Artificial Intelligence-Based Evaluation of Chest X-Rays in the Diagnosis of Ventilator-Associated Pneumonia in the Intensive Care Unit: A Retrospective Comparative Study
| Registry | NCT07509697 |
|---|---|
| Status | Completed |
| Study type | Observational |
| Enrollment | 119 (Actual) |
| Sponsor | Dr Abdurrahman Yurtaslan Ankara Oncology Training and Research Hospital (Other) |
| Conditions | Ventilator-Associated Pneumonia, Intensive Care Unit (ICU), Pneumonia, Bacterial, Artificial Intelligence (AI), Radiography, Thoracic |
| Dates | start 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 in Turkey (Türkiye) |
Related Papers Related Patents Related Grants Related Experts
All trials for Ventilator-Associated Pneumonia All trials for Intensive Care Unit (ICU)
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.
| Arm | Type | Interventions | Description |
|---|---|---|---|
| VAP Patients | This cohort includes adult patients admitted to the anesthesia intensive care unit who were mechanically ventilated for at least 48 hours and received a clinical diagnosis of ventilator-associated pneumonia (VAP). For each patient, chest radiographs obtained prior to and at the time of VAP diagnosis were analyzed. Images were evaluated by three approaches: clinical assessment, independent radiologist interpretation, and artificial intelligence-based analysis using the Chester AI system. The study is observational, and no intervention was applied. |
Sex: All, ages: 18 Years to any
Inclusion Criteria: * Adult patients (≥18 years) * Admission to the anesthesia intensive care unit * Requirement of invasive mechanical ventilation for at least 48 hours * Clinical diagnosis of ventilator-associated pneumonia (VAP) based on institutional criteria * Availability of at least one chest X-ray prior to VAP diagnosis and one chest X-ray at the time of diagnosis * Availability of digital chest radiographs in the PACS system suitable for analysis Exclusion Criteria: * Age <18 years * Absence of accessible digital chest radiographs * Chest radiographs with severe technical limitations preventing evaluation * Chest radiographs that could not be processed by the AI system (no score generated) * Presence of extensive pre-existing infiltrative lung disease preventing reliable assessment of new infiltrates * Missing key clinical data (e.g., VAP diagnosis date, mechanical ventilation duration)
| Facility | City | Country | Status |
|---|---|---|---|
| Dr. Abdurrahman Yurtaslan Ankara Oncology Hospital | Yenimahalle, Ankara | Turkey (Türkiye) |