Details

Autor(en) / Beteiligte

• Palacios-Rubio, Julián
• Marina-Breysse, Manuel
• Quintanilla, Jorge G
• Gil-Perdomo, José Miguel
• Juárez-Fernández, Miriam
• Garcia-Gonzalez, Inés
• Rial-Bastón, Verónica
• Corcobado, María Carmen
• Espinosa, María Carmen
• Ruiz, Francisco
• Gómez-Mascaraque Pérez, Francisco
• Bringas-Bollada, María
• Lillo-Castellano, José María
• Pérez-Castellano, Nicasio
• Martínez-Sellés, Manuel
• López de Sá, Esteban
• Martín-Benítez, Juan Carlos
• Perez-Villacastín, Julián
• Filgueiras-Rama, David

Titel

Early prognostic value of an Algorithm based on spectral Variables of Ventricular fibrillAtion from the EKG of patients with suddEn cardiac death: A multicentre observational study (AWAKE)

Ist Teil von

• Archivos de cardiología de México, 2018-12, Vol.88 (5), p.460-467

Ort / Verlag

Mexico: Permanyer Publications

Erscheinungsjahr

2018

Link zum Volltext

Quelle

EZB Free E-Journals

Beschreibungen/Notizen

• Ventricular fibrillation (VF)-related sudden cardiac death (SCD) is a leading cause of mortality and morbidity. Current biological and imaging parameters show significant limitations on predicting cerebral performance at hospital admission. The AWAKE study (NCT03248557) is a multicentre observational study to validate a model based on spectral ECG analysis to early predict cerebral performance and survival in resuscitated comatose survivors. Data from VF ECG tracings of patients resuscitated from SCD will be collected using an electronic Case Report Form. Patients can be either comatose (Glasgow Coma Scale - GCS - ≤8) survivors undergoing temperature control after return of spontaneous circulation (RoSC), or those who regain consciousness (GCS=15) after RoSC; all admitted to Intensive Cardiac Care Units in 4 major university hospitals. VF tracings prior to the first direct current shock will be digitized and analyzed to derive spectral data and feed a predictive model to estimate favorable neurological performance (FNP). The results of the model will be compared to the actual prognosis. The primary clinical outcome is FNP during hospitalization. Patients will be categorized into 4 subsets of neurological prognosis 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. The model-derived categorisation will be also compared with clinical variables to assess model sensitivity, specificity, and accuracy. A model based on spectral analysis of VF tracings is a promising tool to obtain early prognostic data after SCD.