Background Cardiorespiratory arrest (CRA) is a health emergency with high mortality. Mortality could depends on the start time of cardiopulmonary resuscitation (CPR) maneuvers (and the quality of its performance) and the use of the automated external defibrillator (AED).

Methods / design The aim of the study is to determine the effectiveness of a network of volunteers automatically activated by smartwatch and smartphone, on the reduction of the start time of cardiopulmonary resuscitation maneuvers. It is developed in four phases: 1) validation of an application (App) for smartwatch developed to automatically generate a health alert in case of out-of-hospital cardiorespiratory arrest (OHCA); 2) training course in basic CPR maneuvers and use of the AED aimed at the civilian population; 3) creation of a network of volunteers trained in CPR and using the AED that covers the city; 4) simulation study in which members of the network of volunteers will be activated automatically through their smartphone to attend simulated OHCA. 134 activations of the alert will be made. On 67 occasions the alert will be directed to the emergency health services and to the network of volunteers (intervention group). On 67 occasions the alert will be directed to the emergency health services (control group). The arrival time of the first rescuer, category of the first rescuer (emergency services or network of volunteers), start time of the maneuvers and competence in the performance of the maneuvers will be recorded.

Discussion Training in CPR maneuvers is recommended for the civilian population and especially for relatives and close persons of people with heart disease to reduce the start time of CPR and improve survival rates due to CRA. This study aims to observe that the start time of CPR maneuvers and use of the AED will be lower in the intervention group than in the control group.

Methods/design Study aim This clinical trial aims to determine the effectiveness of a network of volunteers trained in CPR maneuvers and using the AED connected through an application (App) for smartwatch, which allows automatic activation in case of out-of-hospital cardiorespiratory arrest (OHCA), on the start time of the CPR maneuvers and use of the AED.

This study will be carried out in 4 phases. 1) validate an App for smartwatch that allows the automatic activation of a network of volunteers trained in CPR maneuvers and use of the AED (Network-CPR) and the emergency services, in case the user of the smartwatch suffers a OHCA; 2) training in basic CPR and use of the AED in the general population; 3) creating a network of volunteers from the subjects trained (Network-CPR); 4) determine the effectiveness of the automatic activation of the Network-CPR through an app for smartwatch on the start time of the CPR maneuvers and use of the AED; and to evaluate the competences in the performance of the maneuvers by the members of the Network-CPR through simulations in the city streets.

Development of the mobile app An App was developed in the Android operating system for smartwatch, an App for mobile smartphones with Android operating systems, and a platform to install in the central computer of the Primary Care Emergency Center (PCEC). In case of detecting an absence of the heart rate (>3 seconds without heartbeat) and falling down to the ground of the smartwatch carrier, the application will send an alert in the first place to the smartwatch, if it is a false positive the smartwatch carrier will deactivate it. If it is a real alert and after 6 seconds the smartwatch carrier does not deactivate it, a warning alert will be generated and sent automatically to an App installed on the smartphones of the members of the Network-CPR (limited to members that are within a radius of 300 meters where the warning alert was generated), and at the same time will also reach a platform installed in the central computer of the PCEC. The members of the Network-CPR will receive on their smartphone the signal with the geolocation of the CRA, the map with the fastest route to reach the location of the CRA and the point where the nearest AED is located.

Phase 1. Validation of the App. This validation will be done through the determination of automatic activations in various locations in the city, it will be determined if the alert reach the members of the Network-CPR and the PCEC and if it is geolocated in a precise way . In addition, during 3 months, four volunteers with high risk of CRA will carry the smartwatch and it will be determined if false activations (false positives) occur during this period of time.

Phase 2 and 3. Training and creation of the Network-CPR that will cover the city. This network will be created with certain population groups that are routinely in contact with susceptible persons of OHCA (police, firemen, teaching staff, health personnel, merchants, pharmacists, university students, gym monitors, etc.), in addition, relatives of people with heart disease will be included. In the case of elderly people who are alone, they will include their neighbors or caregivers. In the city, there are 2,105 people with heart disease susceptible to OHCA. The research team and the health personnel of the participating primary care centers (PCC) will offer training courses on basic CPR maneuvers and use of the AED, following the protocol of the Center Català de Ressucitació (CCR) [14]. The training is aimed at training 430 people (20% of the relatives of people with heart disease) and will be made by trainers accredited by the CCR. There will be a total of 30 sessions with groups of approximately 15 people.

At the end of the training courses, the research team will explain the project and offer voluntary participation in the Network-CPR. Recruitment of 100 participants (25% of the trained participants) is expected. This participation implies having a qualification of suitable, based on the evaluation of the competences during the course; being over 18 years; have a smartphone with Android operating system; the signing of the informed consent document; and the installation of the App receiving the alerts on the smartphone.

Phase 4. Simulation study. A total of 134 simulations will be carried out with simulated CRA warnings alerts in the city. On 67 times, the alerts will reach the Network-CPR and the emergency services (intervention group) and 67 times only the emergency services(control group).

The warnings alerts will be generated in 134 locations randomly, based on the locations where a CRA was notified to the emergency services during the year 2017 (51 locations). The intervention group will be activated through generated alerts that will arrive through the App for smartphones of the members of the Network-CPR that are in a radius of 300 meters; and through the platform installed in the PCEC central computer to the emergency services. The control group will be activated by telephone calls to the PCEC.

The simulations will be carried out during two periods (morning and afternoon). During the time of the simulations a medical doctor and an emergency nurse (PCEC team) will be in the PCEC, to be activated, go to the locations and perform the simulations. The PCEC team will not know in which simulations they are activated or in which the Network-CPR is activated.

At the locations you will find two trained and standardized health personnel (victim team: medical doctor or an emergency nurse and a trainer accredited by the CCR), duly identified, with a CPR mannequin and a practice AED.

Inclusion Criteria:

• Qualification of suitable, based on the evaluation of the competences during the course.
• Being over 18 years.
• Have an smartphone with Android operating system.
• The signing of the informed consent document
• The installation of the App on the smartphone.

Exclusion Criteria

• Qualification of no-suitable, based on the evaluation of the competences during the course.
• No-being over 18 years.
• Have an smatphone with an operating system diferent from Android.
• no-singning of the informed consent document.
• The no-intallation of the App on the smartphone.
• No understood the language.