Could heart rate variability predict outcome in patients with severe head injury? A pilot study

Despite major improvements in the resuscitation of patients with head injury, the outcome of patients with head trauma often remains poor and difficult to establish. Heart rate variability (HRV) analysis is a noninvasive tool used to measure autonomic nervous system (ANS) activity. The aim of this prospective study was to investigate whether HRV analysis might be a useful adjunct for predicting outcome in patients with severe head injury. Twenty patients with severe head trauma (Glasgow Coma Scale [GCS] or= 10) to HRV in patients characterized by a worsened neurologic state (GCS < 10). Statistical analysis used the Kruskal-Wallis test, P < .05. To assess whether HRV could predict evolution to brain death, receiver operating characteristic (ROC) curves were generated the day after trauma for Total Power, natural logarithm of high-frequency component of spectral analysis (LnHF), natural logarithm of low-frequency component of spectral analysis (LnLF), and root mean square for successive interval differences (rMSSD). Seven patients died between Day 1 and Day 5 after trauma. Six of those had progressed to brain death. In these six patients, at Day 1, Global HRV and parasympathetic tone were significantly higher. Referring to the area under the rMSSD ROC curve, HRV might provide useful information in predicting early evolution of patients with severe head trauma. During the awakening period, global HRV and the parasympathetic tone were significantly lower in the worsened neurologic state group. In conclusion, HRV could be helpful as a predictor of imminent brain death and a useful adjunct for predicting the outcome of patients with severe head injury.