When the machine is wrong. Characteristics of true and false predictions of Out-of-Hospital Cardiac arrests in emergency calls using a machine-learning model

Barriers for Responding to Pediatric Out-of-Hospital Cardiac Arrest During Emergency Medical Calls: A Qualitative Study

BACKGROUND

Rapid recognition of pediatric out-of-hospital cardiac arrest (POHCA) is a critical component to prompt initiation of bystander interventions. We aimed to investigate barriers for responding to POHCA during emergency medical calls.

METHODS AND RESULTS

We included all POHCA calls (aged 0-18 years) from the emergency dispatch center in the Capital Region of Denmark between 2018 and 2021 and excluded POHCAs with no resuscitation order, found dead, where trained health professionals were on site, or where there was no possibility for initiation of cardiopulmonary resuscitation. A qualitative analysis was undertaken. POHCA calls were divided according to the speed of telecommunicator-recognition into 3 groups: POHCA recognition within 90 seconds (group 1), POHCAs recognition >90 seconds (group 2), and POHCAs recognized by the emergency medical services at ambulance arrival (group 3). A total of 20 calls were included. We identified 3 major barriers to telecommunicator recognition of POHCA. First, prolonged conversations between callers and telecommunicators focusing on the cause of the child's condition rather than adherence to the assessment of consciousness and breathing. Second, challenges in assessing breathing such as cases where the child had agonal or unregular breathing or gasping breaths. Finally, callers who were unable to communicate or follow instructions from the telecommunicator.

CONCLUSIONS

Telecommunicator recognition of POHCA is challenged by factors such as prolonged conversations focusing on causes rather than initiating bystander interventions, barriers in assessing breathing, as well as callers' abilities to partake in communication with telecommunicators. Efforts to address these barriers in current dispatch protocols may improve recognition of POHCA.

2024 International Consensus on Cardiopulmonary Resuscitation and Emergency Cardiovascular Care Science With Treatment Recommendations: Summary From the Basic Life Support; Advanced Life Support; Pediatric Life Support; Neonatal Life Support; Education, Implementation, and Teams; and First Aid Task Forces

This is the eighth annual summary of the International Liaison Committee on Resuscitation International Consensus on Cardiopulmonary Resuscitation and Emergency Cardiovascular Care Science With Treatment Recommendations; a more comprehensive review was done in 2020. This latest summary addresses the most recent published resuscitation evidence reviewed by the International Liaison Committee on Resuscitation task force science experts. Members from 6 International Liaison Committee on Resuscitation task forces have assessed, discussed, and debated the quality of the evidence, using Grading of Recommendations Assessment, Development, and Evaluation criteria, and their statements include consensus treatment recommendations. Insights into the deliberations of the task forces are provided in the Justification and Evidence-to-Decision Framework Highlights sections. In addition, the task forces list priority knowledge gaps for further research.

Optimising telecommunicator recognition of out-of-hospital cardiac arrest: A scoping review

Aim

To summarize existing literature and identify knowledge gaps regarding barriers and enablers of telecommunicators' recognition of out-of-hospital cardiac arrest (OHCA).

Methods

This scoping review was undertaken by an International Liaison Committee on Resuscitation (ILCOR) Basic Life Support scoping review team and guided by the Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for scoping reviews (PRISMA-ScR). Studies were eligible for inclusion if they were peer-reviewed and explored barriers and enablers of telecommunicator recognition of OHCA. We searched Ovid MEDLINE® and Embase and included articles from database inception till June 18th, 2024.

Results

We screened 9,244 studies and included 62 eligible studies on telecommunicator recognition of OHCA. The studies ranged in methodology. The majority were observational studies of emergency calls. The barriers most frequently described to OHCA recognition were breathing status and agonal breathing. The most frequently tested enabler for recognition was a variety of dispatch protocols focusing on breathing assessment. Only one randomized controlled trial (RCT) was identified, which found no difference in OHCA recognition with the addition of machine learning alerting telecommunicators in suspected OHCA cases.

Conclusion

Most studies were observational, assessed barriers to recognition of OHCA and compared different dispatch protocols. Only one RCT was identified. Randomized trials should be conducted to inform how to improve telecommunicator recognition of OHCA, including recognition of pediatric OHCAs and assessment of dispatch protocols.

2024 International Consensus on Cardiopulmonary Resuscitation and Emergency Cardiovascular Care Science With Treatment Recommendations: Summary From the Basic Life Support; Advanced Life Support; Pediatric Life Support; Neonatal Life Support; Education, Implementation, and Teams; and First Aid Task Forces

This is the eighth annual summary of the International Liaison Committee on Resuscitation International Consensus on Cardiopulmonary Resuscitation and Emergency Cardiovascular Care Science With Treatment Recommendations; a more comprehensive review was done in 2020. This latest summary addresses the most recent published resuscitation evidence reviewed by the International Liaison Committee on Resuscitation task force science experts. Members from 6 International Liaison Committee on Resuscitation task forces have assessed, discussed, and debated the quality of the evidence, using Grading of Recommendations Assessment, Development, and Evaluation criteria, and their statements include consensus treatment recommendations. Insights into the deliberations of the task forces are provided in the Justification and Evidence-to-Decision Framework Highlights sections. In addition, the task forces list priority knowledge gaps for further research.

