NCT07509697

Artificial Intelligence-Based Evaluation of Chest X-Rays in Ventilator-Associated Pneumonia

Artificial Intelligence-Based Evaluation of Chest X-Rays in the Diagnosis of Ventilator-Associated Pneumonia in the Intensive Care Unit: A Retrospective Comparative Study

• Status: Completed
• Phase: —
• Study type: Observational
• Enrollment: 119 (actual)
• Sponsor: Dr Abdurrahman Yurtaslan Ankara Oncology Training and Research Hospital · Academic / Other
• Sex: All
• Age: 18 Years
• Healthy volunteers: Not accepted

Summary

Ventilator-associated pneumonia (VAP) is a common and serious infection in critically ill patients receiving mechanical ventilation in intensive care units (ICUs). One of the key diagnostic criteria for VAP is the presence of a new or progressive infiltrate on chest X-ray; however, interpretation of bedside chest radiographs is often challenging and subject to inter-observer variability. This retrospective observational study aims to evaluate the role of artificial intelligence (AI) in the assessment of chest X-rays in patients with VAP. Chest radiographs obtained before and at the time of VAP diagnosis will be analyzed using a deep learning-based AI tool (Chester the AI Radiology Assistant), and changes in "infiltration" and "pneumonia" probability scores will be assessed. AI-based findings will be compared with clinical decisions and independent radiologist evaluations regarding the presence of new infiltrates. The study aims to determine the level of agreement between these approaches and to explore whether AI-based analysis can support a more objective and standardized interpretation of chest radiographs in the diagnosis of VAP.

Conditions

• Ventilator-Associated Pneumonia
• Intensive Care Unit (ICU)
• Pneumonia, Bacterial
• Artificial Intelligence (AI)
• Radiography, Thoracic

Timeline

• Start date: 2026-03-01
• Primary completion: 2026-03-20
• Completion: 2026-03-25
• First posted: 2026-04-03
• Last updated: 2026-04-03

Locations

1 site across 1 country: Turkey (Türkiye)