Evaluation and Application of Ultra-Low-Resolution Pressure Reactivity Index in Moderate or Severe Traumatic Brain Injury

Background: The pressure reactivity index (PRx) has emerged as a surrogate method for the continuous bedside estimation of cerebral autoregulation and a predictor of unfavorable outcome after traumatic brain injury (TBI). However, calculation of PRx require continuous high-resolution monitoring currently limited to specialized intensive care units. The aim of this study was to evaluate a new index, the ultra-low-frequency PRx (UL-PRx) sampled at ∼0.0033 Hz at ∼5 minutes periods, and to investigate its association with outcome. Methods: Demographic data, admission Glasgow coma scale, in-hospital mortality and Glasgow outcome scale extended at 12 months were extracted from electronic records. The filtering and preparation of time series of intracranial pressure (ICP), mean arterial pressure and cerebral perfusion pressure (CPP), and calculation of the indices (UL-PRx, Δ-optimal CPP), were performed in MATLAB using an in-house algorithm. Results: A total of 164 TBI patients were included in the study; in-hospital and 12-month mortality was 29.3% and 38.4%, respectively, and 64% of patients had poor neurological outcome at 12 months. On univariate analysis, ICP, CPP, UL-PRx, and ΔCPPopt were associated with 12-month mortality. After adjusting for age, Glasgow coma scale, ICP and CPP, mean UL-PRx and UL-PRx thresholds of 0 and +0.25 remained associated with 12-month mortality. Similar findings were obtained for in-hospital mortality. For mean UL-PRx, the area under the receiver operating characteristic curves for in-hospital and 12-month mortality were 0.78 (95% confidence interval [CI]: 0.69-0.87; P<0.001) and 0.70 (95% CI: 0.61-0.79; P<0.001), respectively, and 0.65 (95% CI: 0.57-0.74; P=0.001) for 12-month neurological outcome. Conclusions: Our findings indicate that ultra-low-frequency sampling might provide sufficient resolution to derive information about the state of cerebrovascular autoregulation and prediction of 12-month outcome in TBI patients.