Coronary Artery Calcium Score: Current Efficacy of Cardiac CT in Patients at Hail Region, Saudi Arabia

Calcium levels in the Coronary Artery are an indicative marker of the presence and extent of atherosclerosis. This serves as an additional prognostic indicator in addition to traditional risk factors. Moreover, the coronary calcium test is associated with a descriptor known as the calcium score or calcium score (Cs), which is primarily useful for stratifying the risk of asymptomatic patients, while for patients with acute or chronic chest pain, coronary axial computed tomography is generally required. A retrospective analysis of data was conducted in the radiology department of King Salman Specialist Hospital in Hail City, the kingdom of Saudi Arabia, between January and May 2022. A total of 40 patients were randomly selected, 25 males and 15 females. The study included all patients with or suspected of having a calcium deposit who underwent a CT scan using the Siemens SOMATOM definition MDC scan. Patients underwent a scan with the preparations and laboratory tests required for their coronary artery calcium scores. In this study, males were more likely to be affected by calcium deposits (64%), whereas females were 36%. Approximately 50 percent of the study populations were found to be normal (no identifiable calcium deposits) and 37.5% to have moderate calcium deposits. There is a significant association between CACS and moderate CVD risks based on age and gender in this study. Better control of cardiovascular system (CVS) risks is recommended in all primary care centers in the Kingdom of Saudi Arabia (KSA).Copyright © 2022 International Journal of Pharmaceutical Research and Allied Sciences. All rights reserved.

Automated Detection of Covid-19 from X-ray Using SVM

Earlier discovery of COVID-19 through precise diagnosis, particularly in instances with no evident symptoms, may reduce the mortality rate of patients. Chest X-ray images are the primary diagnostic tool for this condition. Patients exhibiting COVID-19 symptoms are causing hospitals to become overcrowded, which is becoming a big concern. The contribution that machine learning has made to big data medical research has been very helpful, opening up new ways to diagnose diseases. This study has developed a machine vision method to identify COVID-19 using X-ray images. The preprocessing stage has been applied to resize images and enhance the quality of X-ray images. The Gray-level co-occurrence matrix (GLCM) and Gray-Level Run Length Matrix (GLRLM) are then used to extract features from the X-ray images, and these features are combined to develop the performance classification via training by Support Vector Machine (SVM). The testing phase evaluated the model's performance using generalized data. This developed feature combination utilizing the GLCM and GLRLM algorithms assured a satisfactory evaluation performance based on COVID-19 detection compared to the immediate, single feature with a testing accuracy of 96.65%, a specificity of 99.54%, and a sensitivity of 97.98%. © 2022 IEEE.

Benchmarking Framework for COVID-19 Classification Machine Learning Method Based on Fuzzy Decision by Opinion Score Method

Coronavirus disease (COVID-19), which is caused by SARS-CoV-2, has been announced as a global pandemic by the World Health Organization (WHO), which results in the collapsing of the healthcare systems in several countries around the globe. Machine learning (ML) methods are one of the most utilized approaches in artificial intelligence (AI) to classify COVID-19 images. However, there are many machine-learning methods used to classify COVID-19. The question is: which machine learning method is best over multi-criteria evaluation? Therefore, this research presents benchmarking of COVID-19 machine learning methods, which is recognized as a multi-criteria decision-making (MCDM) problem. In the recent century, the trend of developing different MCDM approaches has been raised based on different perspectives;however, the latest one, namely, the fuzzy decision by opinion score method that was produced in 2020, has efficiently been able to solve some existing issues that other methods could not manage to solve. because of the multiple criteria decision-making problem and because some criteria have a conflict problem. The methodology of this research was divided into two main stages. The first stage related to identifying the decision matrix used eight different ML methods on chest X-ray (CXR) images and extracted a new decision matrix so as to assess the ML methods. The second stage related to FDOSM was utilized to solve the multiple criteria decision-making problems. The results of this research are as follows: (1) The individual benchmarking results of three decision makers are nearly identical;however, among all the used ML methods, neural networks (NN) achieved the best results. (2) The results of the benchmarking group are comparable, and the neural network machine learning method is the best among the used methods. (3) The final rank is more logical and closest to the decision-makers' opinion. (4) Significant differences among groups' scores are shown by our validation results, which indicate the authenticity of our results. Finally, this research presents many benefits, especially for hospitals and medical clinics, with a view to speeding up the diagnosis of patients suffering from COVID-19 using the best machine learning method. © 2023 University of Baghdad-College of Science. All rights reserved.

