Innovative technologies to improve cardiac arrest resuscitation effectiveness

Is this trial a fit for you?

A plain-English reading of the study's rules. Only the study team can confirm whether you qualify.

What this trial studies

This study focuses on enhancing the effectiveness of resuscitation for out-of-hospital cardiac arrest (OHCA) through the development of artificial intelligence algorithms, smartphone applications, and novel devices. It aims to improve the recognition of OHCA and ensure timely and effective interventions by tailoring cardiopulmonary resuscitation (CPR) and defibrillation techniques to individual patient needs. The study will collect biosignals from wearable devices to predict major cardiovascular events and assess the impact of these innovations on survival rates and brain health. By addressing the current limitations in CPR practices, the study seeks to significantly improve outcomes for patients experiencing OHCA.

Why it matters

Who can join: the full rules

AIM 1: PREDICTION AND RECOGNITION OF CARDIAC ARREST AIM 1.1: PREDICT A MAJOR CARDIOVASCULAR EVENT

Inclusion criteria:

* Age 18-70 years;
* Being a healthy volunteer (i.e., an individual with no history of cardiovascular events willing to contribute to the project) or a patient (survivors and non-survivors) who experienced major cardiovascular events (i.e., myocardial infarction or cardiac arrest);
* Users of a smartwatch or smartphone that continuously and automatically collect health data;
* Informed consent.

Exclusion criteria:

* Impossibility to access/export data;
* User did not wear the wearable device for periods longer than 24 hours;
* User did not wear the wearable device in the 4 weeks preceding the event.

AIM 1.2 CARDIAC ARREST DETECTION FROM VIDEOS No patient involved.

AIM 2: TECHNOLOGIES TO INCREASE CPR AND DEFIBRILLATION USE BEFORE AMBULANCE ARRIVAL No patient involved.

AIM 3: PATIENT-TAILORED RESUSCITATION AIM 3.1: CLINICAL STUDY IN PATIENTS WHO RECEIVED CPR

Inclusion criteria:

* Adults (≥ 18 years);
* Patients suffering a non-traumatic cardiac arrest treated with chest compressions (both survivors and non-survivors);
* Received a TEE, chest x-ray, or chest CT scan as the standard clinical assessment following cardiac arrest;
* Informed consent.

Exclusion criteria:

\- Patients with severe thorax/mediastinal deformity.

AIM 3.2 CLINICAL STUDY IN PATIENTS WHO RECEIVED A CHEST CT SCAN

Inclusion criteria:

* Adults (≥ 18 years);
* Received a chest CT scan for any reasons;
* Informed consent.

Exclusion criteria:

\- Patients with severe thorax/mediastinal deformity.

AIM 3.3 MACHINE LEARNING (ML) ALGORITHM No patient involved.

Where it's running

• IRCCS Ospedale San Raffaele
  Milan, Italy Recruiting
• AOU Policlinico Federico II
  Naples, Italy Not yet recruiting
• Azienda Ospedaliera Universitaria Vanvitelli
  Naples, Italy Not yet recruiting

Study contacts

• Principal investigator: Alberto Zangrillo, MD — IRCCS Ospedale San Raffaele
• Study coordinator: Giovanni Landoni, MD
• Email: landoni.giovanni@hsr.it
• Phone: +390226436151

Similar studies

Other studies for the same condition or treatment. Recruiting studies are listed first.

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• Heartsight helps caregivers of kids after cardiac arrest manage uncertainty and fear

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How to take part

1. Review the eligibility criteria above with your treating physician.
2. Check the official listing on ClinicalTrials.gov for the latest contact details and recruitment status.
3. Contact the study coordinator or principal investigator to ask for pre-screening. Pre-screening is free and never obligates you to enroll.