Out-of-Hospital Cardiac Arrest Before, During, and After the Pandemic of COVID-19.

Background/

Objectives

This study aimed to evaluate the incidence and outcomes of emergency medical service (EMS)-treated out-of-hospital cardiac arrest (OHCA) and to determine whether predictors of outcomes differed across the pre-pandemic, pandemic, and post-pandemic periods.

Methods

A retrospective observational study was conducted over a six-year period and included 1150 patients with EMS-treated OHCA. Patients were categorized into three groups according to the study period.

Results

The incidence of EMS-treated OHCA differed significantly across the three study periods (χ2 = 15.184, p = 0.001), with the highest number of cases observed during the pandemic. The rate of return of spontaneous circulation (ROSC) also varied significantly between periods (p = 0.035). Although the highest overall mortality was observed during the pandemic period (97.5%), differences in overall mortality across the study periods did not reach statistical significance (p = 0.079). Variables independently associated with ROSC were EMS response time, initial cardiac rhythm, and the administration of adrenaline and atropine. Age and initial cardiac rhythm were independently associated with mortality. No significant interactions were observed between study period and the identified predictors of ROSC or mortality.

Conclusions

The COVID-19 pandemic was associated with a significant increase in EMS-treated OHCA incidence and poorer patient outcomes, including lower ROSC and survival rates. Although outcomes improved in the post-pandemic period, multivariable analysis demonstrated that the pandemic period itself was not independently associated with ROSC or mortality after adjustment for relevant clinical factors. Instead, outcome differences were primarily explained by established clinical predictors, including patient age, initial cardiac rhythm, EMS response time, and resuscitation-related factors. Prospective studies incorporating more detailed data on patient characteristics, the quality of resuscitation, and organizational characteristics of the healthcare system may enable more accurate outcome modeling.