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• W2012119954 abstract "There is a need for robust, effective predictors of the outcome from shock for out-of-hospital cardiac arrest patients. Such technology would enable the emergency responder to provide a therapy tailored to the patient's needs. Here we report our most recent findings while dwelling intentionally on the rationale behind the decisions taken during system development. Specifically, we illustrate the need for sensible data selection, fully cross-validated results and the care necessary when evaluating system performance. We analyze 878 pre-shock ECG traces, all of at least 10 s duration from 110 patients with cardiac arrest of cardiac aetiology. The continuous wavelet transform was applied to preshock segments of ECG trace. Time-frequency markers are extracted from the transform and a linear threshold derived from a training set to provide high sensitivity prediction of successful defibrillation. These systems are then evaluated on a withheld test set. All experiments are cross-validated. When compared to popular Fourier-based techniques our wavelet transform method, COP (Cardioversion Outcome Predictor), provides a 10-20% improvement in performance with values of 66 +/- 4 specificity at 95 +/- 4 sensitivity, 61 +/- 4 specificity at 97 +/- 2 sensitivity and 56 +/- 1 specificity at 98 +/- 2 sensitivity achieved for datasets limited to 3, 6, and 9 shocks per patient, respectively. Thus, the assessment of the wavelet marker was associated with a high specificity value at or above 95% sensitivity in comparison to previously reported methods. Therefore, COP could provide an optimal index for the identification of patients for whom shocking would be futile, and for whom an alternative therapy could be considered." @default.
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• W2012119954 date "2006-01-01" @default.
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• W2012119954 title "Practical issues in the evaluation of methods for the prediction of shock outcome success in out-of-hospital cardiac arrest patients" @default.
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• W2012119954 doi "https://doi.org/10.1016/j.resuscitation.2005.06.013" @default.
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