Exploration of Diagnosis and Treatment Strategies and Prognostic Prediction Models for Acute Respiratory Distress Syndrome Based on Radiographic Evaluations Assessed by Artificial Intelligence

Fudan University

Status: Completed

Conditions: ARDS (Acute Respiratory Distress Syndrome); AI (Artificial Intelligence)

Treatments: Diagnostic Test: CT scan

Study type: Observational

Funder types: Other

Identifiers

NCT07328997

B2024-180

Details and patient eligibility

About

By using multi-center chest CT data, an intelligent assessment model for the severity of ARDS was constructed. Based on CT quantitative features and clinical characteristics, a prediction model for short-term critical events (such as mechanical ventilation decisions, prone position strategies, death, ECMO use, etc.) was established. The disease was staged and quantified, and a diagnosis and risk stratification model for ARDS was developed to assist in guiding the diagnosis and treatment strategies for ARDS.

Enrollment: 400 patients

Sex: All

Ages: 18 to 100 years old

Volunteers: No Healthy Volunteers

Inclusion criteria

• Meets the diagnostic criteria for ARDS
• Be admitted to the intensive care unit
• There are chest CT images

Exclusion criteria

• Age less than 18 years old
• Missing medical records
• No chest CT images

Trial design

400 participants in 1 patient group

Training group, testing group, validation group

Description:

The study adopts a stratified random sampling strategy with an 8:2 split to construct training and internal validation datasets, together with an independent external test cohort from a separate center. No randomization of clinical interventions or treatments is involved. The model will be developed and evaluated using observational data derived from real-world clinical pathways and outcomes, with the objectives of assessing performance in disease severity stratification, treatment recommendation, and mortality prediction. Model performance will be compared with established ICU severity scores and existing AI-based approaches according to a prespecified statistical analysis plan.

Treatment:

Diagnostic Test: CT scan