Evaluation of the Prognostic Value and Modifiability of Low-Frequency Pressure Reactivity Index in Patients with Traumatic Brain Injury

Evaluation of the Prognostic Value and Modifiability of Low-Frequency Pressure Reactivity Index in Patients with Traumatic Brain Injury | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Evaluation of the Prognostic Value and Modifiability of Low-Frequency Pressure Reactivity Index in Patients with Traumatic Brain Injury Ue-Cheung Ho, Nathan Wei, Lu-Ting Kuo This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7029976/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background/Objective : Cerebral autoregulation is a critical determinant of traumatic brain injury (TBI) outcomes. Low-frequency pressure reactivity index (LPRx), from routine monitoring, dynamically assesses autoregulation; impairment (elevated LPRx) is linked to poor outcomes. However, the impact of clinical interventions on LPRx and LPRx-derived optimal CPP (CPPopt) utility are unclear. This study evaluated LPRx's prognostic value and therapeutic modifiability in TBI patients, examining its dynamics related to 6-month clinical outcomes (survival, Glasgow Outcome Scale Extended [GOSE]) and common neurocritical care interventions. Methods : We conducted a retrospective analysis of 35 moderate-to-severe TBI patients undergoing neurosurgery and intensive care unit (ICU) monitoring with minute-by-minute recordings at two Taiwanese university hospitals (2022-2024). LPRx (moving Pearson correlation of 1-minute averaged arterial blood pressure/ICP) and CPPopt (nadir of LPRx-CPP curve) were calculated. Patients were stratified by 6-month survival and GOSE (favorable: GOSE 5–8; unfavorable: GOSE 1–4). LPRx relationships with outcomes, ICP, CPPopt, decompressive craniectomy, and mannitol were analyzed using non-parametric tests and generalized estimating equations (GEE). Results : Among 35 patients (26 survivors, 8 favorable outcomes), significantly higher median LPRx and a greater proportion of time with LPRx > thresholds (e.g., >0.2, p=0.013) correlated with unfavorable outcomes. Early impaired LPRx (days 1, 3, 4) was associated with unfavorable function. LPRx showed a U-shaped ICP relationship (nadir ~10 mmHg). CPPopt was derivable in only 32% of monitoring time, with no consistent LPRx relationship. Decompressive craniectomy and mannitol did not significantly alter LPRx (mannitol GEE: p=0.786). Conclusion : Impaired cerebral autoregulation (elevated LPRx) is associated with poor TBI outcomes. While CPPopt is an attractive theoretical target, its limited feasibility and inconsistent physiological correlation pose challenges to its clinical utility. LPRx offers a continuous, practical measure; however, its responsiveness to conventional therapies remains uncertain, warranting further investigation. Registration : The study design was not preregistered. Traumatic Brain Injury Pressure Reactivity Index Cerebral Autoregulation Decompressive Craniectomy Osmotic Therapy Figures Figure 1 Figure 2 Figure 3 Introduction Traumatic brain injury (TBI) remains a critical global health concern, contributing to high mortality and long-term disability rates across a wide demographic range. Contemporary management of moderate-to-severe TBI focuses on preventing secondary brain insults, such as intracranial hypertension and cerebral hypoperfusion, both of which are associated with poor neurological outcomes. Traditionally, therapeutic strategies have focused on maintaining intracranial pressure (ICP) and cerebral perfusion pressure (CPP) within fixed thresholds. 1 However, these standardized targets often overlook patient-specific variations in cerebral autoregulation. Cerebral autoregulation, the brain's ability to maintain stable blood flow despite fluctuations in perfusion pressure, is a fundamental physiological process that can be significantly disrupted by TBI. The pressure reactivity index (PRx), derived from the correlation between slow-wave changes in mean arterial pressure and ICP, serves as a continuous, dynamic surrogate marker of autoregulatory integrity. 2 Elevated PRx levels indicate impaired autoregulation and have been continuously associated with increased mortality and unfavorable long-term functional outcomes in both adult and pediatric populations. 2 – 5 Despite its established prognostic value, there is limited evidence on how clinical interventions such as pharmacological agents or surgical procedures directly influence PRx trajectories over time. Most current practices treat PRx as a monitoring tool rather than a modifiable target, leaving a gap in understanding whether individualized treatments can actively restore or stabilize the autoregulatory capacity. As emerging approaches advocate tailoring CPP targets to a patient's optimal CPP (CPPopt) derived from the lowest PRx, investigating the modifiable determinants of PRx has become increasingly relevant​. Although high-resolution PRx monitoring has demonstrated strong prognostic significance in patients with TBI, its clinical implementation requires continuous waveform recording and advanced signal-processing infrastructure, and resources are often limited to specialized neurocritical care units. As a more practical alternative, the low-frequency pressure reactivity index (LPRx), which is derived from minute-by-minute averaged arterial and intracranial pressure signals, has been proposed to estimate cerebral autoregulation using standard intensive care monitoring systems. 6 Although slightly less sensitive than its high-resolution counterpart, LPRx has demonstrated comparable associations with patient outcomes, enabling the wider adoption of autoregulation-based assessments across different care settings. 