TY - JOUR
T1 - Resuscitation for out-of-hospital cardiac arrest in Ireland 2012–2020
T2 - Modelling national temporal developments and survival predictors
AU - Out-of-Hospital Cardiac Arrest Registry Steering Group
AU - Barry, Tomás
AU - Kasemiire, Alice
AU - Quinn, Martin
AU - Deasy, Conor
AU - Bury, Gerard
AU - Masterson, Siobhan
AU - Segurado, Ricardo
AU - Murphy, Andrew W.
N1 - Publisher Copyright:
© 2024 The Author(s)
PY - 2024/6
Y1 - 2024/6
N2 - 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.
AB - 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.
KW - Cardiopulmonary Resuscitation
KW - Out-of-Hospital Cardiac Arrest
KW - Public Health
KW - Registry Data
KW - Resuscitation
KW - Statistical Models
UR - https://www.scopus.com/pages/publications/85190730806
U2 - 10.1016/j.resplu.2024.100641
DO - 10.1016/j.resplu.2024.100641
M3 - Article
AN - SCOPUS:85190730806
SN - 2666-5204
VL - 18
JO - Resuscitation Plus
JF - Resuscitation Plus
M1 - 100641
ER -