Changes in Clinical Practice amongst Nepalese Otolaryngologists during COVID-19 Pandemic.

Background COVID-19 pandemic changed clinical practices more so for otolaryngologists due to inevitable risk of exposure. Objective To assess the changes in the clinical practice among Nepalese otolaryngologists during this pandemic. Method It was an observational study conducted as an online survey in the first two weeks of December 2020. A questionnaire pertaining to changes in clinical practice was mailed to 190 registered otolaryngologists working in various provinces of Nepal. Data were entered in Microsoft Excel 2007 and analysed in percentages. Result Out of the 77 (40.5%) who responded, nearly 50% resumed clinical practice after a month of national lockdown restarting everyday consultation by 64.9% mostly in hospital setting (81.8%) after screening patients via fever clinic by 87%. Modifications in clinical examinations was mostly done for neck (85.7%), oral cavity (44.2%) and nose (29.8%) examination with least with for ear examination (3.9%) Regular endoscopic evaluation was avoided by 19.4%. Only around 57% used adequate personal protective equipment. There was 93.5% reduction in elective operations. Mandatory COVID test was done by 89.6% mostly with reverse transcriptase polymerase chain reaction (95.9%) prior to semi-urgent case. Conclusion Changes in clinical practice were adapted to mitigate viral transmission. The changes were evident in the outpatient department where most patients were screened for fever and modifications made in the clinical examinations. Personal protective equipments were worn when available. Operative lists were limited to semi-urgent and urgent cases with covid testing customarily done for semi-urgent cases.

Changes in Clinical Practice amongst Nepalese Otolaryngologists during COVID-19 Pandemic

Background COVID-19 pandemic changed clinical practices more so for otolaryngologists due to inevitable risk of exposure. Objective To assess the changes in the clinical practice among Nepalese otolaryngologists during this pandemic. Method It was an observational study conducted as an online survey in the first two weeks of December 2020. A questionnaire pertaining to changes in clinical practice was mailed to 190 registered otolaryngologists working in various provinces of Nepal. Data were entered in Microsoft Excel 2007 and analysed in percentages. Result Out of the 77 (40.5%) who responded, nearly 50% resumed clinical practice after a month of national lockdown restarting everyday consultation by 64.9% mostly in hospital setting (81.8%) after screening patients via fever clinic by 87%. Modifications in clinical examinations was mostly done for neck (85.7%), oral cavity (44.2%) and nose (29.8%) examination with least with for ear examination (3.9%) Regular endoscopic evaluation was avoided by 19.4%. Only around 57% used adequate personal protective equipment. There was 93.5% reduction in elective operations. Mandatory COVID test was done by 89.6% mostly with reverse transcriptase polymerase chain reaction (95.9%) prior to semi-urgent case. Conclusion Changes in clinical practice were adapted to mitigate viral transmission. The changes were evident in the outpatient department where most patients were screened for fever and modifications made in the clinical examinations. Personal protective equipments were worn when available. Operative lists were limited to semi-urgent and urgent cases with covid testing customarily done for semi-urgent cases. Copyright © 2022, Kathmandu University. All rights reserved.

A Survey on Information Distortion of COVID19: Applying Machine Learning and Natural Language Processing

The online infodemic created a lot of misinformation about covid-19. It is uncontrollable to stop the spreading of misleading information. It has reached a peak where people cannot differentiate fake news from the real one. The rapid spreading of covid19 fake news created a havoc among people. Here in this study, we will be comparing and studying all the ML techniques of AI which can predict the fake news from the real one. And also, NLP is used for understanding the take on text sentiments. By collecting and analyzing all the data from social media i.e., Twitter, Facebook, WhatsApp, Digital news we will start mining for the hoaxes. Here we will be able to see which ML techniques of AI like SVM, random forest, decision tree, logistic regression and some more, can give more precise results, and also to what extend an NLP can predict a sentiment from the given piece of text. Altogether this article explores the potential by demonstrating how algorithms try to understand human sentiments. This provides a new perception of throughout pandemic, how people in general interacts with misinformation and information found on the internet. Out of all, SVM brought out an accuracy of 98%. © 2022 Bharati Vidyapeeth, New Delhi.