Method of predicting or prognosticating neurological performance and survival in patients who have suffered a cardiac arrest due to ventricular fibrillation (VF)
Developed by: Instituto de Investigación Sanitaria Hospital La Paz
Description and special features
Method with high sensitivity, specificity and c‐Statistic values for the early prediction ‐based on a validated and reliable risk‐score (RS)‐ of neurological performance (FNP) and survival (S) in patients undergoing therapeutic hypothermia after cardiac arrest due to ventricular fibrillation (VF) and comatose status on admission.
The method consists of a multiple logistic regression with four predictors and combines: i) information of ventricular fibrillation (VF) spectral characteristics registered at the time of the first reported Direct Current Shock (DCShock), and ii) ambulatory patient‐specific clinical information to provide a reliable RS of the expected outcome, cerebral performance and survival, at hospital discharge.
The key scientific findings that confer an innovative practical approach to this invention are that the research team 1) have shown the cut‐off value of the Dominant Frequency (DF) before the first DCShock, as a strong independent predictor for favorable neurological performance (FNP); 2) have derived two further significant spectral variables crucial for predicting not only neurological performance but also survival: the high‐to‐low power spectral density ratio (HL‐PSDR), and the high‐to‐low peak ratio (HL‐pKR), (3) have also discovered that the number of shocks delivered before ROSC (“Return of spontaneous circulation”) is also important for the early prognosis of neurological performance.
Up to date, the reliability of early prognosis in comatose survivors undergoing therapeutic hypothermia after cardiac arrest due to VF has been very limited, which has severely impaired the ability of physicians to provide accurate information to patients’ relatives and to optimize the use of intensive‐resource care.
Standardization of mild hypothermia delays neurological evaluation and prognostication due to sedation as well as higher rates of misleading biomarker values within the first 24‐48 h. Moreover, the large variability of threshold biomarker values used to predict poor outcome and different measurement techniques makes it necessary to exert caution and question the prognostic accuracy provided by biochemical markers. And on the other hand, clinical variables alone are inconsistent in predicting both cerebral performance and survival.
The prediction model proposed herein enables an early reliable prognostication of survival and/or neurological performance after hospital discharge and/or for at least 6 months after suffering cardiac arrest, in patients which have suffered a cardiac arrest, and optionally comatose status, due to VF.
Estado de protección
European patent EP14382456.3, applied for in November 2014.
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