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Pressure reactivity index (PRx) and brain tissue oxygen (PbtO2) are associated with outcome in traumatic brain injury (TBI). This study explores the relationship between PRx and PbtO2 in adult moderate/severe TBI. Using the Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) high resolution intensive care unit (ICU) sub-study cohort, we evaluated those patients with archived high-frequency digital intraparenchymal intracranial pressure (ICP) and PbtO2 monitoring data of, a minimum of 6 h in duration, and the presence of a 6 month Glasgow Outcome Scale –Extended (GOSE) score. Digital physiological signals were processed for ICP, PbtO2, and PRx, with the % time above/below defined thresholds determined. The duration of ICP, PbtO2, and PRx derangements was characterized. Associations with dichotomized 6-month GOSE (alive/dead, and favorable/unfavorable outcome; ≤ 4 = unfavorable), were assessed. A total of 43 patients were included. Severely impaired cerebrovascular reactivity was seen during elevated ICP and low PbtO2 episodes. However, most of the acute ICU physiological derangements were impaired cerebrovascular reactivity, not ICP elevations or low PbtO2 episodes. Low PbtO2 without PRx impairment was rarely seen. % time spent above PRx threshold was associated with mortality at 6 months for thresholds of 0 (area under the curve [AUC] 0.734, p = 0.003), > +0.25 (AUC 0.747, p = 0.002) and > +0.35 (AUC 0.745, p = 0.002). Similar relationships were not seen for % time with ICP >20 mm Hg, and PbtO2 < 20 mm Hg in this cohort. Extreme impairment in cerebrovascular reactivity is seen during concurrent episodes of elevated ICP and low PbtO2. However, the majority of the deranged cerebral physiology seen during the acute ICU phase is impairment in cerebrovascular reactivity, with most impairment occurring in the presence of normal PbtO2 levels. Measures of cerebrovascular reactivity appear to display the most consistent associations with global outcome in TBI, compared with ICP and PbtO2.

Current accepted cerebrovascular reactivity indices suffer from the need of high frequency data capture and export for post-acquisition processing. The role for minute-by-minute data in cerebrovascular reactivity monitoring remains uncertain. The goal was to explore the statistical time-series relationships between intra-cranial pressure (ICP), mean arterial pressure (MAP) and pressure reactivity index (PRx) using both 10-s and minute data update frequency in TBI. Prospective data from 31 patients from 3 centers with moderate/severe TBI and high-frequency archived physiology were reviewed. Both 10-s by 10-s and minute-by-minute mean values were derived for ICP and MAP for each patient. Similarly, PRx was derived using 30 consecutive 10-s data points, updated every minute. While long-PRx (L-PRx) was derived via similar methodology using minute-by-minute data, with L-PRx derived using various window lengths (5, 10, 20, 30, 40, and 60 min; denoted L-PRx_5, etc.). Time-series autoregressive integrative moving average (ARIMA) and vector autoregressive integrative moving average (VARIMA) models were created to analyze the relationship of these parameters over time. ARIMA modelling, Granger causality testing and VARIMA impulse response function (IRF) plotting demonstrated that similar information is carried in minute mean ICP and MAP data, compared to 10-s mean slow-wave ICP and MAP data. Shorter window L-PRx variants, such as L-PRx_5, appear to have a similar ARIMA structure, have a linear association with PRx and display moderate-to-strong correlations (r ~ 0.700, p < 0.0001 for each patient). Thus, these particular L-PRx variants appear closest in nature to standard PRx. ICP and MAP derived via 10-s or minute based averaging display similar statistical time-series structure and co-variance patterns. PRx and L-PRx based on shorter windows also behave similarly over time. These results imply certain L-PRx variants may carry similar information to PRx in TBI.

