ERS International Congress 2021: highlights from the Allied Respiratory Professionals assembly.
Lucy RobertsonFilipa MachadoSebastian RutkowskiLiliana SilvaSabina MirandaIngeborg Farver-VestergaardThomas JanssensKarl P SylvesterChris BurtinAndreja ŠajnićJoana CruzPublished in: ERJ open research (2022)
This paper provides an overview of some of the most memorable sessions that were (co)organised by the Allied Respiratory Professionals Assembly during the 2021 European Respiratory Society International Congress, which was held online for the second consecutive year due to the COVID-19 pandemic. Early Career Members from Assembly 9 summarised the content of the sessions (three oral communication sessions, two symposia and one Expert View) with the support of the chairs from the four Assembly groups: Respiratory Function Technologists and Scientists (Group 9.01); Physiotherapists (Group 9.02); Nurses (Group 9.03); and Psychologists and Behavioural Scientists (Group 9.04). The sessions covered the following topics: impact of COVID-19 on lung function and healthcare services, and the importance of quality assurance and technology in lung function assessment; diagnosis and management of sarcopenia in patients with chronic respiratory disease; maintenance of the effects of pulmonary rehabilitation; solutions outside the hospital for the management of patients with COVID-19 in need of health care; the nursing perspective during the COVID-19 pandemic; and psychological and behavioural issues in respiratory care. This highlights article provides valuable insight into the latest scientific data and emerging areas affecting clinical practice of allied respiratory professionals.
Keyphrases
- healthcare
- lung function
- cystic fibrosis
- air pollution
- clinical practice
- chronic obstructive pulmonary disease
- respiratory tract
- mental health
- sars cov
- coronavirus disease
- skeletal muscle
- pulmonary hypertension
- social media
- primary care
- palliative care
- quality improvement
- health information
- drug induced
- machine learning
- big data
- sleep quality
- respiratory syndrome coronavirus
- clinical evaluation