55,973 research outputs found

    Blood Count

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    This music clip is from the CD entitled Field of Play. The band was directed by Dr. Robert Washut.https://scholarworks.uni.edu/jazzband/1008/thumbnail.jp

    Complete Blood Count

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    Complete Blood Count

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    Complete Blood Count

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    Complete Blood Count

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    Haematalogical investigations in children

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    The haematology laboratory is able to perform a number of tests to help establish the cause of illness in children. The full blood count (FBC, also known as a complete blood count, CBC) is one of the most basic blood tests performed on children attending hospital or a primary care clinic. All doctors should therefore have an understanding of how the test is performed, possible pitfalls, be able to interpret results and know when more specialised testing or advice is required. Other haematological investigations in routine use include coagulation screens, blood film examination, reticulocyte counts and methods for estimation of iron stores and detection of abnormal haemoglobins. This section will focus on these basic tests and simple algorithms for the subsequent investigation and differential diagnosis of the commonest haemato-logical abnormalities encountered in general paediatric practice. The reader is referred to Chapter 15 for an account of the clinical presentation and management of primary haematological disorders in children

    Complete blood count and C-reactive protein to predict positive blood culture among neonates using machine learning algorithms

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    Purpose: The authors aimed to develop a Machine-Learning (ML) algorithm that can predict positive blood culture in the neonatal intensive care unit, using complete blood count and C-reactive protein values. Methods: The study was based on patients’ electronic health records at a tertiary neonatal intensive care unit in São Paulo, Brazil. All blood cultures that had paired complete blood count and C-reactive protein measurements taken at the same time were included. To evaluate the machine learning model's performance, the authors used accuracy, Area Under the Receiver Operating Characteristics (AUROC), recall, precision, and F1-score. Results: The dataset included 1181 blood cultures with paired complete blood count plus c-reactive protein and 1911 blood cultures with paired complete blood count only. The f1-score ranged from 0.14 to 0.43, recall ranged from 0.08 to 0.59, precision ranged from 0.29 to 1.00, and accuracy ranged from 0.688 to 0.864. Conclusion: Complete blood count parameters and C-reactive protein levels cannot be used in ML models to predict bacteremia in newborns

    Comparative Assessment of Red Blood Cell Morphology in Anaemic Children

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    Anaemia (haemoglobin level < 11 g/dl) is a health burden among preschool children and women of child bearing age and affects over 27% of the World population. Anaemia results from reduction in the functional haemoglobin or red blood cell numbers or mass leading to decreased oxygen carrying capacity characterized by clinical features such as; skin pallor, fatigue, shortness of breath, congestive heart failure, jaundice and tachycardia. Evaluating and interpreting red blood cell morphology provides key information in the differential diagnosis of Anaemia. However, the current standard Peripheral thin blood method of assessing red blood cell morphology is highly technical and time consuming. There was need to carry out assessment into the alternative Automated Complete Blood Count method to aid in the selection of the reliable assay. The objective of the study was to compare between Peripheral blood thin film and Automated Complete Blood Count morphologically classified Anaemia in children. The study was cross-sectional and employed simple random sampling technique. Blood samples were obtained from the participants, assessed for red blood cell morphology by Automated Complete Blood Count and Peripheral thin blood film. Data was analyzed using SPSS and a paired t-test used to test for the statistical significance. Results show no significant difference in the scores for Peripheral thin blood film (M=25.5, SD=11.82) and Automated Complete Blood Count (M=25.5, SD=12.66) t (3) =0.00, p =1.000. Automated Complete Blood Count is a method of choice in assessing red blood cell morphology and evaluating Anaemia. The study recommends assessment into various Automated Complete Blood Count models available in the market to aid in the selection of most reliable one. &nbsp

    Postpartum hemorrhage risk is driven by changes in blood composition through pregnancy.

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    The extent to which women differ in the course of blood cell counts throughout pregnancy, and the importance of these changes to pregnancy outcomes has not been well defined. Here, we develop a series of statistical analyses of repeated measures data to reveal the degree to which women differ in the course of pregnancy, predict the changes that occur, and determine the importance of these changes for post-partum hemorrhage (PPH) which is one of the leading causes of maternal mortality. We present a prospective cohort of 4082 births recorded at the University Hospital, Lausanne, Switzerland between 2009 and 2014 where full labour records could be obtained, along with complete blood count data taken at hospital admission. We find significant differences, at a [Formula: see text] level, among women in how blood count values change through pregnancy for mean corpuscular hemoglobin, mean corpuscular volume, mean platelet volume, platelet count and red cell distribution width. We find evidence that almost all complete blood count values show trimester-specific associations with PPH. For example, high platelet count (OR 1.20, 95% CI 1.01-1.53), high mean platelet volume (OR 1.58, 95% CI 1.04-2.08), and high erythrocyte levels (OR 1.36, 95% CI 1.01-1.57) in trimester 1 increased PPH, but high values in trimester 3 decreased PPH risk (OR 0.85, 0.79, 0.67 respectively). We show that differences among women in the course of blood cell counts throughout pregnancy have an important role in shaping pregnancy outcome and tracking blood count value changes through pregnancy improves identification of women at increased risk of postpartum hemorrhage. This study provides greater understanding of the complex changes in blood count values that occur through pregnancy and provides indicators to guide the stratification of patients into risk groups
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