4 , 6 – 9 In this study, we utilized the LPRx as a practical and accessible surrogate for assessing cerebral autoregulation in patients with TBI. We aimed to examine LPRx dynamics in relation to clinical outcomes and treatment interventions with the goal of advancing individualized, physiology-driven approaches in neurocritical care. Methods Study Participants and Setting We conducted a retrospective analysis of 35 consecutive patients with TBI who underwent surgery at the National Taiwan University Hospital (NTUH) and its Yunlin branch between January 2022 and December 2024. Surgical procedures included decompressive craniotomy or craniectomy with or without hematoma evacuation, accompanied by ICP monitoring or external ventricular drain (EVD) placement. Prehospital and surgical care adhered to the contemporary TBI management guidelines. 1 Eligible patients were 18 years or older and had sustained a moderate-to-severe TBI requiring neurosurgical intervention. All patients were admitted to the intensive care unit (ICU) for postoperative care, during which arterial blood pressure (ABP) and ICP were continuously monitored, allowing for subsequent analysis of LPRx. Inclusion also required a signed proxy informed consent obtained from the patient's legal representative or next of kin upon admission. Patients were excluded if they had a history of neurological disorders, such as brain tumors, stroke, previous head trauma, meningitis, known substance use disorders, or a prior history of brain surgery. Patients whose injuries were deemed unsurvivable at presentation, who were pregnant at the time of admission, or who had a do-not-resuscitate order authorized by their families were also excluded. Furthermore, those without sufficient quality physiological data, defined as fewer than 24 hours of valid ICP and CPP recordings, or those lacking essential clinical information, were excluded from the analysis. All patients were admitted to the ICU for postoperative care, where ABP, ICP, oxygen saturation, and body temperature were continuously monitored. Standard ICU management includes prophylactic antibiotics, antiepileptic drugs, and early initiation of enteral nutrition. Hourly neurological assessments, including the Glasgow Coma Scale (GCS) score and evaluation of pupil size and light reflex, were performed. Specific treatment decisions were made at the discretion of the attending neurosurgeons. To explore the clinical and physiological correlates of outcomes, patients were categorized into groups based on 6-month survival (survivors vs. non-survivors) and 6-month functional outcome, as determined by the Glasgow Outcome Scale Extended (GOSE), and dichotomized into favorable outcomes (GOSE 5–8) and unfavorable outcomes (GOSE 1–4). These groupings were used for the subsequent comparative and statistical analyses. This study was approved by the National Taiwan University Hospital Research Ethics Committee (#202408094RINE) and conducted in accordance with the Declaration of Helsinki. All patients provided general consent upon admission for the use of their anonymized medical data for academic purposes. Data were extracted from electronic medical records in a de-identified format, and patient privacy was maintained throughout the study. Management of Increased Intracranial Pressure A standardized, stepwise treatment strategy was employed to control elevated ICP in accordance with contemporary neurocritical care guidelines and institutional protocols. The primary therapeutic goal was to maintain ICP 50 mmHg throughout the critical monitoring period. 1 Initial management included elevating the head of the bed to 30°, ensuring neutral neck positioning, and providing adequate sedation and analgesia, typically with agents such as fentanyl and midazolam. In patients exhibiting signs of agitation or sympathetic hyperactivity, deeper sedation or intermittent neuromuscular blockade was administered at the discretion of the treating surgeon. For patients with EVDs, intermittent cerebrospinal fluid drainage was initiated when ICP exceeded the target range. Continuous ABP monitoring was performed using radial artery transducers calibrated at the tragus level to accurately reflect cerebral perfusion. When the ICP remained persistently above the threshold values for more than 10 minutes despite initial measures, osmotic therapy was administered. This included intravenous boluses of 20% mannitol (0.5–1.0 g/kg over 15–20 minutes), repeated as needed based on clinical response and serum osmolality monitoring. Hypertonic saline solutions were considered alternatives or adjuncts when renal function was impaired. Fever control, electrolyte balance, and maintenance of euvolemia were concurrently ensured as part of a comprehensive approach to ICP management. Data Collection of LPRx Physiological monitoring data were retrospectively collected from the electronic ICU systems at NTUH and its Yunlin branch. For each patient, invasive ABP and ICP values were recorded at 1-minute intervals from the time of postoperative admission until discontinuation of invasive monitoring. All measurements were acquired using a standard ICU bedside Philips IntelliVue patient monitoring system (Philips Healthcare, Andover, MA, USA) and were subsequently archived in a centralized clinical data management system. Data collection began immediately after surgery and continued throughout the intensive care monitoring period, typically spanning the first several days of critical care. Minute-by-minute recordings of the ABP and ICP were extracted in a de-identified format for subsequent analysis. These signals were used to compute the LPRx, defined as the moving Pearson correlation coefficient between 20 consecutive 1-minute averages of ABP and ICP, recalculated every minute 6 . This windowed approach enabled dynamic, overlapping assessments of cerebral autoregulation with a level of temporal resolution sufficient for clinical interpretation while minimizing the technical demands of high-frequency waveform acquisition. Artifacts resulting from patient movement, nursing care, or technical interruptions were visually inspected and manually excluded from the analysis. The