New technologies and decision making in out-of-hospital cardiac arrest

Abstract

In this thesis, we performed analyses on basic life support, AED (automated external defibrillator) use by first responders (police, fire-fighters, and citizen-responders), and advanced life support by emergency medical services (EMS) in out-of-hospital cardiac arrest (OHCA). We studied the proportion of shockable initial rhythm over 10 years and showed that this proportion declined during the total study period, and remained stable when limiting the analysis to the last five years. We assessed the clinical benefit of the new AED algorithm cprINSIGHT which can analyze the heart rhythm during chest compressions. We showed that cprINSIGHT could make a shock/no-shock decision with high sensitivity (96%) and high specificity (98%) and led to a higher chest compression fraction and shorter pre-shock pauses compared to conventional AEDs. We gained more insight into patients transported without ROSC and showed that in this patient population the survival rate declined when time-on-scene before transport increased. We showed that in patients with prehospital ROSC, survivors had a significantly shorter time-to-ROSC compared to non-survivors and calculated that the time point for the decision to transport appears to be between 8 and 15 minutes after EMS arrival. We explored EMS decision-making on scene and found that known factors such as age, OHCA location, witnessed status and first rhythm only explained 36% of the variance in the decision to transport and other factors related to the patient, local circumstances, the paramedic, and the structure of the organization were identified as important additional themes contributing to the decision to transport a patient with ongoing CPR