Disease states are associated with a breakdown in healthy interactions and are often characterized by reduced signal complexity. We applied approximate entropy (ApEn) analysis to investigate the correlation between the complexity of heart rate (ApEn-HR), mean arterial pressure (ApEn-MAP), intracranial pressure (ApEn-ICP), and a combined ApEn-product (product of the three individual ApEns) and outcome after traumatic brain injury. In 174 severe traumatic brain injured patients, we found significant differences across groups classified by the Glasgow Outcome Score in ApEn-HR (p = 0.007), ApEn-MAP (p = 0.02), ApEn-ICP (p = 0.01), ApEn-product (p = 0.001), and pressure reactivity index (PRx) (p = 0.004) in the first 6 h. This relationship strengthened in a 24 h and 72 h analysis (ApEn-MAP continued to correlate with death but was not correlated with favorable outcome). Outcome was dichotomized as survival versus death, and favorable versus unfavorable; the ApEn-product achieved the strongest statistical significance at 6 h (F = 11.0; p = 0.001 and F = 10.5; p = 0.001, respectively) and was a significant independent predictor of mortality and favorable outcome (p < 0.001). Patients in the lowest quartile for ApEn-product were over four times more likely to die (39.5% vs. 9.3%, p < 0.001) than those in the highest quartile. ApEn-ICP was inversely correlated with PRx (r = -0.39, p < 0.000001) indicating unique information related to impaired cerebral autoregulation. Our results demonstrate that as early as 6 h into monitoring, complexity measures from easily attainable vital signs, such as HR and MAP, in addition to ICP, can help triage those who require more intensive neurological management at an early stage.
Keywords: ICP; approximate entropy; autoregulation; complexity; traumatic brain injury.