The Prevalence of Anemia and Hematological Findings in COVID-19 Patients in Saudi Arabia

Objectives: The aim of this study was to estimate the prevalence of anemia among COVID-19 patients in Saudi Arabia and evaluate their hematological parameters. Materials and Methods: A descriptive, cross-sectional, hospital-based study was conducted between February 2021 to March 2021, data collection covered the period between September 2020 to March 2021. All the patients were hospitalized for confirmed COVID-19. Results: A total of 6048 COVID-19 patients included in our study, 2358 (48.9%) were anemic, 3666 (60.61%) were normal HGB level, and only 24 (0.49%) were having polycythemia. Hemoglobin level ranged from 5 g/dL to 18 g/dL with a median (interquartile range) of 11.8 g/dL (8.9 to 13.1) g/dL. The median for male (interquartile range) was for anemic patient’s 9.8 g/dL (8.5 to 11.4) g/dL, normal 14 g/dL (13.5 to 14.8) g/dL, and polycythemia 17.4 g/dL (17.2 to 17.7) g/dL. The median for female (interquartile range) was for anemic patient’s 9.1 g/dL (8.2 to 10.2) g/dL, normal 13.5 g/ dL (12.5 to 14.5) g/dL, and polycythemia 17 g/dL (16.82 to 17.2) g/dL. Hematological parameters detected are indicative of severe complications in anemic patients compared to non-anemic patients. Conclusion: Our findings were consistent with other studies that reported poor outcomes of anemia in COVID-19 patients. © 2022, Association of Pharmaceutical Teachers of India. All rights reserved.

A Case of COVID-19 in an Elderly Patient Evaluated by Axial CT Presented with Severe Signs and Symptoms: A Correlation of Severe Hypoxia with Remaining Lung Tissue

Identification of computerized tomography (CT) characteristics of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is essential to early diagnosis and treatment of patients and stage the disease according to the appearance of the lung field involvement. The CT chest images of a patient with severe SARS-CoV-2 were collected to assess the CT findings and characteristics. Patchy ground-glass opacities (GGO) were found in some upper lung zones with right upper lung interlobar septal thickening and formation of consolidation throughout the middle and lower zones of the lungs of Crazy Paving pattern type. The remaining lung tissue is directly proportional to the measured oxygen concentration in a severe symptomatic COVID-19 case. These findings are beneficial for early detection and assessment of the severity of SARS-CoV-2.

IVC STENT CAUSING RIGHT ATRIAL(RA)-AORTIC(AO) FISTULA

Background: Venous stents are small mesh tubes used mostly for SVC stenosis, SVC syndrome, May-Thurner syndrome and to a lesser extent for IVC obstruction/stenosis. Even though this procedure can relieve obstruction, it has been associated with a wide variety of complications such as thrombosis, migration, obstruction and fracture. Limited guidelines exist about the use of such stents in the IVC. We present a rare case of IVC stent migration causing RA-AO fistula in a 56 year old female. Case: 56 year old female with a history including Autoimmune thyroiditis, hepatitis, breast cancer, recurrent VTE on warfarin found to have IVC stenosis leading to IVC BMS stent 24 x 70mm Wallstent placement in March 2021 after a new DVT was found while on warfarin, switched to Xarelto, COVID pneumonia in august with SOB with a workup showing extension of the IVC stent to the right atrium. Her fatigue and SOB was initially attributed to COVID pneumonia and she was scheduled to have a repeat TTE as outpatient to follow up on the stent. She continued to have worsening SOB and fatigue even after recovering from COVID PNA. Decision-making: Repeat TTE showed severe MR that was not present before and confirmed the presence of the IVC stent in the RA. TEE showed right atrial-aortic cusp fistula attributed to IVC wallsent extending from RA to Aorta leading to high output state and therefore severe MR carpentier IIIb. The patient was admitted to the hospital where a surgical intervention was entertained, she had LHC and RHC that showed normal coronaries with severe Pulmonary hypertension and Qp/Qs: 1.89. Surgical consultation was obtained and she underwent patch repair of aortic fistula with partial IVC stent removal and MV and TV repair. Conclusion: An arteriovenous fistula involving the coronary arteries and the aorta is rare. Even though IVC stents have the potential to alleviate symptoms caused by large narrowed veins, It is important to recognize complications caused by such stents especially in a patient with new Symptoms of heart failure and Valvular regurgitation as an Iatrogenic cause that requires prompt surgical consultation and intervention.

