an indication of persistent benign ovarian cysts without torsion (control group) at Zeynep Kamil Women and Children’s Health Training and Research Hospital and Department of Obstetrics &amp; Gynecology at Erciyes University Medical Faculty between 2011 and 2015. Complete blood count parameters were utilized to predict ovarian torsion cases.</p><p><strong>Result:</strong> Neutrophil (AUC=792, P=&lt;0.001), white blood cell (AUC=787, P=&lt;0.001) counts and neutrophil/lymphocyte ratio (AUC=770, P=&lt;0.001) were significant predictors for adnexal torsion. Optimal cut off value for white blood cell, neutrophil count and neutrophil/lymphocyte ratio were 8.3x103 (72% sensitivity, 73% specificity), 5.5x103 (73% sensitivity, 76% specificity), 2.9 (73% sensitivity, 79% specificity) respectively.</p><p><strong>Conclusion:</strong> Among all the parameters white blood cell count, neutrophil/lymphocyte and neutrophil count were the most powerful predictors for real adnexal torsion cases. Simple blood count parameters detailed evaluation may help clinicians to confirm or rule out adnexal torsion in cases presented with ovarian cyst and adnexal mass.</p>

scholarly journals Microfluidic Cartridges for Automated, Point-of-Care Blood Cell Counting

2016 ◽  
Vol 22 (2) ◽  
pp. 176-185
Author(s):  
Suzanne Smith ◽  
Phophi Madzivhandila ◽  
René Sewart ◽  
Ureshnie Govender ◽  
Holger Becker ◽  
...  
Keyword(s):  
Blood Cell ◽  
White Blood Cell ◽  
Red Blood Cell ◽  
Blood Count ◽  
Point Of Care ◽  
Cell Counting ◽  
Full Blood Count ◽  
Diagnostic Tools ◽  
Cell Counts ◽  
Blood Cell Counting

Disposable, low-cost microfluidic cartridges for automated blood cell counting applications are presented in this article. The need for point-of-care medical diagnostic tools is evident, particularly in low-resource and rural settings, and a full blood count is often the first step in patient diagnosis. Total white and red blood cell counts have been implemented toward a full blood count, using microfluidic cartridges with automated sample introduction and processing steps for visual microscopy cell counting to be performed. The functional steps within the microfluidic cartridge as well as the surrounding instrumentation required to control and test the cartridges in an automated fashion are described. The results recorded from 10 white blood cell and 10 red blood cell counting cartridges are presented and compare well with the results obtained from the accepted gold-standard flow cytometry method performed at pathology laboratories. Comparisons were also made using manual methods of blood cell counting using a hemocytometer, as well as a commercially available point-of-care white blood cell counting system. The functionality of the blood cell counting microfluidic cartridges can be extended to platelet counting and potential hemoglobin analysis, toward the implementation of an automated, point-of-care full blood count.

scholarly journals Establishing Classifiers With Clinical Laboratory Indicators to Distinguish COVID-19 From Community-Acquired Pneumonia: Retrospective Cohort Study (Preprint)

2020 ◽  
Author(s):  
Wanfa Dai ◽  
Pei-Feng Ke ◽  
Zhen-Zhen Li ◽  
Qi-Zhen Zhuang ◽  
Wei Huang ◽  
...  
Keyword(s):  
Uric Acid ◽  
Blood Cell ◽  
Neutrophil Count ◽  
High Performance ◽  
Clinical Laboratory ◽  
Recall Rate ◽  
Community Acquired Pneumonia ◽  
Data Set ◽  
Wbc Count ◽  
Rbc Count

BACKGROUND The initial symptoms of patients with COVID-19 are very much like those of patients with community-acquired pneumonia (CAP); it is difficult to distinguish COVID-19 from CAP with clinical symptoms and imaging examination. OBJECTIVE The objective of our study was to construct an effective model for the early identification of COVID-19 that would also distinguish it from CAP. METHODS The clinical laboratory indicators (CLIs) of 61 COVID-19 patients and 60 CAP patients were analyzed retrospectively. Random combinations of various CLIs (ie, CLI combinations) were utilized to establish COVID-19 versus CAP classifiers with machine learning algorithms, including random forest classifier (RFC), logistic regression classifier, and gradient boosting classifier (GBC). The performance of the classifiers was assessed by calculating the area under the receiver operating characteristic curve (AUROC) and recall rate in COVID-19 prediction using the test data set. RESULTS The classifiers that were constructed with three algorithms from 43 CLI combinations showed high performance (recall rate &gt;0.9 and AUROC &gt;0.85) in COVID-19 prediction for the test data set. Among the high-performance classifiers, several CLIs showed a high usage rate; these included procalcitonin (PCT), mean corpuscular hemoglobin concentration (MCHC), uric acid, albumin, albumin to globulin ratio (AGR), neutrophil count, red blood cell (RBC) count, monocyte count, basophil count, and white blood cell (WBC) count. They also had high feature importance except for basophil count. The feature combination (FC) of PCT, AGR, uric acid, WBC count, neutrophil count, basophil count, RBC count, and MCHC was the representative one among the nine FCs used to construct the classifiers with an AUROC equal to 1.0 when using the RFC or GBC algorithms. Replacing any CLI in these FCs would lead to a significant reduction in the performance of the classifiers that were built with them. CONCLUSIONS The classifiers constructed with only a few specific CLIs could efficiently distinguish COVID-19 from CAP, which could help clinicians perform early isolation and centralized management of COVID-19 patients.

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