Rationale for withholding professional resuscitation in emergency medical system-attended out-of-hospital cardiac arrest

Out-of-Hospital Cardiac Arrest

Survival from out-of-hospital cardiac arrest (OHCA) is predicated on a community and system-wide approach that includes rapid recognition of cardiac arrest, capable bystander CPR, effective basic and advanced life support (BLS and ALS) by EMS providers, and coordinated postresuscitation care. Management of these critically ill patients continues to evolve. This article focuses on the management of OHCA by EMS providers.

Cardiorespiratory Sensors and Their Implications for Out-of-Hospital Cardiac Arrest Detection: A Systematic Review

Out-of-hospital cardiac arrest (OHCA) is a major health problem, with a poor survival rate of 2-11%. For the roughly 75% of OHCAs that are unwitnessed, survival is approximately 2-4.4%, as there are no bystanders present to provide life-saving interventions and alert Emergency Medical Services. Sensor technologies may reduce the number of unwitnessed OHCAs through automated detection of OHCA-associated physiological changes. However, no technologies are widely available for OHCA detection. This review identifies research and commercial technologies developed for cardiopulmonary monitoring that may be best suited for use in the context of OHCA, and provides recommendations for technology development, testing, and implementation. We conducted a systematic review of published studies along with a search of grey literature to identify technologies that were able to provide cardiopulmonary monitoring, and could be used to detect OHCA. We searched MEDLINE, EMBASE, Web of Science, and Engineering Village using MeSH keywords. Following inclusion, we summarized trends and findings from included studies. Our searches retrieved 6945 unique publications between January, 1950 and May, 2023. 90 studies met the inclusion criteria. In addition, our grey literature search identified 26 commercial technologies. Among included technologies, 52% utilized electrocardiography (ECG) and 40% utilized photoplethysmography (PPG) sensors. Most wearable devices were multi-modal (59%), utilizing more than one sensor simultaneously. Most included devices were wearable technologies (84%), with chest patches (22%), wrist-worn devices (18%), and garments (14%) being the most prevalent. ECG and PPG sensors are heavily utilized in devices for cardiopulmonary monitoring that could be adapted to OHCA detection. Developers seeking to rapidly develop methods for OHCA detection should focus on using ECG- and/or PPG-based multimodal systems as these are most prevalent in existing devices. However, novel sensor technology development could overcome limitations in existing sensors and could serve as potential additions to or replacements for ECG- and PPG-based devices.

Automated cardiac arrest detection using a photoplethysmography wristband: algorithm development and validation in patients with induced circulatory arrest in the DETECT-1 study

BACKGROUND

Unwitnessed out-of-hospital cardiac arrest is associated with low survival chances because of the delayed activation of the emergency medical system in most cases. Automated cardiac arrest detection and alarming using biosensor technology would offer a potential solution to provide early help. We developed and validated an algorithm for automated circulatory arrest detection using wrist-derived photoplethysmography from patients with induced circulatory arrests.

METHODS

In this prospective multicentre study in three university medical centres in the Netherlands, adult patients (aged 18 years or older) in whom short-lasting circulatory arrest was induced as part of routine practice (transcatheter aortic valve implantation, defibrillation testing, or ventricular tachycardia induction) were eligible for inclusion. Exclusion criteria were a known bilateral significant subclavian artery stenosis or medical issues interfering with the wearing of the wristband. After providing informed consent, patients were equipped with a photoplethysmography wristband during the procedure. Invasive arterial blood pressure and electrocardiography were continuously monitored as the reference standard. Development of the photoplethysmography algorithm was based on three consecutive training cohorts. For each cohort, patients were consecutively enrolled. When a total of 50 patients with at least one event of circulatory arrest were enrolled, that cohort was closed. Validation was performed on the fourth set of included patients. The primary outcome was sensitivity for the detection of circulatory arrest.

FINDINGS

Of 306 patients enrolled between March 14, 2022, and April 21, 2023, 291 patients were included in the data analysis. In the development phase (n=205), the first training set yielded a sensitivity for circulatory arrest detection of 100% (95% CI 94-100) and four false positive alarms; the second training set yielded a sensitivity of 100% (94-100), with six false positive alarms; and the third training set yielded a sensitivity of 100% (94-100), with two false positive alarms. In the validation phase (n=86), the sensitivity for circulatory arrest detection was 98% (92-100) and 11 false positive circulatory arrest alarms. The positive predictive value was 90% (95% CI 82-94).

INTERPRETATION

The automated detection of induced circulatory arrests using wrist-derived photoplethysmography is feasible with good sensitivity and low false positives. These promising findings warrant further development of this wearable technology to enable automated cardiac arrest detection and alarming in a home setting.

FUNDING

Dutch Heart Foundation (Hartstichting).

Non-prescription drug-associated out-of-hospital cardiac arrest: Changes in incidence over time and the odds of receiving resuscitation

BACKGROUND

Multiple jurisdictions reported a significant increase in out-of-hospital cardiac arrest (OHCA) incidence over the past decade, however the reasons for this remain unclear. We investigated how drug-associated OHCA (DA-OHCA) contributed to overall OHCA incidence, and whether the likelihood of treatment by emergency medical services (EMS) was associated with DA-OHCA classification.