Estimation of levels of TNF α, INF α related with serum levels of ferritin and D-dimer the prognosis of SARS CoV 2 infection

Tumor necrosis factor (TNF) and interferon gamma (IFN-γ) are pro-inflammatory and anti-inflammatory cytokine that is central to the development of autoimmune disease, cancer, and protection against infectious pathogens. A case-control study was conducted in the AL HUSSAIN Teaching General hospital in Thi-Qar governorate with a total of 190 individuals involved in the current study, 95 of them were infected with SARC COV 2, and 95 were healthy as control group. Serum was collected from each of them to assess the levels of The, TNFα, INFα, ferritin, D-dimer. TNF-α level increased significantly (P<0.05) (67, 50.6 and 15.25Pg/L), IFN-γ level significantly reduced (P<0.05) (21, 17 and 6.2IU/L), serum ferritin was significantly increased (P<0.05) (685.2, 395, and 87ng/ml). At the last one D dimer (1.7, 0.9 and 0.05mg/L) in the both patient groups (infected and non-infected) and healthy persons. The mean of TNFα, INFα concentration were higher in patients than control group (P<0.05). © 2021 Iranian Society of Ichthyology.

A Fusion Scheme of Texture Features for COVID-19 Detection of CT Scan Images

Coronavirus (COVID-19) is a new contagious disease reasoned by a new virus that is widely spread over the world, this virus never has been identified in humans before. Respiratory disease can be affected by this virus such as flu with several symptoms, for example, fever, headache, cough, and pneumonia. COVID-19 presence in humans can be tested through blood samples or sputum while the result can be obtained in days. Further, biomedical image analysis assists in showing signs of pneumonia in a patient. Therefore, this paper aims to provide a fully automatic COVID-19 identification system by proposing a new fusion scheme of texture features for CT scan images. This paper presents a fusion scheme based on a machine learning system using three significant texture features, namely, Local Binary Pattern (LBP), Fractal Dimension (FD), and Grey Level Co-occurrence Matrices (GLCM). In experimental results, to demonstrate the efficiency of the proposed scheme we have collected 300 CT scan images from a publicly available database. The experimental result shows the performance of LBP, FD, and GLCM obtained an accuracy of 89.87%, 87.84%, and 90.98%, respectively while the proposed scheme yields better results by achieving 96.91% accuracy. © 2020 IEEE.

Assessment of physical performance and offensive skills during the coronavirus pandemic for a period of three months among advanced handball players

Maintaining a healthy lifestyle has become one of the great challenges facing the world amid the current Coronavirus pandemic, along with the challenge of maintaining the strength of the immune system so that it can do its work efficiently and protect the person from the severity of Covid-19 symptoms in the event of catching an infection. In light of the current situation of a large spread of the pandemic around the world, physical activity has taken special importance as it enhances immune function, reduces inflammation, and thus can reduce the severity of infection and the severity of Covid-19 symptoms. It also helps improve common chronic diseases, which are strongly linked to COVID-19 symptoms. On the other hand, sports and movement tasks are one of the best ways to calm tension and anxiety, which contributes to better physical health that challenges Corona virus. As for the most important objectives of the research, it is to identify the impact of the Corona virus pandemic during periods of absence from training for advanced handball players and to know the differences in physical performance and offensive skills during a three-month break from training for advanced handball players. As for the research methodology, it is the descriptive method and the sample was chosen by an intentional method, which included (40) players in the hand game from the clubs of Misan Governorate, and it was divided into (40) advanced players for the main experiment and (10) players for exploratory experiments. For offensive skills, the most important conclusions of the research are the tests that have been identified that have the ability to evaluate in the field using direct measurement methods during the Coronavirus pandemic. As for the most important recommendations, these tests could be adopted as evaluation methods by coaches before entering training programs to prepare players after the ban ends and to allow the practice of sporting activities.

