Resuscitation
-
Prehospital cardiopulmonary resuscitation is performed from scene arrival to hospital arrival. The diverse prehospital resuscitation phases can affect the quality of chest compressions. This study aimed to evaluate the dynamic changes in chest compression quality during prehospital resuscitation. ⋯ Dynamic changes in chest compression quality were observed during prehospital resuscitation phase. The no-flow fraction was the highest from 1 min before to 1 min after ambulance departure.
-
The NULL-PLEASE score (Nonshockable rhythm, Unwitnessed arrest, Long no-flow or Long low-flow period, blood pH < 7.2, Lactate > 7.0 mmol/L, End-stage renal disease on dialysis, Age ≥85 years, Still resuscitation, and Extracardiac cause) may identify patients with out-of-hospital cardiac arrest (OHCA) unlikely to survive. We aimed to validate the NULL-PLEASE score in a nationwide setting. ⋯ In a nationwide OHCA-cohort, AUCROC values for the predictive ability of NULL-PLEASE were high for all outcomes. However, some survived even with high NULL-PLEASE scores.
-
Recent evidence suggest that extracorporeal cardiopulmonary resuscitation (ECPR) may improve survival rates for nontraumatic out-of-hospital cardiac arrest (OHCA). Eligibility criteria for ECPR are often based on patient age, clinical variables, and facility capabilities. Expanding access to ECPR across the U.S. requires a better understanding of how these factors interact with transport time to ECPR centers. ⋯ Less than 2% of OHCA patients are eligible for ECPR in the U.S. GIS models can identify the impact of clinical criteria, transportation time, and hospital capabilities on ECPR eligibility to inform future implementation strategies.
-
For out-of-hospital cardiac arrest (OHCA), assignment of race/ethnicity data can be challenging. Validation of race/ethnicity in registry data with patients' self-reported race/ethnicity would provide insights regarding misclassification. ⋯ Race/ethnicity in CARES was highly concordant with self-reported race/ethnicity in Medicare, especially for non-Hispanic White and Black individuals. For patients with unknown race/ethnicity data in CARES, the vast majority were of White race.