Improved outcome prediction in unconscious cardiac arrest survivors with sensory evoked potentials compared with clinical assessment


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Abstract

Objective:To compare the prognostic ability of sensory evoked potentials in cardiac arrest survivors with the outcome predicted by a panel of experienced emergency physicians based on detailed prehospital, clinical, and laboratory data.Design:Inception cohort study.Setting:Medical intensive care unit and department of emergency medicine at a university hospital.Patients:A total of 162 unconscious, mechanically ventilated patients who survived ≥24 hrs after resuscitation from cardiac arrest.Interventions:Recording of sensory evoked potentials and outcome prediction after review of detailed clinical and laboratory data by emergency physicians within 24 hrs after cardiac arrest.Measurements and Main Results:At 6 months, the outcome of 36 patients was classified as favorable and 126 patients were rated as poor. After review of prehospital data, emergency physicians predicted favorable vs. poor outcome with a sensitivity of 70% and a specificity of 65%. After additional assessment of data 1 hr after cardiac arrest, the sensitivity of emergency physician predictions increased to 80%, whereas the specificity decreased to 48%. Outcome prediction by emergency physicians was most accurate after obtaining detailed patient data 24 hrs after cardiac arrest (sensitivity, 81%; specificity, 58%). In 35 of 36 patients with favorable outcomes, the cortical evoked potential N70 peak was detected between 72 and 128 msec. Of 113 patients with an N70 peak latency > 130 msec or an absent N70 peak, all except one had a poor outcome. By using a cutoff of 130 msec, the N70 peak latency alone had a sensitivity of 94% and a specificity of 97%. The predictive accuracy of the N70 peak latency was significantly higher than the clinical assessment 24 hrs after cardiac arrest (91% vs. 76%,p= .0003).Conclusion:In unconscious cardiac arrest survivors, a recording of long-latency sensory evoked potentials is more accurate in predicting individual outcome than an emergency physician review of clinical data.

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