Background: since December 2019, China and in particularly Wuhan, faced an unprecedented an outbreak challenge of coronavirus disease 2019, caused by the severe acute respiratory syndrome coronavirus 2. Clinical characteristics of Iraqi patients with COVID-19 and risk factors for mortality needed to be shared with the health care providers to improve the overall disease experience. Methods: prospective, single-center study recruited patients with confirmed SARS-CoV-2 infection who were admitted to Al-Shifaa Isolation Center / Baghdad Medical City between the mid of March and the end of April 2020 until had been discharged or had died. Demographic data, information on clinical signs, symptoms, at presentation, treatment, have been collected from patient records and a research questioner. Result: a total of 60 patients with confirmed COVID-19 infection have been included (mean age, 47 years [range, 12-80 years]; 72% male. Comorbidities were identified in 32 cases (53 %) including respiratory disease, cardiovascular disease, hypertension, and diabetes mellitus. Fever and headache were reported in 27 (45%) and 15 (25%) of the cases respectively. Respiratory manifestations recorded as wheezing observed in 3 (5%), rhinorrhea 12 (20%), crackles 3 (5%) sore throat 22 (36%), bronchial breathing 23 (38.3%) with the most of the patients experienced cough 41 (68.3%) and shortness of breath (SOB) 38 (63.3%). Cyanosis is recognized in 3 (5%), convulsion 4 (6.7%), malaise 41 (68.3%). Gastrointestinal manifestations were diarrhea 8 (13.3%), vomiting 12 (20%). Overall mortality was higher in male gender 8 (18.6%) and the overall average age of the died cases was 60.5 years. Conclusion: the infection with COVID-19 is more likely to infect older men with hypertension, diabetes, cardiovascular disease, and respiratory disease as significant risk factors for COVID-19 patients. The understanding of these factors can enhance defining those COVID-19 patients at higher risk, and allow a more targeted and approach to prevent those deaths.
<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
... Show MoreCoronavirus disease (COVID-19) is a global pandemic caused by the severe acute respiratory syndrome coronavirus, SARS-CoV-2. Infection with SARS-CoV-2 primarily occurs through binding to angiotensin-converting enzyme-2 (ACE2), which is abundantly expressed in various anatomical sites, including the nasopharynx, lungs, cardiovascular system, and gastrointestinal and genitourinary tracts. This study aimed to nurses' knowledge and protective health behaviors about prevention of covid-19 pandemic complications.
A descriptive design stud
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Vaccine hesitancy poses a significant risk to global recovery from COVID-19. To date however, there is little research exploring the psychological factors associated with vaccine acceptability and hesitancy in Iraq.
To explore attitudes towards COVID-19 vaccination in Iraq. To establish the predictors of vaccine uptake and vaccine hesitancy in an Iraqi population.
Using a cross-sectional design, 7,778 participants completed an online questionnaire exploring their vaccination status, likelihood of infection, perc
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COVID-19 is a disease that has abnormal over 170 nations worldwide. The number of infected people (either sick or dead) has been growing at a worrying ratio in virtually all the affected countries. Forecasting procedures can be instructed so helping in scheming well plans and in captivating creative conclusions. These procedures measure the conditions of the previous thus allowing well forecasts around the state to arise in the future. These predictions strength helps to make contradiction of likely pressures and significances. Forecasting procedures production a very main character in elastic precise predictions. In this case study used two models in order to diagnose optimal approach by compared the outputs. This study was introduce
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Today, the world is living in a time of epidemic diseases that spread unnaturally and infect and kill millions of people worldwide. The COVID-19 virus, which is one of the most well-known epidemic diseases currently spreading, has killed more than six million people as of May 2022. The World Health Organization (WHO) declared the 2019 coronavirus disease (COVID-19) after an outbreak of SARS-CoV-2 infection. COVID-19 is a severe and potentially fatal respiratory disease caused by the SARS-CoV-2 virus, which was first noticed at the end of 2019 in Wuhan city. Artificial intelligence plays a meaningful role in analyzing medical images and giving accurate results that serve healthcare workers, especially X-ray images, which are co
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atrogenic atrial septal defect (IASD), post Catheter ablation during electrophysiological study simply can be assess with Echocardiography nowadays ablation consider the main line in the managements of patients with various type of arrhythmia. This study aims to de-termine the outcomes of Iatrogenic Atrial Septal Defect (IASD) six months post radiofrequency ablation (RF) procedure of left atrial arrhythmia using non-invasive Transtho-racic Echocardiography (TTE) parameters (LVEF, E/e` and ASD size) with sheath size as predictors of atrial septal defect closure. Patients and methods: A prospective study was con-ducted in Iraqi Centre for Heart Diseases included 47 patients post Electrophysiology procedure and ablation of left atrial SVT were
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Objective To highlight the main demographic characteristics and clinical profiles of female patients registered with breast cancer in Iraq; focusing on the impact of age.Methods This retrospective study enrolled 1172 female patients who were diagnosed with breast cancer at the Main Center for Early Detection of Breast Cancer/Medical City Teaching Hospital in Baghdad. Data were extracted from an established information system, developed by the principal author under supervision of WHO, that was based on valid clinical records of Iraqi patients affected by breast cancer. The recorded information regarding clinical examination comprised positive palpable lumps, bloody nipple discharge, skin changes, bilateral breast involvement, tumor
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Abstract:
The research aims to shed light on the Corona pandemic and its repercussions on the global economy in general, and on the activities of Iraqi economic units in particular. It also aims to show the impact of the auditor’s reporting on the effects of the Corona pandemic on economic units and its reflection on the quality of his reporting. To achieve the objectives of the research, the researcher prepared a questionnaire according to the five-point Likert scale and took into account in its preparation compatibility with the characteristics of the study community, and that the target community for this questionnaire are the economic units listed in the Iraq Stock Exchange that have complet
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Healthcare professionals routinely use audio signals, generated by the human body, to help diagnose disease or assess its progression. With new technologies, it is now possible to collect human-generated sounds, such as coughing. Audio-based machine learning technologies can be adopted for automatic analysis of collected data. Valuable and rich information can be obtained from the cough signal and extracting effective characteristics from a finite duration time interval that changes as a function of time. This article presents a proposed approach to the detection and diagnosis of COVID-19 through the processing of cough collected from patients suffering from the most common symptoms of this pandemic. The proposed method is based on adopt
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The objective of this study was to assess the impact of the COVID-19 pandemic on healthcare providers (HCPs) at personal and professional levels.
This was a cross-sectional descriptive study. It was conducted using an electronic format survey through Qualtrics Survey Software in English. The target participants were HCPs working in any healthcare setting across Iraq. The survey was distributed via two professional Facebook groups between 7 April and 7 May 2020. The survey items were adopted with modifications from three previous studies of Severe Acute Respiratory Syndrome (SARS) and Avia
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