Background Traumatic brain injury (TBI) can significantly disrupt autonomic nervous system (ANS) regulation, increasing the risk for secondary complications, hemodynamic instability, and adverse outcome. This retrospective study evaluated windowed time-lagged cross-correlation (WTLCC) matrices for describing cerebral hemodynamics–ANS interactions to predict outcome, enabling identifying high-risk patients who may benefit from enhanced monitoring to prevent complications. Methods The first experiment aimed to predict short-term outcome using WTLCC-based convolution neural network models on the Wroclaw University Hospital (WUH) database (P training  = 31 with 1,079 matrices, P val  = 16 with 573 matrices). The second experiment predicted long-term outcome, training on the CENTER-TBI database (P training  = 100 with 17,062 matrices) and validating on WUH (P val  = 47 with 6,220 matrices). Cerebral hemodynamics was characterized using intracranial pressure (ICP), cerebral perfusion pressure (CPP), pressure reactivity index (PRx), while ANS metrics included low-to-high-frequency heart rate variability (LF/HF) and baroreflex sensitivity (BRS) over 72 h. Short-term outcome at WUH was assessed using the Glasgow Outcome Scale (GOS) at discharge. Long-term outcome was evaluated at 3 months at WUH and 6 months at CENTER-TBI using GOS and GOS-Extended, respectively. The XGBoost model was used to compare performance of WTLCC-based model and averaged neuromonitoring parameters, adjusted for age, Glasgow Coma Scale, major extracranial injury, and pupil reactivity in outcome prediction. Results For short-term outcome prediction, the best-performing WTLCC-based model used ICP-LF/HF matrices. It had an area under the curve (AUC) of 0.80, vs. 0.71 for averages of ANS and cerebral hemodynamics metrics, adjusted for clinical metadata. For long-term outcome prediction, the best-score WTLCC-based model used ICP-LF/HF matrices. It had an AUC of 0.63, vs. 0.66 for adjusted neuromonitoring parameters. Conclusions Among all neuromonitoring parameters, ICP and LF/HF signals were the most effective in generating the WTLCC matrices. WTLCC-based model outperformed adjusted neuromonitoring parameters in short-term but had moderate utility in long-term outcome prediction.

Background A previous retrospective single-centre study suggested that the percentage of time spent with cerebral perfusion pressure (CPP) below the individual lower limit of reactivity (LLR) is associated with mortality in traumatic brain injury (TBI) patients. We aim to validate this in a large multicentre cohort. Methods Recordings from 171 TBI patients from the high-resolution cohort of the CENTER-TBI study were processed with ICM+ software. We derived LLR as a time trend of CPP at a level for which the pressure reactivity index (PRx) indicates impaired cerebrovascular reactivity with low CPP. The relationship with mortality was assessed with Mann-U test (first 7-day period), Kruskal–Wallis (daily analysis for 7 days), univariate and multivariate logistic regression models. AUCs (CI 95%) were calculated and compared using DeLong’s test. Results Average LLR over the first 7 days was above 60 mmHg in 48% of patients. %time with CPP < LLR could predict mortality (AUC 0.73, p  =  < 0.001). This association becomes significant starting from the third day post injury. The relationship was maintained when correcting for IMPACT covariates or for high ICP. Conclusions Using a multicentre cohort, we confirmed that CPP below LLR was associated with mortality during the first seven days post injury.

Cerebral autoregulation, as measured using the pressure reactivity index (PRx), has been related to global patient outcome in adult patients with traumatic brain injury (TBI). To date, this has been documented without accounting for standard baseline admission characteristics and intracranial pressure (ICP). We evaluated this association, adjusting for baseline admission characteristics and ICP, in a multi-center, prospective cohort. We derived PRx as the correlation between ICP and mean arterial pressure in prospectively collected multi-center data from the High-Resolution Intensive Care Unit (ICU) cohort of the Collaborative European NeuroTrauma Effectiveness Research in TBI (CENTER-TBI) study. Multi-variable logistic regression models were analyzed to assess the association between global outcome (measured as either mortality or dichotomized Glasgow Outcome Score–Extended [GOSE]) and a range of covariates (IMPACT [International Mission for Prognosis and Analysis of Clinical Trials] Core and computed tomography [CT] variables, ICP, and PRx). Performance of these models in outcome association was compared using area under the receiver operating curve (AUC) and Nagelkerke's pseudo-R2. One hundred ninety-three patients had a complete data set for analysis. The addition of percent time above threshold for PRx improved AUC and displayed statistically significant increases in Nagelkerke's pseudo-R2 over the IMPACT Core and IMPACT Core + CT models for mortality. The addition of PRx monitoring to IMPACT Core ± CT + ICP models accounted for additional variance in mortality, when compared to models with IMPACT Core ± CT + ICP alone. The addition of cerebrovascular reactivity monitoring, through PRx, provides a statistically significant increase in association with mortality at 6 months. Our data suggest that cerebrovascular reactivity monitoring may provide complementary information regarding outcomes in TBI.

