Bystander defibrillation for out-of-hospital cardiac arrest in Ireland.

Aims: To describe and explore predictors of bystander defibrillation in Ireland during the period 2012 to 2020. To examine the relationship between bystander defibrillation and health system developments. Methods: National level Out of Hospital Cardiac Arrest (OHCA) registry data were interrogated, focusing on patients who had defibrillation performed. Bystander defibrillation (as compared to EMS initiated defibrillation) was the key outcome of concern. Logistic regression models were built and refined by fitting predictors, performing stepwise variable selection and by adding pairwise interactions that improved fit. Results: The data included 5,751 cases of OHCA where defibrillation was performed. Increasing year over time (OR 1.17, 95% CI 1.13, 1.21) was associated with increased adjusted odds of bystander defibrillation. Non-cardiac aetiology was associated with reduced adjusted odds of bystander defibrillation (OR 0.30, 95% CI 0.21, 0.42), as were increasing age in years (OR 0.99, 95% CI 0.987, 0.996) and night-time occurrence of OHCA (OR 0.67, 95% CI 0.53, 0.83). Six further variables in the final model (sex, call response interval, incident location (home or other), who witnessed collapse (bystander or not witnessed), urban or rural location, and the COVID period) were involved in significant interactions. Bystander defibrillation was in general less likely in urban settings and at home locations. Whilst women were less likely to receive bystander defibrillation overall, in witnessed OHCAs, occurring outside the home, in urban areas and outside of the COVID-19 period women were more likely, to receive bystander defibrillation. Conclusions: Defibrillation by bystanders has increased incrementally over time in Ireland. Interventions to address sex and age-based disparities, alongside interventions to increase bystander defibrillation at night, in urban settings and at home locations are required.

Health systems developments and predictors of bystander CPR in Ireland.

Aims: To explore predictors of bystander CPR (i.e. any CPR performed prior to EMS arrival) in Ireland over the period 2012-2020. To examine the relationship between bystander CPR and key health system developments during this period. Methods: National level out-of-hospital cardiac arrest (OHCA) registry data relating to unwitnessed, and bystander witnessed OHCA were interrogated. Logistic regression models were built, then refined by fitting predictors, performing stepwise variable selection and by adding pairwise interactions that improved fit. Missing data sensitivity analyses were conducted using multiple imputation. Results: The data included 18,177 OHCA resuscitation attempts of whom 77% had bystander CPR. The final model included ten variables. Four variables (aetiology, incident location, time of day, and who witnessed collapse) were involved in interactions. The COVID-19 period was associated with reduced adjusted odds of bystander CPR (OR 0.77, 95% CI 0.65, 0.92), as were increasing age in years (OR 0.992, 95% CI 0.989, 0.994) and urban location (OR 0.52, 95% CI 0.47, 0.57). Increasing year over time (OR 1.23, 95% CI 1.16, 1.29), and an increased call response interval in minutes (OR 1.017, 95% CI 1.012, 1.022) were associated with increased adjusted odds of bystander CPR. Conclusions: Bystander CPR increased over the study period, and it is likely that health system developments contributed to the yearly increases observed. However, COVID-19 appeared to disrupt this positive trend. Urban OHCA location was associated with markedly decreased odds of bystander CPR compared to rural location. Given its importance bystander CPR in urban areas should be an immediate target for intervention.

Resuscitation for out-of-hospital cardiac arrest in Ireland 2012-2020: Modelling national temporal developments and survival predictors.

Aim: To explore potential predictors of national out-of-hospital cardiac arrest (OHCA) survival, including health system developments and the COVID pandemic in Ireland. Methods: National level OHCA registry data from 2012 through to 2020, relating to unwitnessed, and bystander witnessed OHCA were interrogated. Logistic regression models were built by including predictors through stepwise variable selection and enhancing the models by adding pairwise interactions that improved fit. Missing data sensitivity analyses were conducted using multiple imputation. Results: The data included 18,177 cases. The final model included seventeen variables. Of these nine variables were involved in pairwise interactions. The COVID-19 period was associated with reduced survival (OR 0.61, 95%CI 0.43, 0.87), as were increasing age in years (OR 0.96, 95% CI 0.96, 0.97) and call response interval in minutes (OR 0.97, 95% CI 0.96, 0.99). Amiodarone administration (OR 3.91, 95% CI 2.80, 5.48), urban location (OR 1.40, 95% CI 1.12, 1.77), and chronological year over time (OR 1.14, 95% CI 1.08, 1.20) were associated with increased survival. Conclusions: National survival from OHCA has significantly increased incrementally over time in Ireland. The COVID-19 pandemic was associated with decreased survival even after accounting for potential disruption to key elements of bystander and EMS care. Further research is needed to understand and address the discrepancy between urban and rural OHCA survival. Information concerning pre-event patient health status and inpatient care process may yield important additional insights in future.

Top 5 barriers in cardiac arrest research as perceived by international early career researchers - A consensus study.

Aim of the study: Cardiac arrest research has not received as much scientific attention as research on other topics. Here, we aimed to identify cardiac arrest research barriers from the perspective of an international group of early career researchers. Methods: Attendees of the 2022 international masterclass on cardiac arrest registry research accompanied the Global Out-of-Hospital Cardiac Arrest Registry collaborative meeting in Utstein, Norway, and used an adapted hybrid nominal group technique to obtain a diverse and comprehensive perspective. Barriers were identified using a web-based questionnaire and discussed and ranked during an in-person follow-up meeting. After each response was discussed and clarified, barriers were categorized and ranked over two rounds. Each participant scored these from 1 (least significant) to 5 (most significant). Results: Nine participants generated 36 responses, forming seven overall categories of cardiac arrest research barriers. "Allocated research time" was ranked first in both rounds. "Scientific environment", including appropriate mentorship and support systems, ranked second in the final ranking. "Resources", including funding and infrastructure, ranked third. "Access to and availability of cardiac arrest research data" was the fourth-ranked barrier. This included data from the cardiac arrest registries, medical devices, and clinical studies. Finally, "uniqueness" was the fifth-ranked barrier. This included ethical issues, patient recruitment challenges, and unique characteristics of cardiac arrest. Conclusion: By identifying cardiac arrest research barriers and suggesting solutions, this study may act as a tool for stakeholders to focus on helping early career researchers overcome these barriers, thus paving the road for future research.