AI-Assisted Chest X-Ray for Misplaced Endotracheal and Nasogastric Tubes and Pneumothorax in Emergency and Critical Care Settings

NCT ID: NCT06842043

Last Updated: 2025-02-24

Basic Information

• Recruitment Status: NOT_YET_RECRUITING
• Clinical Phase: NA
• Total Enrollment: 10900 participants
• Study Classification: INTERVENTIONAL
• Study Start Date: 2025-03-01
• Study Completion Date: 2027-12-31

Brief Summary

Background Advancements in artificial intelligence (AI) have driven significant breakthroughs in computer-aided detection (CAD) for chest X-ray imaging. National Taiwan University Hospital (NTUH) research team previously developed an AI-based emergency Capstone CXR system (MOST 111-2634-F-002-015-, Capstone project), which led to the creation of a chest X-ray module. This chest X-ray module has an established model supported by extensive research and is ready for direct application in clinical trials without requiring additional model training. This study will utilize three submodules of the system: detection of misplaced endotracheal tubes, detection of misplaced nasogastric tubes, and identification of pneumothorax.

Objective This study aims to apply a real-time chest X-ray CAD system in emergency and critical care settings to evaluate its clinical and economic benefits without requiring additional chest X-ray examinations or altering standard care and procedures. The study will evaluate the CAD system's impact on mortality reduction, post-intubation complications, hospital stay duration, workload, and interpretation time, alongside a cost-effectiveness comparison with standard care.

Methods This study adopts a pilot trial and cluster randomized controlled trial design, with random assignment conducted at the ward level. In the intervention group, units are granted access to AI diagnostic results, while the control group continues standard care practices. Consent will be obtained from attending physicians, residents, and advanced practice nurses in each participating ward. Once consent is secured, these healthcare providers in the intervention group will be authorized to use the CAD system. Intervention units will have access to AI-generated interpretations, whereas control units will maintain routine medical procedures without access to the AI diagnostic outputs.

Results The study was funded in September 2024. Data collection is expected to last from January 2025 to December 2027.

Conclusions This study anticipates that the real-time chest X-ray CAD system will automate the identification and detection of misplaced endotracheal and nasogastric tubes on chest X-rays, as well as assist clinicians in diagnosing pneumothorax. By reducing the workload of physicians, the system is expected to shorten the time required to detect tube misplacement and pneumothorax, decrease patient mortality and hospital stays, and ultimately lower healthcare costs.

Conditions

Endotracheal Tube; Nasogastric Tube; Pneumothorax

Study Design

• Allocation Method: RANDOMIZED
• Intervention Model: PARALLEL
• Primary Study Purpose: DIAGNOSTIC
• Blinding Strategy: NONE

Study Groups

Intervention

Group Type: EXPERIMENTAL

AI-assisted model

Intervention Type: OTHER

physicians will be authorized to access the AI model's predictions during patient care as an additional decision-making reference. These predictions will be generated in seconds and can help identify issues such as tube misplacement (e.g., nasogastric tube, endotracheal tube) and pneumothorax through AI analysis of CXRs, which will alert the physician to review the images.

standard clinical practice

Group Type: NO_INTERVENTION

No interventions assigned to this group

Interventions

AI-assisted model

physicians will be authorized to access the AI model's predictions during patient care as an additional decision-making reference. These predictions will be generated in seconds and can help identify issues such as tube misplacement (e.g., nasogastric tube, endotracheal tube) and pneumothorax through AI analysis of CXRs, which will alert the physician to review the images.

Intervention Type: OTHER

Eligibility Criteria

Inclusion Criteria

• Emergency critical care or intensive care units.
• The units included the patients requiring chest X-rays due to endotracheal intubation, nasogastric tube insertion, or ventilator use with a risk of pneumothorax.

● Patients who are adults and require chest X-ray due to one of the following conditions: endotracheal intubation, nasogastric intubation, or the use of a ventilator with the potential to cause pneumothorax.

Exclusion Criteria

• The unit supervisor doesn't agree to participate in the trial.
• The unit is unable to implement the AI-assisted system (e.g., no data connection or system support).

• Patients in isolation wards.
• Patients in Infant Intensive Care Unit

• Minimum Eligible Age: 18 Years
• Eligible Sex: ALL
• Accepts Healthy Volunteers: No

Sponsors

Fu Jen Catholic University Hospital

OTHER

Sponsor Role: collaborator

Min-Sheng General Hospital

OTHER

Sponsor Role: collaborator

National Taiwan University

OTHER

Sponsor Role: collaborator

National Taiwan University Hospital

OTHER

Sponsor Role: lead

Responsible Party

Responsibility Role: SPONSOR

Locations

National Taiwan University Hospital

Taipei, , Taiwan

Countries

Taiwan

Facility Contacts

Chu-Lin Tsai, Medical Doctor

Role: primary

chulintsai2@ntu.edu.tw

+886-2-2312-3456 ext. 267684

Other Identifiers

202412055DINA

Identifier Type: -

Identifier Source: org_study_id