Background: Coronavirus disease-19 (COVID-19) pandemic caused by Severe Acute Respiratory Syndrome Corona Virus 2 (SARS-CoV-2) is a novel disease.
Objectives: Our healthcare sector is at the epicentre of this unprecedented global pandemic challenge and we are not fully aware of it's management. Here we have discussed our learning experience in managing and tackling the COVID-19 pandemic at our institute which will set an example for other hospitals as well as instill confidence in our primary care physicians who are the frontline warriors.
Methods And Results: For combating COVID-19, dedicated teams for its management including logistic support was streamlined. Our capacity was built up for 200 isolation beds including 40 ventilator equipped beds and 645 defined quarantine rooms, to be implemented in phased manner. Till date more than 200 COVID-19 patients have been admitted here. Fever and cough were common presentations. Mortality was high in patients with advanced age or who had multiple co-morbid conditions. Efficient training and infection prevention control have resulted in a satisfactory outcome.
Conclusion: In the wake of this pandemic all hospital setup, with collective responsibility should follow a specified protocol so that our hospital is not converted to the hotspot. COVID-19 has imposed a new challenge where not only patients have to be managed but our health care workers also need to be protected. Telemedicine and our primary care physicians will play a crucial role. Here at a medical institute, medical teaching, and learning atmosphere has to be created amidst the pandemic apprehension for our budding medicos.
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http://dx.doi.org/10.4103/jfmpc.jfmpc_836_20 | DOI Listing |
Sci Rep
December 2024
Department of Neurobiology and Behavior, University of California Irvine, Irvine, CA, 92697, USA.
Preserving the ability to vividly recall emotionally rich experiences contributes to quality of life in older adulthood. While prior works suggest that moderate-intensity physical activity (MPA) may bolster memory, it is unclear whether this extends to emotionally salient memories consolidated during sleep. In the current study, older adults (mean age = 72.
View Article and Find Full Text PDFNat Commun
December 2024
Department of Psychology, Cornell University, Ithaca, NY, USA.
Subjective feelings are thought to arise from conceptual and bodily states. We examine whether the valence of feelings may also be decoded directly from objective ecological statistics of the visual environment. We train a visual valence (VV) machine learning model of low-level image statistics on nearly 8000 emotionally charged photographs.
View Article and Find Full Text PDFJMIR Form Res
December 2024
Department of Psychiatry & Behavioral Sciences, University of Minnesota, Minneapolis, MN, United States.
Background: Anxiety disorders are common in alcohol use disorder (AUD) treatment patients. Such co-occurring conditions ("comorbidity") have negative prognostic implications for AUD treatment outcomes, yet they commonly go unaddressed in standard AUD care. Over a decade ago, we developed and validated a cognitive behavioral therapy intervention to supplement standard AUD care that, when delivered by trained therapists, improves outcomes in comorbid patients.
View Article and Find Full Text PDFCatheter Cardiovasc Interv
December 2024
Department of Cardiology, Angiology and Intensive Care Medicine, University Heart Center Lübeck, Lübeck, Germany.
Background: The new Amplatzer Steerable Delivery Sheath is a delivery system designed to improve ease-of-use and procedural results of left atrial appendage closure (LAAC). We aimed to compare procedural results after switching our LAAC program at a tertiary care center with the Amulet device to the Steerable Delivery Sheath, with a control group of LAAC employing the standard sheath.
Methods: The first n = 32 consecutively treated patients at our site using the Amulet device with the Steerable Delivery Sheath were included in this retrospective analysis.
Front Public Health
December 2024
Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore.
Objective: To characterize the public conversations around long COVID, as expressed through X (formerly Twitter) posts from May 2020 to April 2023.
Methods: Using X as the data source, we extracted tweets containing #long-covid, #long_covid, or "long covid," posted from May 2020 to April 2023. We then conducted an unsupervised deep learning analysis using Bidirectional Encoder Representations from Transformers (BERT).
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