It has been postulated previously that individualized cerebral perfusion pressure (CPP) targets can be derived from cerebrovascular reactivity indices. Differences between real CPP and target CPP (named generically optimal CPP) has been linked to global outcome in adult traumatic brain injury (TBI). Different vascular reactivity indices can be utilized in the determination. The goal of this study is to evaluate CPPopt parameters, derived from three intracranial pressure (ICP)–derived cerebrovascular reactivity indices, and determine which one is superior for 6- to 12-month outcome prediction. Using the prospectively collected data from the Collaborative European NeuroTrauma Effectiveness Research in TBI (CENTER-TBI) study, the following indices of cerebrovascular reactivity were derived: pressure reactivity index (PRx; correlation between ICP and mean arterial pressure [MAP]), pulse amplitude index (PAx; correlation between pulse amplitude of ICP [AMP] and MAP), and RAC (correlation between AMP and CPP). CPPopt was derived using each index. Univariate logistic regression models were created to assess the association between CPPopt with global dichotomized outcome at 6 to 12 months, as assessed by Glasgow Outcome Score-Extended. Models were compared via area under the receiver operating curve (AUC) and Delong's Test. A total of 204 patients had available data. CPPopt derived from PRx, PAx, and RAC performed variably in their association with outcomes. PRx- and RAC-based CPPopt performed similarly, with RAC parameters trending towards highest AUC values. PAx-based CPPopt parameters failed to reach significant associations with dichotomized outcomes at 6 to 12 months. CPPopt parameters derived from PRx and RAC appear similar in their overall ability for 6- to 12-month outcome prediction in moderate/severe adult TBI.

Background Morphological analysis of intracranial pressure (ICP) pulse waveforms provides indirect information on cerebrospinal compliance, which might be reduced by space-occupying lesions but also by intracranial hypertension and aging. This study investigates the impact of age and mean ICP on the shape and amplitude of ICP pulse waveform in traumatic brain injury (TBI). Additionally, it explores the association between morphological parameters and mortality after TBI. Methods ICP recordings from 183 TBI patients (median age: 50 (30, 61) years) from the CENTER-TBI database were retrospectively analyzed. ICP morphology was assessed using the artificial intelligence-based pulse shape index (PSI) and peak-to-peak amplitude of ICP pulse waveform (AmpICP). The impact of mean ICP, age, and their interaction on PSI and AmpICP were estimated using factorial ANOVA. To account for influence of disturbance in the intracranial volume on AmpICP and PSI, a multiple regression analysis was performed using age, mean ICP, and the Rotterdam CT score as explanatory variables. The associations of AmpICP and PSI with six-month mortality were assessed using the area under the ROC curve (AUC). Results Age had a predominant influence on PSI ( p  < 0.01), accounting for 33.1% of its variance, while mean ICP explained 6.6% ( p  < 0.01). Conversely, mean ICP primarily affected AmpICP ( p  < 0.01), explaining 22.8% of its variance, with age contributing 8.0% ( p  < 0.01). A combined effect of age and mean ICP on AmpICP ( p  = 0.01) explained 11.7% of its variance but did not influence PSI. After accounting for Rotterdam CT score, the results remained consistent, indicating that advanced age has the strongest impact on PSI (β = 0.342, p  < 0.01) while elevated mean ICP has dominant influence on AmpICP (β = 0.522, p  < 0.01). Both AmpICP and PSI were moderately associated with mortality (AUC: 0.76 and 0.71, respectively). Conclusions AmpICP and PSI capture distinct aspects of cerebrospinal compliance. PSI appears to reflect age-related stiffening of the cerebrovascular system, while AmpICP, influenced by mean ICP, indicates acute volume compensatory changes. Combined, they provide a more comprehensive assessment of cerebrospinal volume–pressure compensation. Both morphological metrics are associated with mortality after TBI. As cerebrospinal compliance declines with age, older TBI patients become more susceptible to uncontrolled rises in ICP, which can worsen their outcome.

PurposeCPPopt denotes a Cerebral Perfusion Pressure (CPP) value at which the Pressure-Reactivity index, reflecting the global state of Cerebral Autoregulation, is best preserved. CPPopt has been investigated as a potential dynamically individualised CPP target in traumatic brain injury patients admitted in intensive care unit. The prospective bedside use of the concept requires ensured safety and reliability of the CPP recommended targets based on the automatically-generated CPPopt. We aimed to: Increase stability and reliability of the CPPopt automated algorithm by fine-tuning; perform outcome validation of the adjusted algorithm in a multi-centre TBI cohort.MethodsICM + software was used to derive CPPopt and fine-tune the algorithm. Parameters for improvement of the algorithm were selected based on qualitative and quantitative assessment of stability and reliability metrics. Patients enrolled in the Collaborative European Neuro Trauma Effectiveness Research in TBI (CENTER-TBI) high-resolution cohort were included for retrospective validation. Yield and stability of the new algorithm were compared to the previous algorithm using Mann–U test. Area under the curves for mortality prediction at 6 months were compared with the DeLong Test.ResultsCPPopt showed higher stability (p < 0.0001), but lower yield compared to the previous algorithm [80.5% (70—87.5) vs 85% (75.7—91.2), p < 0.001]. Deviation of CPPopt could predict mortality with an AUC of [AUC = 0.69 (95% CI 0.59–0.78), p < 0.001] and was comparable with the previous algorithm.ConclusionThe CPPopt calculation algorithm was fine-tuned and adapted for prospective use with acceptable lower yield, improved stability and maintained prognostic power.

