Early WAKE-up Predictors After Out-of-Hospital Cardiac Arrest

Background: Post-resuscitation care following out-of-hospital cardiac arrest remains a critical area of research to optimize neurological recovery and cardiovascular outcomes. Recent findings from the Targeted Temperature Management (TTM) trials have led to the discontinuation of therapeutic hypothermia in Denmark, eliminating the need for deep sedation. The optimal sedation strategy in post-resuscitation care remains unknown, with sedation hypothesized to be neuroprotective controlling intracranial pressure but also known to be harmful and associated with adverse outcomes such as delirium, ventilator associated pneumonia, venous thromboembolism, prolonged intensive care unit (ICU) stay, delayed mobilization and patient prognostication. Though there is emerging interest in early weaning from sedation within post-resuscitation care, limited data exist on its feasibility, prognostic implications and cost-effectiveness. Certain neuromonitoring modalities including automated pupillometry, transcranial doppler and electroencephalography (EEG) have shown promising prognostic properties, also in predicting favorable outcomes. However, sparse literature exists on early (\<6 hours) prognostication related to length of sedation, and further knowledge in this area is needed to support clinical decision making. The Danish Out-of-Hospital Cardiac Arrest (DANOHCA) study (NCT05895838) is an on-going multicenter randomized trial enrolling 1,000 participants to early wake-up (\<6 hours) or standard (28-36 hours) length of sedation. This provides an opportunity to further understand neuroprognostication related to length of sedation in post-resuscitation care. Aim and hypothesis: This present study is designed within the context of the DANOHCA trial with the aim of identifying patient and neuromonitoring predictors of successful early and late wake-up. The hypothesis is: Specific patient variables and neuromonitoring parameters are associated with successful wake-up. Materials and Methods: WAKE-OHCA will be conducted as a two-part analysis with 1) entire DANOHCA cohort (n=1,000 participants) with ICU admission data and 2) neuromonitoring data collected within the ICU on the patient cohorts at two Danish university hospital sites (Aarhus University Hospital and Rigshospitalet) during the study inclusion period (anticipated n=250 participants, with the exception of n=100 participants for EEG measurements, as these will only be performed at Aarhus University Hospital site). DANOHCA inclusion criteria are: Out-of-hospital cardiac arrest of a presumed cardiac cause, age \> 18 years, sustained return of spontaneous circulation for more than 20 minutes, unconscious upon admission. The first part will include baseline characteristics, cardiac arrest data, and initial biochemistry. Data is collected from Danish prehospital patient journal (PPJ), electronic patient journals (EPJ, Sundhedsplatformen), Danish cardiac arrest registry and DANOHCA patient database. The second part will include the following non-invasive neuromonitoring data collected prospectively at 0-6 hours, 20-28 hours, 44-52 hours and 66-72 hours after enrolment: * Bilateral automated pupillometry * Transcranial doppler evaluating both middle cerebral arteries. * Bilateral Optic Nerve Sheath Diameter measured by ultrasound. * Continuous 4-channel EEG background activity and EEG reactivity tests. These will provide insight on early neurological status and recovery patterns, cerebral hemodynamics and intracranial pressure. Neuromonitoring data will only be collected on participants that are still comatose. Clinicians will be blinded from collected data, and it will have no impact on participants' treatment. Automated pupillometry will be done with a NeurOptics NPi-200 pupillometer (NeurOptics, Irvine, California, USA). Transcranial doppler and ONSD measurements will be conducted with a Vivid S70N (GE Healthcare, Chicago, IL, USA) and analysed using Echopac (GE Healthcare, Chicago, IL, USA). EEG measurements will be done with Mindray BeneVision N-series with an aEEG module (Shenzhen Mindray Bio-Medical Electronics Co., Nanshan, Shenzhen, China). Logistic regression analysis will be conducted to explore the association between participant and neuromonitoring variables and successful wake-up with unsuccessful wake-up as reference group. Secondary analyses will investigate how neuromonitoring variables perform in predicting patient outcomes (mortality, neurological outcome) in the early and late wake-up groups as well as how serial neuromonitoring variables are associated with successful wake-up at later stages. Significance: By identifying key predictors of early wake-up success, this project may refine patient selection, optimize individualized treatment, and enhance prognostication. Insights into neuromonitoring could improve clinical decision-making and reduce unnecessary sedation, minimizing associated complications.