Analyzing Twitter Conversations on Side Effects of Covid-19 Vaccine

This paper mines social media conversations collected using #sideeffects during the early phases of the Covid-19 vaccine roll out. The multi-dimensional analysis seeks to uncover post-vaccination symptoms and their intensity, latent underlying emotions, how the discourse spreads and is received, and ultimately separate the content into two groups according to their severity. The paper infers that people share their severe symptoms that cause major inconvenience and disruption using exaggerated emotions, and the follower networks of these authors are stronger. Tweets outlining mild symptoms are liked and retweeted many more times, and the friends networks of these authors are stronger. Both types of tweets (severe and mild) express heavy surprise and some fear. Classification of the tweets into mild and severe groups is attempted using boosting, neural network and BERT-based natural language transformer methods. BERT significantly outperforms the former two achieving a F1-score of 0.88. Given that the Covid-19 vaccine was developed and deployed rapidly, with limited clinical data on its side effects, this research fills an important gap in gathering such information under real-life settings. The paper thus concludes with a discussion of how these findings could be leveraged by public health organizations to combat vaccine hesitancy and maximize vaccine uptake. © 2022 IEEE.

Development of a wellbeing care plan for staff: Implementation and evaluation within mental health inpatient services

NHS staff have been under increasing pressure since Covid-19. Workload remains a pressing concern (NHS England, 2020). This article describes the implementation and evaluation of a wellbeing care plan designed for staff as a means of supporting their wellbeing. © 2022, British Psychological Society. All rights reserved.

Emergency Department Management and Outcomes of COVID-19 Acute Hypoxemic Respiratory Failure During the New York City Surge

Study Objectives: Delays in intensive care unit (ICU) admission for critically ill patients are associated with worse outcomes, but the effect of “boarding” during the COVID-19 pandemic has not been well characterized. This study describes the emergency department (ED)-based care for patients presenting with COVID-19-related acute hypoxemic respiratory failure (AHRF) to five hospitals in a large, academic health system during the initial surge in New York City, examining both respiratory modality choice and settings. For those managed with noninvasive respiratory support, we also aimed to explore the association between ED boarding time and patient morbidity and mortality. Methods: We conducted a retrospective cohort study of ED patients presenting from 3/1/2020 to 7/10/2020 with COVID-19-related AHRF and requiring ICU admission at any time during their hospitalization. Patient demographics, comorbidities, severity of illness (Mortality Probability Model III on admission), clinical course, including the use, settings (initial and changes), and duration of respiratory support modalities (ie, noninvasive ventilation [NIV], high flow nasal cannula [HFNC], invasive mechanical ventilation [IMV]), as well as hospital site, were collected through validated electronic query and standardized manual chart abstraction. AHRF severity was defined using a PaO2/FiO2 ratio (PF): 200-300 (mild), 100-199 (moderate), and <100 (severe). For patients without a PaO2, the PF was imputed using SpO2/FiO2 ratio using previously validated non-linear conversion. Boarding was defined as the time interval from ED request for admission to ED departure. The primary outcome was a composite outcome of ICU admission, intubation, or mortality within 48 hours of ED arrival. Descriptive analyses stratified by boarding duration and AHRF were completed. Multivariable logistic regression modelling was used to determine the association between ED boarding and the primary outcome. Results: A total of 679 ED patients with COVID-19 AHRF required ICU admission during the study period. They were managed with low flow oxygen only (261, 38.4%), or with NIV (120, 17.7%), HF (51, 7.5%), and/or IMV (99, 14.6%), with setting ranges detailed in Table 1. Of the patients with a known PF ratio (N=418), 110 (26.35%) had mild, 34 (5.0%) had moderate, and 274 (40.4%) had severe AHRF. Of these patients, 279 (41.1%) had a change documented to their settings, with increased likelihood of adjustments with longer boarding time (p<0.001) and higher AHRF severity (p<0.001). Median boarding duration across all site was 9.5 hours (IQR 5.3-16.9 hours) with site variation. AHRF severity and support modality were not associated with differences of boarding time (p = 0.77 and p=0.54). Controlling for age, sex, race, and severity of illness, boarding time was not associated with worse patient outcomes in 48 hours (OR 0.85, 95% CI 0.67-1.08, p=0.17) Conclusion: During the COVID-19 pandemic, critically ill patients presented to the ED and boarded for long periods of time, requiring prolonged ventilatory management. Despite the surge state and resource limitations, boarding times did not worsen post-ED outcomes for patients managed with non-invasive modalities. [Formula presented]