Frailty and COVID-19: A Systematic Scoping Review.
Giuseppe MalteseAndrea CorsonelloMirko di RosaLuca SoraciCristiana VitaleFrancesco CoricaFabrizia LattanzioPublished in: Journal of clinical medicine (2020)
Older people have paid a huge toll in terms of mortality during the coronavirus disease-19 (COVID-19) pandemic. Frailty may have contributed to the vulnerability of older people to more severe clinical presentation. We aimed at reviewing available evidence about frailty and COVID-19. We searched PUBMED, Web of Science, and EMBASE from 1 December 2019 to 29 May 2020. Study selection and data extraction were performed by three independent reviewers. Qualitative synthesis was conducted and quantitative data extracted when available. Forty papers were included: 13 editorials, 15 recommendations/guidelines, 3 reviews, 1 clinical trial, 6 observational studies, 2 case reports. Editorials and reviews underlined the potential clinical relevance of assessing frailty among older patients with COVID-19. However, frailty was only investigated in regards to its association with overall mortality, hospital contagion, intensive care unit admission rates, and disease phenotypes in the few observational studies retrieved. Specific interventions in relation to frailty or its impact on COVID-19 treatments have not been evaluated yet. Even with such limited evidence, clinical recommendations on the use of frailty tools have been proposed to support decision making about escalation plan. Ongoing initiatives are expected to improve knowledge of COVID-19 interaction with frailty and to promote patient-centered approaches.
Keyphrases
- coronavirus disease
- community dwelling
- sars cov
- intensive care unit
- clinical trial
- healthcare
- respiratory syndrome coronavirus
- emergency department
- decision making
- clinical practice
- cardiovascular events
- systematic review
- type diabetes
- public health
- randomized controlled trial
- electronic health record
- coronary artery disease
- cardiovascular disease
- machine learning
- high resolution
- big data
- adverse drug
- double blind
- meta analyses