calculated LPRx values were then used in downstream analyses to assess autoregulatory trends, derive surrogate indicators of cerebral perfusion optimization, and explore their associations with clinical outcomes. Optimal CPP For each patient, monitoring data were segmented into CPP bins at 5 mmHg intervals within the 40–120 mmHg range. The corresponding mean LPRx values were aggregated within each bin. We then fitted a second-degree polynomial curve (quadratic regression) to the binned CPP-LPRx data using SPSS. The CPP value corresponding to the nadir of the resulting U-shaped curve (i.e., the point of the lowest LPRx) was identified as CPPopt, reflecting the pressure range most associated with a preserved autoregulatory function. Assessment of LPRx During Osmotic Therapy Infusion To evaluate the influence of osmotic therapy on cerebral autoregulation, we analyzed the changes in LPRx following the administration of osmotic therapy. For each dosing event, the LPRx values were derived from minute-by-minute recordings of ABP and ICP, which were continuously collected using standardized bedside monitors. Osmotic therapy infusion events were included only if the patients were free from routine nursing care, physiotherapy, or other potential sources of hemodynamic disturbances during the monitoring period. The temporal profile of each osmotic therapy was divided into two epochs: a 20-minute pre-infusion period, designated as the baseline phase, and a 40-minute post-infusion segment (from 20 to 60 minutes after initiation of therapy), representing the treatment phase. This post-treatment window was selected to capture the delayed hemodynamic effects of osmotic therapy, as described in previous studies. LPRx was computed as the moving Pearson correlation coefficient between 20 consecutive 1-minute averaged ABP and ICP values, updated every minute. Thus, each dosing event was characterized by two sets of LPRx measurements: baseline and post-infusion. These values were aggregated across all interventions for each patient over the intensive care monitoring. Data Analysis Statistical analyses were performed using IBM SPSS Statistics for Windows (version 29.0; IBM Corp., Armonk, NY). Since most physiological variables, including LPRx and CPPopt, were not normally distributed, they were summarized as median values with interquartile ranges (IQRs) and compared between groups using non-parametric tests. To evaluate the relationship between cerebral autoregulation and clinical parameters, median LPRx and CPPopt values for each patient were calculated across the entire monitoring period. The patients were stratified based on outcome groups and levels of autoregulatory function. Comparisons between groups were performed using the Mann–Whitney U test for two-group analyses. To examine the effects of osmotic therapy on cerebral autoregulation, generalized estimating equations (GEE) were employed to model LPRx as a response variable, with the intervention phase (baseline vs. treatment) as the primary predictor. The model accounted for within-subject correlations arising from repeated measurements over time and multiple dosing events. Statistical significance was set at a two-tailed p -value < 0.05. Results Demographic, Clinical, and Monitoring Data A total of 35 patients with TBI were included in the analysis. Of these, 26 (74.3%) survived and nine (25.7%) did not. When stratified by 6-month outcomes, eight patients (22.9%) had favorable outcomes, whereas 27 (77.1%) had unfavorable outcomes. No statistically significant differences were observed in demographic characteristics or underlying diseases between survivors and non-survivors or between the favorable and unfavorable outcome groups. Age, sex, and weight were comparable across all groups. A detailed summary of the demographic and clinical variables is provided in Table 1 . Table 1 Demographic, Clinical, and Monitoring Characteristics of the Study Cohort, Stratified by Survival and Functional Outcome Variables Survivors Non-survivors p Favorable Unfavorable p Total, n (%) 26 (74.3) 9 (25.7) 8 (22.9) 27 (77.1) Demographics Age, mean, year 65.00 ± 4.347 70.33 ± 7.721 0.557 59.00 ± 9.59 68.56 ± 3.97 0.380 Males, n (%) 18 (69.2) 5 (55.6) 0.456 7 (87.5) 16 (59.3) 0.139 Weight, mean, kilogram 61.22 ± 1.92 64.07 ± 3.14 0.453 61.11 ± 4.48 62.20 ± 1.70 0.825 Initial white blood cell count, mean 12.39 ± 0.98 11.93 ± 1.48 0.802 12.63 ± 1.72 12.16 ± 0.93 0.816 Initial blood sugar, mean 169.50 ± 11.57 161.00 ± 14.98 0.659 155.63 ± 17.54 170.78 ± 11.00 0.477 Underlying disease Hypertension 11 (42.3) 3 (33.3) 0.636 3 (37.5) 11 (40.7) 0.869 Diabetes mellitus 7 (26.9) 3 (33.3) 0.714 2 (25.0) 8 (29.6) 0.802 Coronary artery disease 1 (3.8) 2 (22.2) 0.094 0 (0) 3 (11.1) 0.331 Hemodialysis 1 (3.8) 0 (0) 0.556 0 (0) 1 (3.7) 0.586 Neurological status Initial GCS 7.5 (6–10) 5 (3-7.5) 0.022 7 (6–12) 7 (5–9) 0.563 Initial E 1.5 (1–3) 1 (1–1) 0.089 1.5 (1-2.75) 1 (1–3) 0.694 Initial M 5 (4–5) 3 (1-4.5) 0.019 4.5 (4-5.75) 4 (3–5) 0.463 Initial V 1 (1–3) 1 (1–1) 0.074 1 (1-3.5) 1 (1–2) 0.675 Overall monitoring period Total monitoring time, day 4.38 ± 0.30 4.10 ± 0.66 0.705 3.68 ± 0.45 4.50 ± 1.69 0.159 ICP, median, mmHg 8 (6.8–12.3) 12 (7-16.5) 0.145 10 (6.25–13.75) 9 (7–13) 0.89 ICP > 20 (median % time) 1.75 (0.5-4) 6.8 (0.6–31.5) 0.163 2.05 (0.46–5.38) 1.87 (0.49–6.78) 0.753 Mean arterial pressure, median, mmHg 86 (80.67–88.75) 79.67 (76.67–92.67) 0.497 87.83 (84.33-89.00) 82.33 (77.67–88.67) 0.099 Cerebral perfusion pressure, median, mmHg 73.5 (69.67–82.17) 72.17 (65.83-79.00) 0.257 81.00 (71.58–82.33) 73.33 (69.00-81.33) 0.223 LPRx, median 0.036 (-0.164-0.159) 0.102 (0.037–0.303) 0.105 –0.083 (–0.257 − 0.044) 0.071 (–0.012–0.227) 0.028 LPRx > 0 (median % time) 52.74 (38.53–64.57) 59.56 (53.32–69.32) 0.131 43.41 (31.44–54.52) 56.12 (48.66–65.18) 0.025 LPRx > 0.2 (median % time) 35.77 (26.58–45.03) 40.86 (35.07–56.35) 0.083 28.00 (20.56–34.15) 39.62 (30.91–51.69) 0.013 LPRx > 