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Hematological changes associated with COVID‐19 infection
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Abstract<sec><title>Background

The unresolved COVID‐19 pandemic considerably impacts the health services in Iraq and worldwide. Consecutive waves of mutated virus increased virus spread and further constrained health systems. Although molecular identification of the virus by polymerase chain reaction is the only recommended method in diagnosing COVID‐19 infection, radiological, biochemical, and hematological studies are substantially important in risk stratification, patient follow‐up, and outcome prediction.

Aim

This narrative review summarized the hematological changes including the blood indices, coagulative indicators, and other associated biochemical laboratory markers in different stages of COVID‐19 infection, highlighting the diagnostic and prognostic significance.

Methods

Literature search was conducted for multiple combinations of different hematological tests and manifestations with novel COVID‐19 using the following key words: “hematological,” “complete blood count,” “lymphopenia,” “blood indices,” “markers” "platelet" OR "thrombocytopenia" AND "COVID‐19," "coronavirus2019," "2019‐nCoV," OR "SARS‐CoV‐2." Articles written in the English language and conducted on human samples between December 2019 and January 2021 were included.

Results

Hematological changes are not reported in asymptomatic or presymptomatic COVID‐19 patients. In nonsevere cases, hematological changes are subtle, included mainly lymphocytopenia (80.4%). In severe, critically ill patients and those with cytokine storm, neutrophilia, lymphocytopenia, elevated D‐dimer, prolonged PT, and reduced fibrinogen are predictors of disease progression and adverse outcome.

Conclusion

Monitoring hematological changes in patients with COVID‐19 can predict patients needing additional care and stratify the risk for severe course of the disease. More studies are required in Iraq to reflect the hematological changes in COVID‐19 as compared to global data.

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Thu Oct 01 2020
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Palarch’s Journal Of Archaeology Of Egypt/egyptology
Delivering an information resources service to users' homes to ensure Healthcare during COVID -19: Case study"
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ABSTRACT University college libraries are one of the most important information institutions for all researchers during their research and study life, they seeks to provide information sources such as; books, periodicals, theses, databases, Inquiry service and answering questions services in various disciplines to achieve its goals. In 2020, college libraries of all types stepped up to meet the needs of their users' as they responded to the impacts of COVID-19, also extended necessary lifelines to community members facing job losses, healthcare crises, and remote work and learning during an unprecedented and uncertain time. The research aim to identifying the services provided to the postgraduate students users at University of Baghdad coll

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Publication Date
Sun Jan 01 2023
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Proceedings Of The 1st International Conference On Frontier Of Digital Technology Towards A Sustainable Society
The most ABO blood group susceptibility to COVID-19 infections in Baghdad city
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Tue Feb 14 2023
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Psychological Stress As A Result of the Spread of the COVID-19 Pandemic
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The pressures of life have become a tangible phenomenon in all societies in varying degrees. This disparity determines several factors, including the nature of societies, the level of their urbanization, the intensity of interaction, the intensity of conflict, and the increasing rate of change in those societies. many people name The modern era in which we live the “era of pressures", where one of the most important of these changes is the “new Coronavirus 19-COVID”, which has spread widely throughout the world, as the pandemic, has affected all aspects of daily life, including the educational and academic process, academic activities have been suspended in universities, which caused sudden change

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Publication Date
Wed Sep 01 2021
Journal Name
Baghdad Science Journal
Coronavirus Disease Diagnosis, Care and Prevention (COVID-19) Based on Decision Support System
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Sat Oct 31 2020
Journal Name
The Egyptian Journal Of Otolaryngology
Incidence and recovery of smell and taste dysfunction in COVID-19 positive patients
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Abstract<sec> <title>Background

This study aims to find the chemosensitive dysfunction incidence in COVID-19-positive patients and its recovery.

We collected the data from sixty-five patients, all COVID-19 positive, quarantined in-hospital between 5 April 2020 and 17 May 2020, by a questionnaire distributed in the quarantine ward.

Results

Smell dysfunction appeared in 89.23% with or without other symptoms of COVID-19. 39.66% of them recovered the sense of smell. Taste dysfunction found in 83.08% patients with other COVID-19 symptoms. Only 29.63% of them recovered. The recovery took 1–3 weeks, and most

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Journal Of Legal Sciences
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Wed Feb 01 2023
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Classification of COVID-19 from CT chest images using Convolutional Wavelet Neural Network
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<p>Analyzing X-rays and computed tomography-scan (CT scan) images using a convolutional neural network (CNN) method is a very interesting subject, especially after coronavirus disease 2019 (COVID-19) pandemic. In this paper, a study is made on 423 patients’ CT scan images from Al-Kadhimiya (Madenat Al Emammain Al Kadhmain) hospital in Baghdad, Iraq, to diagnose if they have COVID or not using CNN. The total data being tested has 15000 CT-scan images chosen in a specific way to give a correct diagnosis. The activation function used in this research is the wavelet function, which differs from CNN activation functions. The convolutional wavelet neural network (CWNN) model proposed in this paper is compared with regular convol

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Wed Feb 01 2023
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Classification of COVID-19 from CT chest images using Convolutional Wavelet Neural Network
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<p>Analyzing X-rays and computed tomography-scan (CT scan) images using a convolutional neural network (CNN) method is a very interesting subject, especially after coronavirus disease 2019 (COVID-19) pandemic. In this paper, a study is made on 423 patients’ CT scan images from Al-Kadhimiya (Madenat Al Emammain Al Kadhmain) hospital in Baghdad, Iraq, to diagnose if they have COVID or not using CNN. The total data being tested has 15000 CT-scan images chosen in a specific way to give a correct diagnosis. The activation function used in this research is the wavelet function, which differs from CNN activation functions. The convolutional wavelet neural network (CWNN) model proposed in this paper is compared with regular convol

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