Repetitive Transcranial Magnetic Stimulation (rTMS) as Non-Invasive Therapeutic for Post-Stroke Dysphagia: A Case Report

Introduction and importance: One of the worst complications that affects people with stroke is dysphagia. Dysphagia causes mortality through dehydration, malnutrition, aspiration pneumonia, and suffocation. For stroke survivors to have better results, post-stroke dysphagia must be adequately addressed using proven treatment methods. Presentation of case: A 64-year-old man complaints of difficulty swallowing with Gugging Swallowing Screen scoring (GUSS)= 7 (severe dysphagia) with left hemiparesis and slurred speech due to ischemic stroke on August 14th 2022. Head CT Scan found bilateral lacunar basal ganglia infarcts with brain atrophy. Patients were treated with standard ischemic stroke therapy, medical rehabilitation and repeated Transcranial Magnetic Stimulation (rTMS) procedures for 10 sessions. GUSS was carried out after the 10th session of rTMS and increased to 14 (moderate dysphagia). Discussion: By stimulating the esophagus cortex bilaterally in post-stroke dysphagia, rTMS is known to be beneficial in modulating cortical excitability and minimizing the imbalance between the hemispheres. Furthermore, it appears to be safe and well-accepted by patients. Conclusions: Our case study shows that rTMS in bilateral esophageal cortex is safe and has therapeutic potential in patients with post-stroke dysphagia

ANATOMI UMUM DAN COLLI FACIALIS

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Characteristics and outcomes of an international cohort of 600 000 hospitalized patients with COVID-19

Background: We describe demographic features, treatments and clinical outcomes in the International Severe Acute Respiratory and emerging Infection Consortium (ISARIC) COVID-19 cohort, one of the world's largest international, standardized data sets concerning hospitalized patients. Methods: The data set analysed includes COVID-19 patients hospitalized between January 2020 and January 2022 in 52 countries. We investigated how symptoms on admission, co-morbidities, risk factors and treatments varied by age, sex and other characteristics. We used Cox regression models to investigate associations between demographics, symptoms, co-morbidities and other factors with risk of death, admission to an intensive care unit (ICU) and invasive mechanical ventilation (IMV). Results: Data were available for 689 572 patients with laboratory-confirmed (91.1%) or clinically diagnosed (8.9%) SARS-CoV-2 infection from 52 countries. Age [adjusted hazard ratio per 10 years 1.49 (95% CI 1.48, 1.49)] and male sex [1.23 (1.21, 1.24)] were associated with a higher risk of death. Rates of admission to an ICU and use of IMV increased with age up to age 60 years then dropped. Symptoms, co-morbidities and treatments varied by age and had varied associations with clinical outcomes. The case-fatality ratio varied by country partly due to differences in the clinical characteristics of recruited patients and was on average 21.5%. Conclusions: Age was the strongest determinant of risk of death, with a ∼30-fold difference between the oldest and youngest groups; each of the co-morbidities included was associated with up to an almost 2-fold increase in risk. Smoking and obesity were also associated with a higher risk of death. The size of our international database and the standardized data collection method make this study a comprehensive international description of COVID-19 clinical features. Our findings may inform strategies that involve prioritization of patients hospitalized with COVID-19 who have a higher risk of death

The value of open-source clinical science in pandemic response: lessons from ISARIC

International audienc

ISARIC-COVID-19 dataset: A Prospective, Standardized, Global Dataset of Patients Hospitalized with COVID-19

The International Severe Acute Respiratory and Emerging Infection Consortium (ISARIC) COVID-19 dataset is one of the largest international databases of prospectively collected clinical data on people hospitalized with COVID-19. This dataset was compiled during the COVID-19 pandemic by a network of hospitals that collect data using the ISARIC-World Health Organization Clinical Characterization Protocol and data tools. The database includes data from more than 705,000 patients, collected in more than 60 countries and 1,500 centres worldwide. Patient data are available from acute hospital admissions with COVID-19 and outpatient follow-ups. The data include signs and symptoms, pre-existing comorbidities, vital signs, chronic and acute treatments, complications, dates of hospitalization and discharge, mortality, viral strains, vaccination status, and other data. Here, we present the dataset characteristics, explain its architecture and how to gain access, and provide tools to facilitate its use