Cardiovascular risk factors in COVID-19 and artificial intelligence-an innovative approach to current pandemic

Background: Coronavirus 2019 (COVID-19), also known as Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), infection is a pandemic that causes acute respiratory injury, hospital admission and death. Older adults are at a higher risk of serious illness and death from this pandemic. Many COVID-19 patients have a pre-existing cardiovascular disease (CVD). We aim to develop a risk factor stratification tool, using Artificial Intelligence (AI) method, to predict mortality, ICU admission, and length of hospital stay, in patients with CVD during this pandemic. Methods: This is a retrospective cohort study. An IRB approval was obtained. Patients with confirmed (SARS-Cov-2) test, age more than 60 and older, who were admitted to the Sparrow hospital between March 2020 and October 2020 were included. CV risk factors including Hypertension (HTN), Chronic Ischemic Heart Disease (CHD), Heart Failure (HF), and Cardiac Arrhythmia (CA) were used. Results: Of the 426 patients with COVID-19(mean age:74.5 years), at least 1 CVD was identified in most patients. HTN being the most common (55%), followed by CHD (22%), HF (20%) and CA (3%). Multivariable logistic regression has been conducted to identify risk factors for adverse outcomes and competing risk survival analysis for mortality. Outcomes measures included hospital stay > 7 days, ICU admission, and death. Discussion: Our data suggests patients with HTN required longer hospital stay, had higher ICU admissions and death rate. Conclusion: CV risk factors are common in older adults. HTN is the commonest CVD in this population. Several CV risk factors may contribute to the severity of COVID19 and its impact on older adults. Our study suggests that CV risk factors including HTN, HF, CHD, and CA have major impact on COVID-19 infection in hospitalized geriatric populations - see graph 1. Patients with HTN, had longer hospital stay, ICU admission, and mortality. Based on this work, we suggest that a large data sample might be required to develop an AI software that can help predict outcomes and the need for certain resources for older patients.

Identify human cluster of differentiation 147 (CD147), a new target of SARS-CoV-2 invasion

Objective: to determine the level of blood markers of cellular Human Cluster of Differentiation 147 (CD147) by ELISA assay. Immunological system, establishing the profile in patientsSARS-CoV-2 invades host cells via a novel route: CD147-spike protein. Methods: a case-control study including 30 patients (10 female) with SARS-CoV-2 repertory disorder whose follow-up was carried out at the outpatient clinic of the intensive care unit Service at Al Hussain Hospital, southern of Iraq, Patients were divided into three subgroups based on the onset of symptoms within the first 6 days of the acute phase of disease: subgroup A, subgroup B, and C. according to the type of drugs. Main systemic subgroup. Treatment group included 60 outpatients (25 female) being submitted to follow-up at the same hospital for non-inflammatory diseases. For determined the plasmatic levels of Human Cluster of Differentiation 147 (CD147), groups of S proteins Results: To start with, in vitro antiviral tests showed Meplazumab, infliximab and Etrolizumab an foe of CD147 adapted neutralizer, essentially hindered the infections from attacking host cells in comparison to controls, patients with presented concentrations of CD147 products (determined by plasmatic levels of S protein circulating in blood. Conclusion: our results indicate the presence of molecular SARS-CoV-2 invades respiratory cells determined by assay in patients which confirm a decrease in the defense capacity of the cellular system against toxicity induced by drugs in these patients. © 2020, Advanced Scientific Research. All rights reserved.