COVID-19: Investigating Strategies for Mechanical Ventilation in COVID-19 via Computational Simulation of Virtual Patients
- Funded by UK Research and Innovation (UKRI)
- Total publications:6 publications
Grant number: EP/V014455/1
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Key facts
Disease
COVID-19Start & end year
20202021Known Financial Commitments (USD)
$442,319.07Funder
UK Research and Innovation (UKRI)Principal Investigator
Declan BatesResearch Location
United KingdomLead Research Institution
University of WarwickResearch Priority Alignment
N/A
Research Category
Clinical characterisation and managementResearch Subcategory
Supportive care, processes of care and managementSpecial Interest Tags
Digital HealthStudy Type
Non-ClinicalClinical Trial Details
N/ABroad Policy Alignment
PendingAge Group
Not ApplicableVulnerable Population
Not applicableOccupations of Interest
Not applicable
Abstract
1]. The pathophysiological basis for this disease phenotype is currently unclear. A recent study also noted a significant time-related disease spectrum in COVID-19 patients, with at least two potential "sub-phenotypes": Type L, characterized by low elastance (i.e. high compliance), low ventilation to perfusion ratio, low lung weight and low recruitability by imaging; and a Type H, characterized by high elastance, high right-to-left shunt, high lung weight and high recruitability
6 Publications linked via Europe PMC
Last Updated:4 days ago
View all publications at Europe PMC