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Prognostic Value of Ventricular Fibrillation Spectral Analysis in Sudden Cardiac Death

Hospital San Carlos, Madrid · 2016
ClinicalTrials.gov · Datasets · License: Public Domain · 2016
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resuscitationsudden-cardiac-deathventricular-fibrillation
Ventricular fibrillation (VF)-related sudden cardiac death (SCD) is a leading cause of mortality. Patients may survive with neurological damage despite state-of-the-art treatment. Current biological and imaging parameters show significant limitations on early predicting cerebral performance at hospital admission. A spectral-based model was recently suggested to correlate time-dependent VF spectral changes with acute cerebral injury in comatose survivors after cardiac arrest, which opens the possibility to implement early prognostic tools in clinical practice. The AWAKE trial is an investigator-initiated, multicenter, observational trial aiming to validate a spectral-based model to early predict cerebral performance and survival in resuscitated comatose survivors admitted to specialized intensive care units. The primary clinical outcome is favorable neurological performance (FNP) during hospitalization. Patients will be categorized into 4 subsets of NP according to the risk score obtained from the predictive model. The secondary clinical outcomes are survival to hospital discharge, and FNP and survival after 6 months of follow-up. Model-derived categorization will be compared with clinical outcomes to assess model sensitivity, specificity and accuracy. Eligible patients will be included prospectively and retrospectively, using an electronic Case Report Form to enter data from medical records and in-person interviews. Patients will be divided into: study group (predictive data required) including comatose (Glasgow Coma Scale -GCS- ≤8) survivors undergoing temperature control after return of spontaneous circulation (RoSC), and control group including patients who regain consciousness (GCS=15) after RoSC. VF tracings prior to the first DC shock will be digitized and analyzed to derive spectral data and risk scores.
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