0.3 (median % time) 26.19 (20.38–38.22) 33.42 (27.02–50.02) 0.07 22.08 (15.47–25.32) 31.94 (22.35–45.31) 0.017 E = eye; GCS = Glasgow coma scale; ICP = intracranial pressure; LPRx = low-frequency pressure reactivity index; M = motor; V = verbal At admission, the median initial GCS score was significantly lower in non-survivors (5 [IQR: 3–7.5]) than in survivors (7.5 [IQR: 6–10]) ( p = 0.022). Among the GCS components, motor response showed a notable distinction, with survivors demonstrating higher scores (median M = 5 [IQR: 4–5]) than non-survivors (median M = 3 [IQR: 1–4.5]; p = 0.019). Eye-opening and verbal response scores also tended to be lower in the non-survivors, although the differences were not statistically significant. When stratified by 6-month outcomes, there were no significant differences in the initial GCS scores between the favorable and unfavorable outcome groups. The duration of physiological monitoring was similar across the groups. Likewise, mean arterial pressure and CPP were comparable between survivors and non-survivors, as well as between favorable and unfavorable outcome groups. Although ICP and the percentage of time spent above the 20-mmHg threshold tended to be higher in non-survivors, these differences were not statistically significant. In contrast, LPRx values were more impaired in patients with unfavorable functional outcomes. Specific.ally, the median LPRx was higher in non-survivors than in survivors, and the proportion of monitoring time with LPRx > 0, >0.2, and > 0.3 was consistently greater in the non-survivors group. While trends toward higher LPRx were observed among non-survivors, statistical significance was reached only in the comparison between the favorable and unfavorable outcome groups. These differences were significant for median LPRx ( p = 0.028), LPRx > 0 ( p = 0.025), LPRx > 0.2 ( p = 0.013), and LPRx > 0.3 ( p = 0.017). Temporal Trends in LPRx and Their Associations with Mortality and Long-Term Functional Outcome To assess the temporal pattern of cerebral autoregulation in relation to outcomes, we compared daily median LPRx values between survivors and non-survivors, as well as between patients with favorable and unfavorable 6-month functional outcomes. Non-survivors consistently exhibited higher LPRx values across all seven days; however, none of these comparisons reached statistical significance. Mann–Whitney U tests yielded p-values ranging from 0.090 on day 4 to 0.857 on day 7 (Fig. 1 a). When stratified by functional outcomes, a similar trend of higher LPRx values was observed in the group with poor outcomes. Notably, statistically significant differences were identified on days 1 ( p = 0.031), 3 ( p = 0.019), and 4 ( p = 0.036), indicating that impaired cerebral autoregulation during the early post-injury period was more strongly associated with long-term neurological disability than with in-hospital mortality. These findings are visually summarized in the accompanying chart, which shows persistently higher median LPRx values in the poor outcome group (Fig. 1 b). Association Between Decompressive Craniectomy and LPRx To evaluate the influence of decompressive craniectomy on cerebral autoregulation, the daily median LPRx values were compared between the patients who underwent craniectomy (Group 1) and those who did not (Group 0). Throughout the seven-day monitoring period, no statistically significant differences in LPRx were observed between the two groups on any day (Fig. 1 c). Association Between ICP and LPRx To examine the relationship between ICP and cerebral autoregulation, median LPRx was plotted across ICP bins at 5 mm Hg intervals. The analysis revealed a U-shaped pattern with a nadir at approximately 10 mmHg, suggesting an optimal autoregulatory function near this pressure level. As ICP increased beyond 15 mmHg, LPRx progressively increased, indicating worsening cerebral autoregulation. This trend became especially pronounced at ICP levels ≥ 25 mmHg, where median PRx increased steeply, reflecting impaired cerebral autoregulation. These findings support the concept of pressure-dependent vulnerability of cerebral autoregulation, emphasizing the clinical relevance of maintaining ICP within an optimal range (Fig. 2 ). Association Between Optimal CPP and LPRx To evaluate the relationship between CPPopt and cerebral autoregulation, the median LPRx was plotted across the CPPopt intervals. Unlike the U-shaped pattern observed for ICP, no consistent or statistically significant relationship was observed between CPPopt and LPRx (Fig. 3 ). The median LPRx remained relatively stable across the CPPopt range of 50–90 mmHg, with wider variability at the extremes. These findings suggest that within the studied range, CPPopt alone may not reliably predict autoregulatory function as indexed by LPRx, highlighting the complexity of individualized cerebral hemodynamics in TBI. Effect of Osmotic Therapy on Cerebral Autoregulation To evaluate the effect of mannitol treatment on cerebral autoregulation, a GEE model was applied using repeated LPRx measurements from 35 patients. Each treatment was administered as an individual visit, and the patients were observed across multiple time points using both pre- and post-infusion data. A total of 957 valid observations are included in the model. The estimated mean difference in LPRx between the pre- and post-mannitol phases was 0.004, which was not statistically significant (Wald χ² = 0.074, p = 0.786). Discussion Although PRx-based CPPopt has been proposed as a promising individualized target for TBI management, its clinical applicability remains limited. In this study, CPPopt could only be derived for 32% of the monitoring period, reflecting its limited availability in real-time clinical scenarios. This observation is consistent with prior reports, in which the yield of CPPopt generally ranged from 50 to 97%. 