Current trends in the management of out of hospital cardiac arrest (OHCA)

Sudden cardiac arrest remains a relevant problem with a significant number of deaths worldwide. Although survival rates have more than tripled over the last 20 years (4% in 2001 vs. 14% in 2020), survival rates with good neurological outcomes remain persistently low, representing a major socioeconomic problem. Every minute of delay from patient collapse to start cardiopulmonary resuscitation (CPR) and early defibrillation reduces the chance of survival by approximately 10-12%. Therefore, the time to treatment is a crucial factor in the prognosis of patients with out-of-hospital cardiac arrest (OHCA). Research teams working in the pre-hospital setting are therefore looking for ways to improve the transmission of information from the site of an emergency event and to make it easier for emergency medical dispatch centres (EMDC) to recognise life-threatening conditions with minimal deviation. For emergency unit procedures already at the scene of the event, methods are being sought to efficiently and temporarily replace a non-functioning cardiopulmonary system. In the case of traumatic cardiac arrest (TCA), the focus is mainly on effective affecting non-compressible haemorrhage.

Clinical decision support system in emergency telephone triage: A scoping review of technical design, implementation and evaluation

OBJECTIVES

Emergency department overcrowding could be improved by upstream telephone triage. Emergency telephone triage aims at managing and orientating adequately patients as early as possible and distributing limited supply of staff and materials. This complex task could be improved with the use of Clinical decision support systems (CDSS). The aim of this scoping review was to identify literature gaps for the future development and evaluation of CDSS for Emergency telephone triage.

MATERIALS AND METHODS

We present here a scoping review of CDSS designed for emergency telephone triage, and compared them in terms of functional characteristics, technical design, health care implementation and methodologies used for evaluation, following the PRISMA-ScR guidelines.

RESULTS

Regarding design, 19 CDSS were retrieved: 12 were knowledge based CDSS (decisional algorithms built according to guidelines or clinical expertise) and 7 were data driven (statistical, machine learning, or deep learning models). Most of them aimed at assisting nurses or non-medical staff by providing patient orientation and/or severity/priority assessment. Eleven were implemented in real life, and only three were connected to the Electronic Health Record. Regarding evaluation, CDSS were assessed through various aspects: intrinsic characteristics, impact on clinical practice or user apprehension. Only one pragmatic trial and one randomized controlled trial were conducted.

CONCLUSION

This review highlights the potential of a hybrid system, user tailored, flexible, connected to the electronic health record, which could work with oral, video and digital data; and the need to evaluate CDSS on intrinsic characteristics and impact on clinical practice, iteratively at each distinct stage of the IT lifecycle.

Artificial intelligence to support out-of-hospital cardiac arrest care: A scoping review

Background

Artificial intelligence (AI) has demonstrated significant potential in supporting emergency medical services personnel during out-of-hospital cardiac arrest (OHCA) care; however, the extent of research evaluating this topic is unknown. This scoping review examines the breadth of literature on the application of AI in early OHCA care.

Methods

We conducted a search of PubMed®, Embase, and Web of Science in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews guidelines. Articles focused on non-traumatic OHCA and published prior to January 18th, 2023 were included. Studies were excluded if they did not use an AI intervention (including machine learning, deep learning, or natural language processing), or did not utilize data from the prehospital phase of care.

Results

Of 173 unique articles identified, 54 (31%) were included after screening. Of these studies, 15 (28%) were from the year 2022 and with an increasing trend annually starting in 2019. The majority were carried out by multinational collaborations (20/54, 38%) with additional studies from the United States (10/54, 19%), Korea (5/54, 10%), and Spain (3/54, 6%). Studies were classified into three major categories including ECG waveform classification and outcome prediction (24/54, 44%), early dispatch-level detection and outcome prediction (7/54, 13%), return of spontaneous circulation and survival outcome prediction (15/54, 20%), and other (9/54, 16%). All but one study had a retrospective design.

Conclusions

A small but growing body of literature exists describing the use of AI to augment early OHCA care.

AI-Enabled Public Surveillance Cameras for Rapid Emergency Medical Service Activation in Out-of-Hospital Cardiac Arrests

This study aims to evaluate the potential usefulness of a novel artificial intelligence (AI)-based video processing algorithm for rapidly activating ambulance services (EMS) in unwitnessed out-of-hospital cardiac arrest (OHCA) cases in public places. We hypothesized that AI should activate EMS using public surveillance cameras after detecting a person fallen due to OHCA. We created an AI model based on our experiment performed at the Lithuanian University of Health Sciences, Kaunas, Lithuania, in Spring 2023. Our research highlights the potential benefits of AI-based surveillance cameras for rapidly detecting and activating EMS during cardiac arrests.