The future of resuscitation

Article information

Clin Exp Emerg Med. 2023;10(1):1-4
Publication date (electronic) : 2023 February 16
doi : https://doi.org/10.15441/ceem.23.008
1Department of Emergency Medicine, Yonsei University Wonju College of Medicine, Wonju, Korea
2Research Institute of Resuscitation Science, Yonsei University Wonju College of Medicine, Wonju, Korea
Correspondence to: Kyoung-Chul Cha Department of Emergency Medicine, Yonsei University Wonju College of Medicine, 20 Ilsan-ro, Wonju 26426, Korea Email: chaemp@yonsei.ac.kr
Received 2023 January 24; Revised 2023 January 31; Accepted 2023 January 31.

INTRODUCTION

The estimated annual incidence of emergency medical service (EMS)-treated out-of-hospital cardiac arrest (OHCA) is 30.0 to 97.1 patients per 100,000 population and this will increase with population aging [1,2]. Although cardiopulmonary resuscitation (CPR) guidelines have been updated based on scientific evidence and implemented in clinical practice, no major breakthroughs have been made to improve the survival rate or neurological recovery of cardiac arrest patients [2–4]. Recently, various trials have been attempted in the field of resuscitation with technological advances and system development. This commentary seeks to introduce the future of resuscitation in terms of cardiac arrest treatment and resuscitation science.

NEW TOOLS FOR CARDIAC ARREST RECOGNITION AND EMS ACTIVATION

Wearable devices can obtain varied personalized health data such as blood pressure, oximetry, electrocardiography, or electroencephalography [5]. Despite concerns about the safety and reliability of using wearable devices in healthcare, these “little uncomfortable monitoring systems” can be used to detect early warning signs of sudden cardiac death. Passive agonal breathing detection software using a smartphone speaker has shown high accuracy for detecting and differentiating hypopnea, central apnea, or obstructive apnea [6]. A machine learning-based dispatcher recognition of OHCA demonstrated the potential to surpass human recognition in a randomized clinical trial [7]. A mobile application (app) has been designed to identify prodromal symptoms in patients who are at highest risk for acute cardiac events including acute myocardial infarction or sudden cardiac death (SCD). This system can alert an individual and EMS simultaneously [8]. A single depth camera detecting thoracic and abdominal respiration can be a tool for detecting unanticipated emergencies in a medical facility with insuffcient monitoring systems [9]. This technology can be applied to the detection of cardiac arrest in residential care settings.

INCREASING BYSTANDER CPR WITH A MOBILE PHONE-BASED ALERT SYSTEM

During the treatment of cardiac arrest, CPR and/or automated external defibrillator (AED) use by a bystander has a crucial impact on resuscitation outcomes. A mobile phone can be a medium for alerting potential rescuers to a nearby cardiac arrest. The arrival of citizen responders dispatched by an app or short message system (SMS) before the arrival of EMS is associated with a high rate of bystander CPR and an increase in bystander defibrillation rate resulting in favorable resuscitation outcomes [10–12]. A mobile phone-based alert system can be an important element in establishing a cardiac arrest treatment system in a community to increase survival rates [13].

FACILITATING ACCESS TO PUBLIC AEDs

Early defibrillation is a key treatment for victims with a shockable rhythm [13]. Dispatching citizen responders using an app or SMS increases AED use and improves resuscitation outcomes [10,11]. Inadequate maintenance of public AEDs and limited 24-hour availability are significant issues limiting the effectiveness of public access defibrillation (PAD) programs in the community [14]. The 24-hour accessibility is limited for AEDs installed in places that are not open 24 hour. Whether the installation site is open 24 hours should be considered when planning a PAD program. Installation of AEDs on walls outside of buildings is one way to facilitate access to AEDs. The delivery of AEDs to the scene of cardiac arrest by drones is emerging as a new way to increase onsite defibrillation. Delivery of an AED by drones shortens total time from cardiac arrest to AED use compared to ground search for an AED [15]. An autonomous drone AED system activated by trained citizen responders is feasible and makes it possible to perform defibrillation before EMS arrival [16]. Integration of an automatic chest compression device and an AED as an all-in-one CPR device may shorten the time from collapse to chest compression and defibrillation, which could increase survival and improve neurologic outcomes in OHCA patients.

OPTIMIZING PERFUSION DURING CPR

Physiology-directed CPR results in better resuscitation outcome than advanced life support conforming to the current CPR guidelines [17,18]. However, since hemodynamic measurements can only be performed in hospitals equipped with invasive monitoring equipment, there are limitations in the general application of physiology-directed CPR. Development of technologies for waveform analysis of chest compression and prediction of hemodynamic parameters will make it possible to guide high quality, physiologydirected CPR during prehospital resuscitation [19,20]. Prehospital application of extracorporeal CPR can be used to optimize perfusion in OHCA patients as extracorporeal membrane oxygenators are becoming more compact and easier to apply to patients [21].

REINFORCING THE SURVIVAL ENVIRONMENT FOR CARDIAC ARREST

The survival environment for cardiac arrest includes medical and nonmedical factors related to the prevention, treatment, and rehabilitation of victims of cardiac arrest [13]. Technological advances in medical and nonmedical aspects will reinforce the survival environment of cardiac arrest in the future. For example, widespread use of social media will increase public awareness of cardiac arrest and CPR, improve CPR education, and thus raise the rate of bystander CPR and early defibrillation.

Primary prevention of SCD is the best way to prevent the consequences arising in the event of cardiac arrest. Recent studies investigating risk factors for SCD suggest that healthy lifestyle modifications are associated with low odds of SCD occurrence [22–24]. Machine learning-based analysis of large population-based clinical data and omics technology using minimal blood samples have attracted attention in terms of SCD risk factor analysis [25,26]. These new technologies can predict the risk of SCD, not only in the individual but also in the population, which can be applied to establishing regional and national healthcare policies to reduce SCD.

Changes in the community can affect the survival environment for cardiac arrest. The COVID-19 pandemic forced us to shift the methods of CPR education from group-based simulation to self-training with or without virtual-reality or blended learning [27–29]. The technological developments in CPR education triggered by the COVID-19 pandemic may contribute to improving accessibility and implementation of CPR education.

Regional variation in cardiac arrest survival is a growing issue in resuscitation science [1]. Standardization and regionalization of the survival environment for cardiac arrest should be implemented globally by creating standardized registries and applying the results from these registries to policies to improve cardiac arrest survival.

CONCLUSION

New technologies such as wearable devices, mobile phones and apps, remote monitoring devices, social media, drones, and hemodynamic CPR feedback devices will contribute to improved cardiac arrest survival in several ways, including early detection of cardiac arrest, promotion of public awareness of cardiac arrest and wider availability of CPR education, early CPR and defibrillation, and optimization of perfusion in the near future. Solutions to reinforcing the survival environment for cardiac arrest should be developed by creating global registries, identifying populations at high risk for cardiac arrest, and establishing effective cardiac arrest treatment systems.

Notes

CONFLICT OF INTEREST

No potential conflict of interest relevant to this article was reported.

FUNDING

None.

AUTHOR CONTRIBUTIONS

Conceptualization: KCC; Data curation: KCC; Visualization: all authors; Writing–original draft: KCC; Writing–review & editing: SOH.

All authors read and approved the final manuscript.

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