METHODS

Using a large provincial cardiac arrest registry, we included consecutive, non-traumatic adult OHCA from 2016-2022. We classified as drug-associated if there were historical accounts of non-prescription drug use within the preceding 24 hours or evidence of paraphernalia at the scene. We examined year-by-year trends in OHCA and DA-OHCA incidence. We also investigated the association between DA-OHCA and odds of EMS treatment using an adjusted logistic regression model.

RESULTS

Of 33,365 EMS-assessed cases, 1,985/18,591 (11%) of EMS-treated OHCA and 887/9,200 (9.6%) of EMS-untreated OHCA were DA-OHCA. Of EMS-treated DA-OHCA, the median age was 40 years (IQR 31-51), 1,059 (53%) had a known history of non-prescription drug use, and 570 (29%) were public-location. From 2016 to 2022, EMS-treated OHCA incidence increased from 60 to 79 per 100,000 person-years; EMS-treated DA-OHCA incidence increased from 3.7 to 9.1 per 100,000 person-years. The proportion of overall OHCA classified as DA-OHCA increased from 6.1% to 11.5%. DA-OHCA was associated with greater odds of EMS treatment (AOR 1.34; 95%CI 1.13-1.58).

CONCLUSION

Although EMS-treated DA-OHCA incidence increased by nearly three-fold, it comprised a minority of the overall OHCA increase during the study period. DA-OHCA was associated with an increased likelihood of EMS treatment.

The effect of recognition on survival after out-of-hospital cardiac arrest and implications for biosensor technologies

BACKGROUND

Biosensor technologies have been proposed as a solution to provide recognition and facilitate earlier responses to unwitnessed out-of-hospital cardiac arrest (OHCA) cases. We sought to estimate the effect of recognition on survival and modelled the potential incremental impact of increased recognition of unwitnessed cases on survival to hospital discharge, to demonstrate the potential benefit of biosensor technologies.

METHODS

We included cases from the British Columbia Cardiac Arrest Registry (2019-2020), which includes Emergency Medical Services (EMS)-assessed OHCAs. We excluded cases that would not have benefitted from early recognition (EMS-witnessed, terminal illness, or do-not-resuscitate). Using a mediation analysis, we estimated the relative benefits on survival of a witness recognizing vs. intervening in an OHCA; and estimated the expected additional number of survivors resulting from increasing recognition alone using a bootstrap logistic regression framework.

RESULTS

Of 13,655 EMS-assessed cases, 11,412 were included (6314 EMS-treated, 5098 EMS-untreated). Survival to hospital discharge was 191/8879 (2.2%) in unwitnessed cases and 429/2533 (17%) in bystander-witnessed cases. Of the total effect attributable to a bystander witness, recognition accounted for 84% (95% CI: 72, 86) of the benefit. If all previously unwitnessed cases had been bystander witnessed, we would expect 1198 additional survivors. If these cases had been recognized, but no interventions performed, we would expect 912 additional survivors.

CONCLUSION

Unwitnessed OHCA account for the majority of OHCAs, yet survival is dismal. Methods to improve recognition, such as with biosensor technologies, may lead to substantial improvements in overall survival.

Out-of-Hospital Cardiac Arrest

Survival from out-of-hospital cardiac arrest (OHCA) is predicated on a community and system-wide approach that includes rapid recognition of cardiac arrest, capable bystander CPR, effective basic and advanced life support (BLS and ALS) by EMS providers, and coordinated postresuscitation care. Management of these critically ill patients continues to evolve. This article focuses on the management of OHCA by EMS providers.

Performance of the medical priority dispatch system in correctly classifying out-of-hospital cardiac arrests as appropriate for resuscitation

BACKGROUND

Emergency dispatch centres receive emergency calls and assign resources. Out-of-hospital cardiac arrests (OHCA) can be classified as appropriate (requiring emergent response) or inappropriate (requiring non-emergent response) for resuscitation. We sought to determine system accuracy in emergency medical services (EMS) OHCA response allocation.

METHODS

We analyzed EMS-assessed non-traumatic OHCA records from the British Columbia (BC) Cardiac Arrest registry (January 1, 2019-June 1, 2021), excluding EMS-witnessed cases. In BC the "Medical Priority Dispatch System" is used. We classified EMS dispatch as "emergent" or "non-emergent" and compared to the gold standard of whether EMS personnel decided treatment was appropriate upon scene arrival. We calculated sensitivity, specificity, and positive and negative predictive values (PPV, NPV), with 95% CI's.

RESULTS

Of 15,371 non-traumatic OHCAs, the median age was 65 (inter quartile range 51-78), and 4834 (31%) were women; 7152 (47%) were EMS-treated, of whom 651 (9.1%) survived). Among EMS-treated cases 6923/7152 had an emergent response (sensitivity = 97%, 95% CI 96-97) and among EMS-untreated cases 3951/8219 had a non-emergent response (specificity = 48%, 95% CI, 47 to 49). Among cases with emergent dispatch, 6923/11191 were EMS-treated (PPV = 62%, 95% CI 61-62), and among those with non-emergent dispatch, 3951/4180 were EMS-untreated (NPV = 95%, 95% CI 94-95); 229/4180 (5.5%) with a non-emergent dispatch were treated by EMS.

CONCLUSION

The dispatch system in BC has a high sensitivity and moderate specificity in sending the appropriate responses for OHCAs deemed appropriate for treatment by paramedics. Future research may address strategies to increase system specificity, and decrease the incidence of non-emergent dispatch to EMS-treated cases.