4,6,10–13 Furthermore, the recent COGiTATE trial demonstrated that even under protocol-driven CPPopt-guided management, concordance between actual CPP and the individualized target (± 5 mmHg) was achieved only 46.5% of the time. 12 These findings underscore the dynamic nature of autoregulation and the challenge of aligning treatment goals with rapidly fluctuating physiological targets. Notably, in the trial, alerts for CPP deviation were generated only six times daily, a frequency that was likely insufficient to inform meaningful and responsive bedside interventions. A more recent approach has been proposed using the lower limit of reactivity derived from PRx trends to define the threshold below which autoregulation becomes impaired. 14 Although this strategy improved the feasibility and target availability, it provided only a range rather than a precise goal for the intervention. The need for continuous estimation and the inherent uncertainty in defining a single actionable CPP target further question the clinical utility of PRx-based optimization strategies in routine neurocritical care. In contrast to the intermittent and often sparse availability of CPPopt, PRx and its low-frequency (LPRx) can be computed continuously, typically at 1-minute intervals, enabling real-time tracking of cerebral autoregulation 7 . This low-frequency resolution enables clinicians to monitor trends in vascular reactivity over time and may offer a more responsive and practical tool in dynamic neurocritical care settings. Although LPRx has been widely studied for its prognostic relevance in TBI, the specific threshold that distinguishes favorable from unfavorable outcomes remains inconsistent across the literature. The reported cutoff values vary considerably and are likely influenced by differences in study design, timing of measurement, and patient populations. 3 , 5 , 13 , 15 , 16 Notably, in contrast to previous findings, we observed that both favorable and unfavorable outcome groups often exhibited median PRx values below the previously suggested thresholds (e.g., 0.2), calling into question the reliability of a universal prognostic cutoff value. These findings suggest that rather than a fixed numerical threshold, the overall trajectory and burden of impaired autoregulation may be more clinically informative. These considerations support the potential value of using PRx or LPRx as a dynamic and continuously available metric rather than CPPopt as a targetable surrogate in individualized TBI management. Consistent with previous studies, our findings demonstrated that patients with favorable outcomes, both in terms of survival and neurological function, tended to exhibit lower LPRx values throughout the entire monitoring period. Although some of these differences were statistically significant, the overall trend supported the notion that preserved cerebral autoregulation is associated with better clinical outcomes. Furthermore, the burden of impaired autoregulation, reflected by the percentage of monitoring time spent above various LPRx thresholds (e.g., > 0, >0.2, and > 0.3), was greater in patients with poor functional outcomes and mortality. These observations suggest that the cumulative burden of autoregulatory failure, rather than isolated LPRx values, may be more predictive of patient trajectory. A similar concept has been discussed in recent ICP literature, where not only peak pressure values but also the duration and extent of intracranial hypertension (i.e., ICP dose) are associated with outcomes. 17 Moreover, PRx is increasingly recognized as a dynamic biomarker, and its prognostic utility varies over the clinical course. A recent study highlighted that the sensitivity of PRx for predicting poor outcomes peaked on hospital day six, after which it declined despite continued monitoring. 18 This temporal shift underscores that the interpretability and clinical relevance of PRx are not static but evolve over time. In our cohort, this time-sensitive pattern was similarly observed; early differences in the LPRx burden appeared more discriminative, suggesting a potential "window of vulnerability" during which autoregulatory failure may exert the greatest prognostic influence. These findings emphasize the importance of longitudinal PRx monitoring and support its role as a real-time physiological guide rather than a one-time measurement in neurocritical care decision making. Our analysis of the relationship between ICP and LPRx revealed a distinct U-shaped curve, with the lowest LPRx observed at an ICP of approximately 10 mmHg. This suggests that cerebral autoregulation is mostly preserved at this pressure level. Using a threshold of PRx > 0.2, which indicates impaired cerebral autoregulation, we found that ICP values below 25 mmHg were generally associated with more favorable LPRx values. This observation aligns well with current TBI guidelines, which recommend maintaining ICP below 22 mmHg. Given that elevated ICP is consistently associated with poor clinical outcomes, our findings reinforce this guideline and suggest that PRx may provide additional context by identifying when ICP falls within a range that supports intact autoregulation. More importantly, within this wide spectrum of "acceptable" ICP values, the critical question becomes not just how high ICP is but whether autoregulation is preserved at a given pressure in a specific clinical context. Thus, the ICP-derived PRx may offer a more nuanced and patient-specific perspective than ICP alone. In contrast, our evaluation of CPPopt derived from LPRx through pooled analysis across all patients and time points did not demonstrate a clear U-shaped relationship between CPPopt and LPRx. The absence of this expected parabolic pattern underscores the limitations of generalizing CPPopt targets across individuals and time frames. Although the theoretical CPPopt, at which LPRx is minimized, offers a compelling individualized treatment target, our data suggest that such a value cannot be consistently identified from pooled observations. This