Multi-center observational study of the relationship of ventilation and outcomes from cardiac arrest using existing data

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Project Summary/Abstract Introduction: Out-of-hospital cardiac arrest (OHCA) is a major public health problem that affects over 350,000 adults in the United States each year. Survival from OHCA remains unacceptably low despite promising advances over the last decade. During cardiac arrest, all circulation stops. Quickly restoring circulation and oxygenation to vital organs such as the heart and brain are important goals of out of hospital cardiac arrest (OHCA) resuscitation. Cardiopulmonary resuscitation (CPR) combines chest compressions with lung inflation to restore perfusion and oxygenation to the body. During the past decade, research focused on measuring chest compressions during CPR has lead to improvements in performance of chest compressions and increased survival rates. However, ventilation has long been a “neglected parameter” in CPR research, in part, because measuring ventilation during OHCA and CPR is difficult. To address this problem, we developed a novel method for measuring ventilation during CPR using thoracic bioimpedance (electrical resistance), which can be monitored through defibrillator pads placed during CPR. Using data from the Resuscitation Outcomes Consortium Dallas-Fort Worth site, we showed that good quality ventilation is associated with improved outcomes such as survival to hospital discharge. However, a multi-center study is necessary to establish the generalizability of those findings. Objectives: To measure ventilation metrics and to determine the association of ventilation during standard CPR with outcomes such as survival to hospital discharge and survival with favorable neurological outcome in patients suffering OHCA. Methods: The study will use data from one of the largest, comprehensive OHCA multi-center trial in the world. The ROC Continuous Chest Compression (CCC) Trial database includes CPR resuscitation metrics, patient outcomes, and access to defibrillator bioimpedance recordings, a rare combination for a cardiac arrest database. A validated method to identify acceptable bioimpedance ventilation waveforms has been programmed into an automated computer algorithm, which will extract ventilation data from defibrillator recordings from approximately 4,000 patients from six ROC sites that participated in the CCC Trial. Ventilation data will be matched with clinical data for each case. Specific Aims: 1) To determine ventilation frequency, incidence, tidal volume, and inspiratory and expiratory times from the 30:2 CPR defibrillator files of six participating ROC regional clinical sites. 2) To determine if ventilation frequency, incidence, and fraction during ventilation with a bag-mask device is associated with survival outcomes in the 30:2 CPR group. 3) Compare outcomes of the 30:2 vs. CCC groups of the CCC Trial. Significance: The results may provide evidence for a paradigm shift and impact CPR training, guidelines, and the future delivery of resuscitation care to hundreds of thousands of people annually in the United States.