The AIR-CPR Study: AI-Guided Chest Compressions

NCT07431710 | Recruiting

• 1 other identifier: 113046-F
• Study Type: observational
• Target: 255
• Locations: 1 country
• Sites: 1

Brief Summary

The AIR-CPR project aims to improve survival rates for patients with Out-of-Hospital Cardiac Arrest (OHCA) by utilizing Artificial Intelligence (AI) to optimize chest compression locations. Current guidelines recommend a standardized compression point (the lower half of the sternum), yet recent research indicates that this position can compress the aortic valve in approximately 48.7% of patients, significantly reducing the chances of successful resuscitation. This study will develop a deep learning model based on YOLO v8 to analyze real-time arterial pressure waveforms to identify proper aortic valve opening and closing. By identifying specific waveform features that humans cannot easily distinguish, the AI will guide rescuers to adjust the compression site-typically toward the left ventricle-to ensure optimal blood output. The project seeks to transform CPR from a standardized "one-size-fits-all" approach into a personalized, precision medicine intervention.

Conditions

Out-of-hospital Cardiac Arrest (OHCA); Cardiopulmonary Resuscitation (CPR); Aortic Valve Compression; Precision Resuscitation

Keywords

Artificial Intelligence; Transesophageal Echocardiography; Arterial Pressure Waveform; Chest Compression Location; Personalized Resuscitation; Hemodynamic Monitoring

Outcome Measures

Primary Outcomes (1)

• AI Identification Accuracy of Aortic Valve Compression

  The accuracy of the AI model in identifying whether the aortic valve is compressed or open during CPR, using Transesophageal Echocardiography (TEE) as the gold standard for verification.

  Collected during the clinical testing phase and feasibility assessment (Years 2 and 3).

Secondary Outcomes (5)

• Successful Avoidance of Aortic Valve Compression

  During the clinical feasibility assessment (Year 3).

• Time Consumed for Compression Adjustment

  During the clinical feasibility assessment (Year 3).

• Rate of Return of Spontaneous Circulation (ROSC)

  From the start of the emergency department resuscitation until hospital discharge or death (up to approximately 30 days).

• Favorable Neurologic Outcome at Discharge

  At the time of hospital discharge (up to approximately 30 days).

• Chest Compression Fraction (CCF)

  During the clinical feasibility assessment (Year 3).

Study Arms (1)

OHCA Patients Receiving AI-Enhanced Resuscitation.

Adult patients (20 years or older) with non-traumatic Out-of-Hospital Cardiac Arrest (OHCA) who receive Advanced Life Support (ALS) at the Far Eastern Memorial Hospital Emergency Department. This cohort provides the data for AI training (Years 1-2) and participates in the clinical validation of the AI-guided compression technique (Year 3).

Device: Device: AI-Enhanced Arterial Waveform Monitor (AIR-CPR App); Procedure: AI-Guided Chest Compression Repositioning; Diagnostic Test: Transesophageal Echocardiography (TEE)

Interventions

Device: AI-Enhanced Arterial Waveform Monitor (AIR-CPR App) DEVICE

A deep learning application based on the YOLO v8 architecture that analyzes real-time arterial pressure waveforms from a femoral A-line. It identifies whether the current chest compression location is causing aortic valve compression (as confirmed by TEE) and provides immediate feedback to the resuscitation team.

OHCA Patients Receiving AI-Enhanced Resuscitation.

AI-Guided Chest Compression Repositioning PROCEDURE

When the AI application indicates aortic valve compression, the rescuer adjusts the mechanical chest compression (LUCAS) position. Based on literature and AI feedback, the adjustment typically involves moving the compression point downward and toward the left parasternal line to avoid the aortic valve and optimize left ventricular output.

OHCA Patients Receiving AI-Enhanced Resuscitation.

Transesophageal Echocardiography (TEE) DIAGNOSTIC_TEST

Used as the "Gold Standard" throughout the study. TEE is performed during CPR to record the actual opening and closing of the aortic valve and the deformation of cardiac chambers, providing the labels for AI training and the verification for clinical testing.

OHCA Patients Receiving AI-Enhanced Resuscitation.

Eligibility Criteria

• Age: 20 Years+
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

The study population consists of adult patients experiencing non-traumatic out-of-hospital cardiac arrest who are transported to the Emergency Department of Far Eastern Memorial Hospital. This facility is the only medical center in New Taipei City and handles approximately 30% of the city's OHCA cases, ensuring a diverse and high-volume sample of patients receiving advanced life support.

You may qualify if:

• Adults aged 20 years or older.
• Patients with out-of-hospital cardiac arrest (OHCA) undergoing 3.cardiopulmonary resuscitation (CPR) in the emergency department.
• Cardiac arrest caused by non-traumatic factors.

You may not qualify if:

• Pregnant patients.
• Patients with obvious signs of death.
• Patients with a signed "Do Not Resuscitate" (DNR) order.
• Patients requiring extracorporeal cardio-pulmonary resuscitation (ECPR).
• Patients requiring Resuscitative Endovascular Balloon Occlusion of the Aorta (REBOA).
• Cardiac arrest caused by massive hemorrhage, aortic emergencies, tension pneumothorax, cardiac tamponade, or pulmonary embolism.
• History of severe aortic valve disease or previous aortic valve surgery.
• Patients for whom TEE or femoral arterial catheterization is contraindicated.
• Situations where the medical team is unable to perform TEE or femoral arterial catheterization during CPR.

Sponsors & Collaborators

• Far Eastern Memorial Hospital: lead
• National Health Research Institutes, Taiwan: collaborator

Study Sites (1)

Far Eastern Memorinal Hospital

New Taipei City, Banqiao, 220, Taiwan

RECRUITING

Related Publications (49)

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MeSH Terms

Conditions

Out-of-Hospital Cardiac Arrest

Interventions

Echocardiography, Transesophageal

Condition Hierarchy (Ancestors)

Heart Arrest; Heart Diseases; Cardiovascular Diseases

Intervention Hierarchy (Ancestors)

Echocardiography; Cardiac Imaging Techniques; Diagnostic Imaging; Diagnostic Techniques and Procedures; Diagnosis; Ultrasonography; Heart Function Tests; Diagnostic Techniques, Cardiovascular

Central Study Contacts

Sheng-En Chu, physician

CONTACT

886-2-7728-1843; ianchu300@msn.com

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: PROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: physician

Study Record Dates

• First Submitted: February 19, 2026
• First Posted: February 24, 2026
• Study Start: January 6, 2025
• Primary Completion (Estimated): December 31, 2027
• Study Completion (Estimated): December 31, 2027
• Last Updated: February 24, 2026

Record last verified: 2026-02

Data Sharing

• IPD Sharing: Will not share

Locations

TW (1)