Physiological parameters, such as intracranial pressure (ICP), are regulated by interconnected feedback loops, resulting in a complex time course. According to the decomplexification theory, disease is characterised by a loss of feedback loops resulting in a reduced complexity of the time course of physiological parameters. We hypothesized that complexity of the ICP time series is decreased during periods of intracranial hypertension (IHT) following adult traumatic brain injury. In an observational retrospective cohort study, ICP was continuously monitored using intraparenchymally implanted probes and stored using ICM + -software. Periods of IHT (ICP > 25 mmHg for at least 1,024 s), were compared with preceding periods of intracranial normotension (ICP < 20 mmHg) and analysed at 1 s-intervals. ICP data (length = 1,024 s) were normalised (mean = 0, SD = 1) and complexity was estimated using the scaling exponent α (as derived from detrended fluctuation analysis), sample entropy (SampEn, m = 1, r = 0.2 × SD) and multiscale entropy. 344 episodes were analysed in 22 patients. During IHT (ICP = 31.7 ± 7.8 mmHg, mean ± SD), α was significantly elevated (α = 1.02 ± 0.22, p < 0.001) and SampEn significantly reduced (SampEn = 1.45 ± 0.46, p = 0.004) as compared to before IHT (ICP = 15.7 ± 3.2 mmHg, α = 0.81 ± 0.14, SampEn = 1.81 ± 0.24). In addition, MSE revealed a significantly (p < 0.05) decreased entropy at scaling factors ranging from 1 to 10. Both the increase in α as well as the decrease in SampEn and MSE indicate a loss of ICP complexity. Therefore following traumatic brain injury, periods of IHT seem to be characterised by a decreased complexity of the ICP waveform.