reinforces the notion that CPPopt is highly dynamic and context-specific and that population-level analyses may obscure the temporal and inter-individual variability inherent to autoregulatory functions. These findings further support the limitations of using CPPopt as a fixed or universally applicable target in clinical decision making. Although the prognostic value of PRx in patients with TBI has been widely documented, its responsiveness to therapeutic interventions remains unexplored. In particular, whether PRx can be meaningfully modulated through clinical management has been a topic of debate. In this study, we evaluated the effects of two commonly employed interventions, decompressive craniectomy (DC) and osmotic therapy, on cerebral autoregulation, as indexed by LPRx. Interestingly, no significant association was found between the intervention and changes in LPRx across the monitoring course. This contrasts with an earlier report 19 in which PRx was observed to increase, suggesting impaired reactivity following DC treatment in the same cohort of patients. It is important to interpret these findings in this context. Their study focused on within-subject comparisons of PRx before and after surgery, a design that might not reflect the broader clinical question of whether DC contributes to the maintenance or restoration of autoregulatory function over time. In fact, as our between-group analysis suggests, patients who received DC may have avoided further deterioration of PRx had the procedure not been performed. Thus, although the derangement of PRx post-DC has been reported, such findings should not be interpreted as evidence of the intervention's overall benefit. Our results underscore the need to assess PRx trends in the context of natural disease progression and the potential counterfactual outcomes in untreated patients. Similarly, we found no significant differences in LPRx before and after osmotic therapy. This finding may reflect the temporally limited effect of osmotic agents such as mannitol, which are known to acutely lower ICP but may not influence long-term vascular reactivity. Additionally, prophylactic osmotic therapy has not consistently demonstrated improvements in clinical outcomes in previous trials, suggesting that its role may be more supportive than that of a transformative therapy. It is plausible that osmotic agents have other physiological effects, such as modulating blood viscosity or endothelial tone, which could influence autoregulation; however, such effects were not apparent in our analysis. These results indicate that, although both DC and osmotic therapy remain vital tools in ICP management, their direct impact on restoring cerebral autoregulation warrants further investigation in larger and more targeted studies. This study has some limitations. First, the relatively small sample size may have limited the statistical power to detect subtle effects. Second, although the use of LPRx enables continuous and practical bedside assessment, it may not capture the full temporal dynamics and sensitivity of high-frequency PRx signals. Third, as a retrospective analysis with potential variability in treatment protocols, the timing of interventions, and patient-specific factors, all of which could influence cerebral autoregulation and confound the observed associations. Lastly, while efforts have been made to evaluate the effect of therapeutic interventions such as decompressive craniectomy and osmotic therapy, the complexity of autoregulatory physiology means that other unmeasured factors may have contributed to the observed patterns. Despite these limitations, our findings provide valuable insights into the application and interpretation of PRx-based monitoring for the clinical management of TBI. We demonstrated that impaired cerebral autoregulation, as indexed by LPRx, was associated with poor outcomes not only in terms of absolute values but also in relation to the duration of autoregulatory dysfunction. Although CPPopt remains a theoretically appealing individualized target for TBI, its low availability and variability limit its practicality in real-world settings. In contrast, LPRx offers a continuous, real-time measure of autoregulation and may serve as a reliable guide for individualized care. The lack of measurable improvement in LPRx following decompressive craniectomy or osmotic therapy further highlights the complexity of cerebral hemodynamics and underscores the need for more nuanced strategies to preserve or restore autoregulatory function. Future prospective studies with larger cohorts and multimodal monitoring are warranted to refine the clinical use of LPRx and to explore its potential role as a prognostic biomarker and modifiable therapeutic target. Conclusion Impaired cerebral autoregulation, as reflected by elevated LPRx and a prolonged burden above the threshold, is associated with unfavorable outcomes in patients with TBI. Although CPPopt remains conceptually attractive, its low availability and variability limit its clinical utility. Further investigation is warranted to better understand how conventional therapies influence autoregulatory functions and whether LPRx can eventually serve as a therapeutic target in personalized TBI management. Declarations Compliance with Journal Instructions: We confirm that the submitted manuscript complies with all the instructions to authors for the Neurocritical Care. This includes adherence to ethical standards, conflict of interest disclosures, formatting guidelines, word count limitations, figure and table requirements, and reference formatting. We have reviewed and followed all journal policies regarding manuscript preparation, submission requirements, and have ensured all authors approve the submission of this manuscript Author Contributions: Ue-Cheung Ho: Conceptualization (Equal); Data curation (Lead); Formal analysis (Lead); Methodology (Supporting); Writing – original draft (Lead). Nathan Wei: