Multimodal Outcome CHAracterization (MOCHA) in comatose cardiac arrest patients

The purpose of this study is to create a Yale School of Medicine Neurology patient clinical data repository that will be used for current and future research projects involving the study of post-cardiac arrest patients and the clinical characteristics and prognostic factors that effect neurologic outcome. This clinical data repository will serve researchers at Yale as well as external collaborators engaged in future observational studies related to post-cardiac arrest syndrome. The clinical data registry will gather a patient's relevant clinical data, including functional outcomes during hospitalization and at discharge (at 3 months, 6 months and 12 months follow-up visits). The clinical information obtained from patients will help researchers understand the target patient population as well as help formulate studies that can assess the progression of disease as it relates to outcome. Our ultimate goal is to come up with a predication model for prognostication in cardiac arrest, using multiple modalities that are already clinically in use, but in a more standardized fashion. Our hope is that these tools, either in isolate or in combination, will be able to more accurately predict outcome for patients initially comatose following cardiac arrest.