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What might COVID-19 patients experience after recovery? A comprehensive review
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Abstract<sec> <title>Objectives

The objective of this review was to describe the COVID-19 complications after recovery.

Methods

The researchers systematically reviewed studies that reported post-COVID-19 complications from three databases: PubMed, Google Scholar and the World Health Organization (WHO) COVID-19 database. The search was conducted between 21 November 2020 and 14 January 2021. Inclusion criteria were articles written in English, with primary data, reporting complications of COVID-19 after full recovery. The review was conducted following the Preferred Reporting Items for Systematic reviews and Meta-Analysis (PRISMA) 2020 statement.

Key findings

This review included 69 studies with 146 725 patients from 22 countries related to post-COVID-19 complications. Thirty-six studies reported post-cure respiratory complications, ranging from dyspnoea to residual pulmonary fibrosis. Cardiac symptoms were reported in nine studies, including palpitation, chest pain and diastolic dysfunction. Neurological complications included post-traumatic stress syndrome, anxiety, depression, memory issues, insomnia and sleeping disturbance, cognitive impairments and stigma. Gastrointestinal symptoms included nausea, vomiting, diarrhoea and acute liver injury. The physical decline was the most common symptom reported in the musculoskeletal complications.

Conclusion

COVID-19 may cause several types of complications after recovery (testing negative PCR). The identified complications include respiratory, neurological/mental, cardiovascular, gastrointestinal tract, urinary tract, musculoskeletal and miscellaneous complications. However, the key impairments were pulmonary consequences, psychological problems and exercise intolerance. Thus, COVID-19 patients may need long-term follow-up.

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Publication Date
Tue Aug 01 2023
Journal Name
Baghdad Science Journal
A New Model Design for Combating COVID -19 Pandemic Based on SVM and CNN Approaches
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       In the current worldwide health crisis produced by coronavirus disease (COVID-19), researchers and medical specialists began looking for new ways to tackle the epidemic. According to recent studies, Machine Learning (ML) has been effectively deployed in the health sector. Medical imaging sources (radiography and computed tomography) have aided in the development of artificial intelligence(AI) strategies to tackle the coronavirus outbreak. As a result, a classical machine learning approach for coronavirus detection from      Computerized Tomography (CT) images was developed. In this study, the convolutional neural network (CNN) model for feature extraction and support vector machine (SVM) for the classification of axial

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Publication Date
Wed May 01 2024
Journal Name
Clinical Epidemiology And Global Health
Systemic and cutaneous side effects of COVID-19 vaccines in Iraq, A cross-sectional study
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Publication Date
Wed May 08 2024
Journal Name
Journal Of Mathematics And Computer Science
How does media coverage affect a COVID-19 pandemic model with direct and indirect transmission?
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In this paper, a compartmental differential epidemic model of COVID-19 pandemic transmission is constructed and analyzed that accounts for the effects of media coverage. The model can be categorized into eight distinct divisions: susceptible individuals, exposed individuals, quarantine class, infected individuals, isolated class, infectious material in the environment, media coverage, and recovered individuals. The qualitative analysis of the model indicates that the disease-free equilibrium point is asymptotically stable when the basic reproduction number R0 is less than one. Conversely, the endemic equilibrium is globally asymptotically stable when R0 is bigger than one. In addition, a sensitivity analysis is conducted to determine which

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Publication Date
Tue Oct 01 2024
Journal Name
Journal Of Engineering
A Comprehensive Review for Integrating Petrophysical Properties, Rock Typing, and Geological Modeling for Enhanced Reservoir Characterization
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Reservoir characterization is an important component of hydrocarbon exploration and production, which requires the integration of different disciplines for accurate subsurface modeling. This comprehensive research paper delves into the complex interplay of rock materials, rock formation techniques, and geological modeling techniques for improving reservoir quality. The research plays an important role dominated by petrophysical factors such as porosity, shale volume, water content, and permeability—as important indicators of reservoir properties, fluid behavior, and hydrocarbon potential. It examines various rock cataloging techniques, focusing on rock aggregation techniques and self-organizing maps (SOMs) to identify specific and

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Publication Date
Tue Feb 13 2018
Journal Name
Journal Of Optics
Solar selective performance of metal nitride/oxynitride based magnetron sputtered thin film coatings: a comprehensive review
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Publication Date
Mon Jan 01 2024
Journal Name
Iraqi Journal Of Hematology
Evaluation of Vitamin D level in thalassemia patients: The experience of a single center
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Publication Date
Wed Sep 14 2016
Journal Name
Journal Of Baghdad College Of Dentistry
Salivary Immunoglobulin A Assessment in Lymphoma Patients before and after Chemotherapy
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Background: Lymphomas are group of diseases caused by malignant lymphocytes that accumulate in lymph nodes and caused the characteristics lymphadenopathy. Occasionally, they may spill over into blood or infiltrate organs outside the lymphoid tissue. The major subdivision of lymphomas is into Hodgkin lymphoma and non–Hodgkin lymphoma and this is based on the histologic presence of Reed-Sternberg cells in Hodgkin lymphoma. Salivary immunoglobulin A is the prominent immunoglobulin and is considered to be the main specific defense mechanism in oral cavity. The aim of this study was to determine the level of salivary immunoglobulin A in lymphoma patients before and after chemotherapy treatment. Subjects, materials and methods: The study i

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Publication Date
Sat May 01 2021
Journal Name
Journal Of Physics: Conference Series
The Prediction of COVID 19 Disease Using Feature Selection Techniques
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Abstract<p>COVID 19 has spread rapidly around the world due to the lack of a suitable vaccine; therefore the early prediction of those infected with this virus is extremely important attempting to control it by quarantining the infected people and giving them possible medical attention to limit its spread. This work suggests a model for predicting the COVID 19 virus using feature selection techniques. The proposed model consists of three stages which include the preprocessing stage, the features selection stage, and the classification stage. This work uses a data set consists of 8571 records, with forty features for patients from different countries. Two feature selection techniques are used in </p> ... Show More
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Publication Date
Sun Nov 01 2020
Journal Name
Travel Medicine And Infectious Disease
Incidence of the COVID-19 in Iraq – Implications for travellers
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Publication Date
Wed May 27 2020
Journal Name
Research Gate
Information Booklet COVID-19 Graphs For Iraq First 3 Months
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This booklet contains the basic data and graphs forCOVID-19 in Iraq during the first three months of thepandemic ( 24 February to 19 May - 2020 ) , It isperformed to help researchers regarding this health problem (PDF) Information Booklet COVID-19 Graphs For Iraq First 3 Months. Available from: https://www.researchgate.net/publication/341655944_Information_Booklet_COVID-19_Graphs_For_Iraq_First_3_Months#fullTextFileContent [accessed Oct 26 2024].

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