Conceptualization (Equal); Data curation (Supporting); Formal analysis (Supporting). Lu-Ting Kuo: Conceptualization (Lead); Methodology (Lead); Resources (Lead); Supervision (Lead); Writing – original draft (Supporting); Writing – review & editing (Lead) Authorship Confirmation Statement: We confirm that all authors meet the authorship requirements as outlined by Neurocritical Care. All authors agree to be accountable for all aspects of the work, ensuring the accuracy and integrity of the research. Exclusive Submission Confirmation: We confirm that this manuscript has not been published elsewhere and is not currently under consideration by another journal. This submission is original and has not been previously disseminated in any form, ensuring its exclusive consideration by Neurocritical Care. Ethical Statement: This study was performed in compliance with local regulations, adhered to the Declaration of Helsinki, and was approved by the institutional review board of the institution of National Taiwan University Hospital (IRB number: 202408094RINE). All patients provided general consent upon admission for the use of their anonymized medical data for academic purposes. Conflicts of Interest: The authors declare that they have no conflicts of interest. Use of EQUATOR Checklist: This manuscript was prepared following the STrengthening the Reporting of OBservational studies in Epidemiology (STROBE) statement. Funding: We declare that we have no sources of funding. Acknowledgments: We would like to thank Editage (www.editage.com) for English language editing and journal submission support. Data Availability: The datasets generated during and/or analyzed during the current study are available from the corresponding author upon reasonable request. References Carney N, Totten AM, O’Reilly C, et al. Guidelines for the management of severe traumatic brain injury. Neurosurgery. 2017;80:6–15. https://doi.org/10.1227/NEU.0000000000001432 . Brady KM, Shaffner DH, Lee JK, et al. Continuous monitoring of cerebrovascular pressure reactivity after traumatic brain injury in children. Pediatrics. 2009;124:e1205–12. https://doi.org/10.1542/peds.2009-0550 . Sorrentino E, Diedler J, Kasprowicz M, et al. Critical thresholds for cerebrovascular reactivity after traumatic brain injury. Neurocrit Care. 2012;16:258–66. https://doi.org/10.1007/s12028-011-9630-8 . Lang EW, Kasprowicz M, Smielewski P, Santos E, Pickard J, Czosnyka M. Short pressure reactivity index versus long pressure reactivity index in the management of traumatic brain injury. J Neurosurg. 2015;122:588–94. https://doi.org/10.3171/2014.10.JNS14602 . Smith CA, Rohlwink UK, Mauff K, et al. Cerebrovascular pressure reactivity has a strong and independent association with outcome in children with severe traumatic brain injury. Crit Care Med. 2023;51:573–83. https://doi.org/10.1097/CCM.0000000000005815 . Santos E, Diedler J, Sykora M, et al. Low-frequency sampling for PRx calculation does not reduce prognostication and produces similar CPPopt in intracerebral haemorrhage patients. Acta Neurochir (Wien). 2011;153:2189–95. https://doi.org/10.1007/s00701-011-1148-5 . Sánchez-Porras R, Santos E, Czosnyka M, Zheng Z, Unterberg AW, Sakowitz OW. Long’ pressure reactivity index (L-PRx) as a measure of autoregulation correlates with outcome in traumatic brain injury patients. Acta Neurochir (Wien). 2012;154:1575–81. https://doi.org/10.1007/s00701-012-1423-0 . Riemann L, Beqiri E, Smielewski P, et al. Low-resolution pressure reactivity index and its derived optimal cerebral perfusion pressure in adult traumatic brain injury: a CENTER-TBI study. Crit Care. 2020;24:266. https://doi.org/10.1186/s13054-020-02974-8 . Hong E, Froese L, Pontén E, et al. Critical thresholds of long-pressure reactivity index and impact of intracranial pressure monitoring methods in traumatic brain injury. Crit Care. 2024;28:256. https://doi.org/10.1186/s13054-024-05042-7 . Steiner LA, Czosnyka M, Piechnik SK, et al. Continuous monitoring of cerebrovascular pressure reactivity allows determination of optimal cerebral perfusion pressure in patients with traumatic brain injury. Crit Care Med. 2002;30:733–8. https://doi.org/10.1097/00003246-200204000-00002 . Aries MJH, Czosnyka M, Budohoski KP, et al. Continuous determination of optimal cerebral perfusion pressure in traumatic brain injury. Crit Care Med. 2012;40:2456–63. https://doi.org/10.1097/CCM.0b013e3182514eb6 . Tas J, Beqiri E, van Kaam RC, et al. Targeting autoregulation-guided cerebral perfusion pressure after traumatic brain injury (COGiTATE): a feasibility randomized controlled clinical trial. J Neurotrauma. 2021;38:2790–800. https://doi.org/10.1089/neu.2021.0197 . Gritti P, Bonfanti M, Zangari R, et al. Evaluation and application of ultra-low-resolution pressure reactivity index in moderate or severe traumatic brain injury. J Neurosurg Anesthesiol. 2023;35:313–21. https://doi.org/10.1097/ANA.0000000000000847 . Beqiri E, Zeiler FA, Ercole A, et al. The lower limit of reactivity as a potential individualised cerebral perfusion pressure target in traumatic brain injury: a CENTER-TBI high-resolution sub-study analysis. Crit Care. 2023;27:194. https://doi.org/10.1186/s13054-023-04485-8 . Czosnyka M, Smielewski P, Kirkpatrick P, Laing RJ, Menon D, Pickard JD. Continuous assessment of the cerebral vasomotor reactivity in head injury. Neurosurgery. 1997;41:11–7. https://doi.org/10.1097/00006123-199707000-00005 . discussion 17–9. Chang JJ, Kepplinger D, Metter EJ, et al. Pressure reactivity index for early neuroprognostication in poor-grade subarachnoid hemorrhage. J Neurol Sci. 2023;450:120691. https://doi.org/10.1016/j.jns.2023.120691 . Zoerle T, Beqiri E, Åkerlund CAI, et al. Intracranial pressure monitoring in adult patients with traumatic brain injury: challenges and innovations. Lancet Neurol. 2024;23:938–50. https://doi.org/10.1016/S1474-4422(24)00235-7 . Chang JJ, Kepplinger D, Metter EJ, et al. Time thresholds for using pressure reactivity index in neuroprognostication for patients with severe traumatic brain injury. Neurosurgery. 