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Review
. 2023 Nov 20:16:100499.
doi: 10.1016/j.resplu.2023.100499. eCollection 2023 Dec.

Wolf Creek XVII part 3: Automated cardiac arrest diagnosis

Wisse M F van den Beuken  1 , Michael R Sayre  2 , Theresa M Olasveengen  3 , Jacob E Sunshine  4   5
Affiliations
Review

Wolf Creek XVII part 3: Automated cardiac arrest diagnosis

Wisse M F van den Beuken et al. Resusc Plus. .

Abstract

Introduction: Automated cardiac arrest diagnosis offers the possibility to significantly shorten the interval between onset of out-of-hospital cardiac arrest (OHCA) and notification of EMS, providing the opportunity for earlier resuscitation and possibly increased survival.

Methods: Automated cardiac arrest diagnosis was one of six focus topics for the Wolf Creek XVII Conference held on June 14-17 2023 in Ann Arbor, Michigan, USA. Conference invitees included international thought leaders and scientists in the field of cardiac arrest resuscitation from academia and industry. Participants submitted via online survey knowledge gaps, barriers to translation and research priorities for each focus topic. Expert panels used the survey results and their own perspectives and insights to create and present a preliminary unranked list for each category that was debated, revised and ranked by all attendees to identify the top 5 for each category.

Results: Top knowledge gaps include the accuracy of automated OHCA detection technologies and the feasibility and reliability of automated EMS activation. The main barriers to translation are the risk of false positives potentially overburdening EMS, development and application costs of technology and the challenge of integrating new technology in EMS IT systems. The top research priorities are large-scale evaluation studies to measure real world performance and user research regarding the willingness to adopt these technologies.

Conclusion: Automated cardiac arrest diagnosis has the potential to significantly impact time to resuscitation and survival of OHCA because it could convert unwitnessed events into witnessed events. Validation and feasibility studies are needed. The specificity of the technology must be high not to overburden limited EMS resources. If adequate event classification is achieved, future research could shift toward event prediction, focusing on identifying potential digital biomarkers and signatures of imminent cardiac arrest. Implementation could be challenging due to high costs of development, regulatory considerations and instantiation logistics.

Keywords: Automated cardiac arrest diagnosis; Health technology; Out-of-hospital cardiac arrest; Resuscitation; Smart devices; Wearables.

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Conflict of interest statement

The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: [Lisa Coon coordinated the conflict of interest statements].

Figures

Fig. 1
Fig. 1
Automated cardiac arrest diagnosis: Top 5 knowledge gaps as ranked by attendees at Wolf Creek XVII, June 15-17, 2023, Ann Arbor, MI, USA.
Fig. 2
Fig. 2
Automated cardiac arrest diagnosis: Top 5 barriers to translation as ranked by attendees at Wolf Creek XVII, June 15-17, 2023, Ann Arbor, MI, USA.
Fig. 3
Fig. 3
Automated cardiac arrest diagnosis: Top 5 research priorities as ranked by attendees at Wolf Creek XVII, June 15-17, 2023, Ann Arbor, MI, USA.
See this image and copyright information in PMC

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