Background Midline shift and mass lesions may occur with traumatic brain injury (TBI) and are associated with higher mortality and morbidity. The shape of intracranial pressure (ICP) pulse waveform reflects the state of cerebrospinal pressure–volume compensation which may be disturbed by brain injury. We aimed to investigate the link between ICP pulse shape and pathological computed tomography (CT) features. Methods ICP recordings and CT scans from 130 TBI patients from the CENTER-TBI high-resolution sub-study were analyzed retrospectively. Midline shift, lesion volume, Marshall and Rotterdam scores were assessed in the first CT scan after admission and compared with indices derived from the first 24 h of ICP recording: mean ICP, pulse amplitude of ICP (AmpICP) and pulse shape index (PSI). A neural network model was applied to automatically group ICP pulses into four classes ranging from 1 (normal) to 4 (pathological), with PSI calculated as the weighted sum of class numbers. The relationship between each metric and CT measures was assessed using Mann–Whitney U test (groups with midline shift > 5 mm or lesions > 25 cm 3 present/absent) and the Spearman correlation coefficient. Performance of ICP-derived metrics in identifying patients with pathological CT findings was assessed using the area under the receiver operating characteristic curve (AUC). Results PSI was significantly higher in patients with mass lesions (with lesions: 2.4 [1.9–3.1] vs. 1.8 [1.1–2.3] in those without; p  << 0.001) and those with midline shift (2.5 [1.9–3.4] vs. 1.8 [1.2–2.4]; p  < 0.001), whereas mean ICP and AmpICP were comparable. PSI was significantly correlated with the extent of midline shift, total lesion volume and the Marshall and Rotterdam scores. PSI showed AUCs > 0.7 in classification of patients as presenting pathological CT features compared to AUCs ≤ 0.6 for mean ICP and AmpICP. Conclusions ICP pulse shape reflects the reduction in cerebrospinal compensatory reserve related to space-occupying lesions despite comparable mean ICP and AmpICP levels. Future validation of PSI is necessary to explore its association with volume imbalance in the intracranial space and a potential complementary role to the existing monitoring strategies.

Decompressive craniectomy (DC) in traumatic brain injury (TBI) has been suggested to influence cerebrovascular reactivity. We aimed to determine if the statistical properties of vascular reactivity metrics and slow-wave relationships were impacted after DC, as such information would allow us to comment on whether vascular reactivity monitoring remains reliable after craniectomy. Using the CENTER-TBI High Resolution Intensive Care Unit (ICU) Sub-Study cohort, we selected those secondary DC patients with high-frequency physiological data for both at least 24 h pre-DC, and more than 48 h post-DC. Data for all physiology measures were separated into the 24 h pre-DC, the first 48 h post-DC, and beyond 48 h post-DC. We produced slow-wave data sheets for intracranial pressure (ICP) and mean arterial pressure (MAP) per patient. We also derived a Pressure Reactivity Index (PRx) as a continuous cerebrovascular reactivity metric updated every minute. The time-series behavior of the PRx was modeled for each time period per patient. Finally, the relationship between ICP and MAP during these three time periods was assessed using time-series vector autoregressive integrative moving average (VARIMA) models, impulse response function (IRF) plots, and Granger causality testing. Ten patients were included in this study. Mean PRx and proportion of time above PRx thresholds were not affected by craniectomy. Similarly, PRx time-series structure was not affected by DC, when assessed in each individual patient. This was confirmed with Granger causality testing, and VARIMA IRF plotting for the MAP/ICP slow-wave relationship. PRx metrics and statistical time-series behavior appear not to be substantially influenced by DC. Similarly, there is little change in the relationship between slow waves of ICP and MAP before and after DC. This may suggest that cerebrovascular reactivity monitoring in the setting of DC may still provide valuable information regarding autoregulation.