AI reads chest X-Rays to spot deadly ICU lung infections
NCT ID NCT07509697
First seen Jun 27, 2026 · Last updated Jun 27, 2026
Summary
This study looked at whether an artificial intelligence (AI) tool can help doctors diagnose ventilator-associated pneumonia (a serious lung infection) in ICU patients. Researchers analyzed chest X-rays from 119 adults on breathing machines, comparing the AI's readings to doctors' assessments. The goal was to see if AI could make X-ray interpretation more consistent and reliable.
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Study facts
What this study's own registry entry says, in plain language.
- Participants
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119 people
The number who actually took part.
- Started
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Mar 2026
- Finished
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Mar 2026
- Lead sponsor
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Other sponsor
The registry's catch-all category, for sponsors it does not file as a company, a government agency, or a research network.
Who can take part
This study's own entry requirements. Only the study team can say for certain whether you qualify.
Who is studied
The study population consists of adult patients admitted to a tertiary care anesthesia intensive care unit who required invasive mechanical ventilation and received a clinical diagnosis of ventilator-associated pneumonia (VAP). Patients were identified retrospectively through hospital electronic medical records and infection control committee databases. This cohort represents a critically ill ICU population with high disease severity and diverse comorbid conditions.
- Ages
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18 years and older
- Sex
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Anyone
- Healthy volunteers
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Not accepted
This study is not open to healthy volunteers. The entry requirements below say who it is open to.
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Copied word for word from the study's registry entry, so the wording is the study team's rather than ours.
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)
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Conditions
The condition(s) this trial relates to.
As listed by the trial registrant
The condition terms exactly as the trial's registrant entered them.
Contacts and locations
Locations
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Dr. Abdurrahman Yurtaslan Ankara Oncology Hospital
Yenimahalle, Ankara, 06370, Turkey (Türkiye)
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