Out-of-hospital cardiac arrest (OHCA) is a leading cause of death worldwide. Despite constantly improving resuscitation techniques, the chances of survival remain limited. During cardiopulmonary resuscitation (CPR), a closure of the airway may occur, impeding ventilation. This phenomenon also complicates the interpretation of the end-tidal CO2 (ETCO2) in the capnogram. The extent to which airway closure occurs is quantified by the Airway Opening Index (AOI). This can be calculated from the capnogram and is seen as a measure of the quality of CPR applied as well as a possible indicator to predict the outcome of CPR. In this study, we analyse capnogram data from approximately 150 cases, collected during interventions for OHCA and logged in the Lazarus database (UZ Gent and AZORG) to answer three research questions below: 1. What is the prevalence of AOI during CPR? 2. Is there a correlation between AOI and return of spontaneous circulation (ROSC)? 3. Does the application of positive end-expiratory pressure (PEEP) affect the AOI and ROSC? A mathematical model for calculating AOI, based on a method from previous work by Bandhari et al. \[1\] will be developed. Using this model, the AOI will be calculated from the individual capnograms for all cases in the Lazarus database. In addition, a multivariable regression model will be used to analyse whether AOI can be used to predict ROSC. Corrections will be made for relevant confounders such as age, gender, witnessed arrest and rhythm pattern. Finally, it is investigated whether PEEP has a positive influence on AOI. This study aims to contribute to better insights into airway dynamics during CPR and the optimization of ventilation in OHCA.
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ROSC
Timeframe: Initial resuscitation (first day)