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.
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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This study attempts to address the importance of communicative digitization in the field of various arts for the sake of continuity of shopping and aesthetic, artistic and intellectual appreciation of artistic achievements by the recipient on various places of their residence in light of the COVID 19 crisis, and to highlight the importance of the plastic arts of the Iraqi painter exclusively and how it expresses in a contemporary way the environment or life reality in Iraq in light of this crisis. With all its implications affecting the life reality from various aspects and methods of its negative and positive employment. As for the research procedures, the researcher reviewed the research methodology represented by the descriptive ana
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We examine 10 hypothetical patients suffering from some of the symptoms of COVID 19 (modified) using topological concepts on topological spaces created from equality and similarity interactions and our information system. This is determined by the degree of accuracy obtained by weighing the value of the lower and upper figures. In practice, this approach has become clearer.
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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<p>Combating the COVID-19 epidemic has emerged as one of the most promising healthcare the world's challenges have ever seen. COVID-19 cases must be accurately and quickly diagnosed to receive proper medical treatment and limit the pandemic. Imaging approaches for chest radiography have been proven in order to be more successful in detecting coronavirus than the (RT-PCR) approach. Transfer knowledge is more suited to categorize patterns in medical pictures since the number of available medical images is limited. This paper illustrates a convolutional neural network (CNN) and recurrent neural network (RNN) hybrid architecture for the diagnosis of COVID-19 from chest X-rays. The deep transfer methods used were VGG19, DenseNet121
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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
(11)
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Drug consultation is an important part of pharmaceutical care. mobile phone call or text message can serve as an easy, effective, and implementable alternative to improving medication adherence and clinical outcomes by providing the information needed significantly for people with chronic illnesses like diabetes and hypertension particularly during pandemics like COVID-19 pandemic.