SHAMS-Smart Hospital Assisting Multitasking System

Advancements in robotics and artificial intelligence technologies have added a prominent contribution in healthcare services. Due to the exponential increase in synthetic viruses specifically these days, the Covid-19 pandemic caused a high rate of infection and death of hospitals' staff. SHAMS-Smart Hospital Assisting Multitasking System was proposed as the first line of defense between hospital staff and this epidemic. Using cutting edge technologies, SHAMS utilized robotics, embedded systems, electrical engineering, electronics, computer vision, natural language processing, and software engineering to facilitate its services. SHAMS can autonomously navigate, and sterilize the hospital, recognize hospital staff, understand speech commands, deliver medicines to patient room, and afford services to patients. Moreover, making self-sterilizing. This paper studies the development and the impact of utilizing autonomous robots in the healthcare crisis. This research paper discusses the main modules of SHAMS robot. SHAMS showed its efficiency, reliability, and scalability in the medical domain. SHAMS also paved the way for robotics to be utilized in various fields in the middle east. © 2021 IEEE.

Relationship of the pulmonary disease severity scoring with thromboembolic complications in COVID-19.

PURPOSE: To correlate thromboembolic (TE) complications secondary to COVID-19 with the extent of the pulmonary parenchymal disease using CT severity scores and other comorbidities. METHODS: In total, 185 patients with COVID-19 and suspected thromboembolic complications were classified into two groups based on the presence or absence of thromboembolic complications. Thromboembolic complications were categorized based on location. Chest CT severity scoring system was used to assess the pulmonary parenchymal disease severity in all patients. Based into severity scores, patients were categorized into three groups (mild, moderate, and sever disease). RESULTS: The final study cohort consisted of 171 patients (99 male and 72 female) after excluding 14 patients with non-diagnostic CT pulmonary angiography. The TE group included 53 patients with a mean age of 55.1 ± 7.1, while the non-TE group included 118 patients with a mean age of 52.9 ± 10.8. Patients with BMI > 30 kg/m2 or having a history of smoking and HTN were found more frequently in the TE group (p < 0.05). Patients admitted to ICU were significantly higher in the TE group (p < 0.001). There was statistically significant difference (p = 0.002) in chest CT-SS between the TE group (22.8 ± 11.4) and non-TE group (17.6 ± 10.7). The percentage of severe parenchymal disease in the TE group was significantly higher compared to the non-TE group (p < 0.05). Severe parenchymal disease, BMI > 30 kg/m2, smoking, and HTN had a higher and more significant odds ratio for developing TE complications. CONCLUSION: The present data suggest that severe pulmonary parenchymal disease secondary to COVID-19 is associated with a higher incidence of thromboembolic complications.

Transbronchial lung cryobiopsy performed in acute COVID-19 pneumonia: first report.

A COVID-19 diagnosis is usually based on PCR detection of viral RNA in airway specimens in a patient with typical clinical fea-tures. Histological features of the COVID-19 lung disease are reported from autopsies. Transbronchial cryobiopsy (TBCB) is an evolving technique usually performed in the diagnosis of interstitial lung disease. We report a TBCB in a 76-year-old female patient who had repeatedly tested negative for SARS-CoV-2 infection. The pathological examination revealed the presence of interstitial pneumonia with lymphocytic infiltration. The qRT-PCR against SARS-CoV-2 from a pharyngeal swab was positive after performing the TBCB.

Peripheral ischemic limb necrosis (Acro-ischemia) associated with severe COVID-19 patients (COVID-19 limbs): A report of three cases.

The association between severe coronavirus disease 2019 and hypercoagulable state was observed in many reports. This may be explained by the presence of hypoxia, severe systemic inflammatory response, immobilization due to intensive care unit (ICU) admission, and diffuse intravascular coagulation. We report three patients who were admitted to our respiratory ICU with acute severe respiratory distress syndrome (ARDS) requiring mechanical ventilation due severe acute respiratory syndrome coronavirus 2 infection, who developed severe limb ischemia during the course of the disease.

Mimickers of novel coronavirus disease 2019 (COVID-19) on chest CT: spectrum of CT and clinical features.

COVID-19 (coronavirus disease 2019) is a recently emerged pulmonary infection caused by severe acute respiratory syndrome coronavirus (SARS-CoV-2). It started in Wuhan, China, in December 2019 and led to a highly contagious disease. Since then COVID-19 continues to spread, causing exponential morbidity and mortality and threatening economies worldwide. While the primary diagnostic test for COVID-19 is the reverse transcriptase-polymerase chain reaction (RT-PCR) assay, chest CT has proven to be a diagnostic tool of high sensitivity. A variety of conditions demonstrates CT features that are difficult to differentiate from COVID-19 rendering CT to be of low specificity. Radiologists and physicians should be aware of imaging patterns of these conditions to prevent an erroneous diagnosis that could adversely influence management and patients' outcome. Our purpose is to provide a practical review of the conditions that mimic COVID-19. A brief description of the forementioned clinical conditions with their CT features will be included.