Artificial Intelligence-based Identification of Imaging Biomarkers of Lung FRAILty in Patients With Acute Respiratory Distress Syndrome.

Status: Recruiting
Location: See all (2) locations...
Intervention Type: Diagnostic test
Study Type: Observational
SUMMARY

The high incidence of barotrauma in patients with COVID-19-related acute respiratory distress syndrome (ARDS) (16.1%, with a mortality rate \>60%) provides rationale for considering COVID-19 ARDS a paradigm for lung frailty. The investigators recently discovered that the Macklin effect is an impressive radiological predictor of barotrauma in COVID-19 ARDS. Since lung frailty is a major issue also in non-COVID-19 ARDS (6% barotrauma, with a mortality rate of 46% ) the investigators want to confirm the importance of Macklin effect in non-COVID-19 ARDS. Using artificial intelligence-based approaches the investigators also want to identify imaging biomarkers to non-invasively assess lung frailty in a mixed cohort of COVID-19/non-COVID-19 ARDS patients. Furthermore, the investigators want to prospectively validate these biomarkers in a cohort of ARDS patients. This will provide a therapeutic algorithm for ARDS patients at high-risk for barotrauma, identifying those most likely to benefit from hyper protective strategies.

Eligibility
Participation Requirements
Sex: All
Minimum Age: 18
Healthy Volunteers: f
View:

• Clinical and radiological signs of ARDS, according to Berlin criteria \[14\], requiring ICU admission;

• Obtain duly signed informed consent.

Locations
Other Locations
Italy
Ospedale Mater Domini
RECRUITING
Catanzaro
IRCCS San Raffaele Scientific Institute
RECRUITING
Milan
Contact Information
Primary
Diego Palumbo, MD
palumbo.diego@hsr.it
+39022643
Backup
Alessandro Belletti, MD
belletti.alessandro@hsr.it
+39022643
Time Frame
Start Date: 2023-08-30
Estimated Completion Date: 2027-07-31
Participants
Target number of participants: 100
Sponsors
Leads: Università Vita-Salute San Raffaele

This content was sourced from clinicaltrials.gov