2024;95:297–304. https://doi.org/10.1227/neu.0000000000002876 . Timofeev I, Czosnyka M, Nortje J, et al. Effect of decompressive craniectomy on intracranial pressure and cerebrospinal compensation following traumatic brain injury. J Neurosurg. 2008;108:66–73. https://doi.org/10.3171/JNS/2008/108/01/0066 . Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7029976","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":483423184,"identity":"4c27e8ee-36f5-4e50-a8a7-6206f92d01a1","order_by":0,"name":"Ue-Cheung Ho","email":"","orcid":"","institution":"National Taiwan University Hospital","correspondingAuthor":false,"prefix":"","firstName":"Ue-Cheung","middleName":"","lastName":"Ho","suffix":""},{"id":483423185,"identity":"3431a860-2dc3-4fb0-9d2c-1b5b5fde0b61","order_by":1,"name":"Nathan Wei","email":"","orcid":"","institution":"National Taiwan University Hospital","correspondingAuthor":false,"prefix":"","firstName":"Nathan","middleName":"","lastName":"Wei","suffix":""},{"id":483423186,"identity":"35a2c7a2-98cb-40cc-b363-14aafad35ae9","order_by":2,"name":"Lu-Ting Kuo","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA1ElEQVRIiWNgGAWjYBACCQYGxgNgir0ByDWwIEoLwwGGBCDFcwCkRYJoLSBWAoxPAEjOSD5wmPeHRZ585POrG34USDDwt3cn4NUiLZGWcJgnQaLY8HZO2c0eoMMkzpzdgFeLnESOAUhL4sbZOWk3eIBaDCRyidUy80zazT/EaJGGaZkvwX7sNlG2SPY8Szg4J00icQNPDtttGQMJHoJ+kTiefPDBG5u6xPntx5/dfPPHRo6/vRe/FjgwOMBjAKJ5iFMOAvIN7A+IVz0KRsEoGAUjCgAALr5HfYNv28cAAAAASUVORK5CYII=","orcid":"https://orcid.org/0000-0002-1405-8700","institution":"National Taiwan University Hospital","correspondingAuthor":true,"prefix":"","firstName":"Lu-Ting","middleName":"","lastName":"Kuo","suffix":""}],"badges":[],"createdAt":"2025-07-02 13:47:49","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7029976/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7029976/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":86674098,"identity":"6aa219f6-8645-4553-95ef-a1cb1ee19888","added_by":"auto","created_at":"2025-07-14 11:51:59","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":469261,"visible":true,"origin":"","legend":"\u003cp\u003eDaily median LPRx during the first seven days post-injury, shown by (a) survivors and non-survivors, (b) functional outcome, and (c) patients with and without decompressive craniectomy.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-7029976/v1/f457627ca78d83834918887d.png"},{"id":86674092,"identity":"ac3de1d9-406a-4b5a-91c0-437f1c77f97c","added_by":"auto","created_at":"2025-07-14 11:51:59","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":139687,"visible":true,"origin":"","legend":"\u003cp\u003eRelationship between ICP and median LPRx\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-7029976/v1/4c74b1685e74023f3681c2f1.png"},{"id":86674093,"identity":"72ed16c6-4c4d-4af1-8a42-aa5bf7de9901","added_by":"auto","created_at":"2025-07-14 11:51:59","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":135434,"visible":true,"origin":"","legend":"\u003cp\u003eRelationship between optimal cerebral perfusion pressure and median LPRx\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-7029976/v1/9c3d3da5a63aa4b842f26728.png"},{"id":87232211,"identity":"96b6b1a8-f517-42a8-92a3-9b3677c15125","added_by":"auto","created_at":"2025-07-21 19:28:10","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1695701,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7029976/v1/7869efe9-f627-43e8-849b-be6c418aa2cc.pdf"}],"financialInterests":"","formattedTitle":"Evaluation of the Prognostic Value and Modifiability of Low-Frequency Pressure Reactivity Index in Patients with Traumatic Brain Injury","fulltext":[{"header":"Introduction","content":"\u003cp\u003eTraumatic brain injury (TBI) remains a critical global health concern, contributing to high mortality and long-term disability rates across a wide demographic range. Contemporary management of moderate-to-severe TBI focuses on preventing secondary brain insults, such as intracranial hypertension and cerebral hypoperfusion, both of which are associated with poor neurological outcomes. Traditionally, therapeutic strategies have focused on maintaining intracranial pressure (ICP) and cerebral perfusion pressure (CPP) within fixed thresholds.\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e However, these standardized targets often overlook patient-specific variations in cerebral autoregulation.\u003c/p\u003e\u003cp\u003eCerebral autoregulation, the brain's ability to maintain stable blood flow despite fluctuations in perfusion pressure, is a fundamental physiological process that can be significantly disrupted by TBI. The pressure reactivity index (PRx), derived from the correlation between slow-wave changes in mean arterial pressure and ICP, serves as a continuous, dynamic surrogate marker of autoregulatory integrity.\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e Elevated PRx levels indicate impaired autoregulation and have been continuously associated with increased mortality and unfavorable long-term functional outcomes in both adult and pediatric populations.\u003csup\u003e\u003cspan additionalcitationids=\"CR3 CR4\" citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e–\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\u003cp\u003eDespite its established prognostic value, there is limited evidence on how clinical interventions such as pharmacological agents or surgical procedures directly influence PRx trajectories over time. Most current practices treat PRx as a monitoring tool rather than a modifiable target, leaving a gap in understanding whether individualized treatments can actively restore or stabilize the autoregulatory capacity. As emerging approaches advocate tailoring CPP targets to a patient's optimal CPP (CPPopt) derived from the lowest PRx, investigating the modifiable determinants of PRx has become increasingly relevant​.\u003c/p\u003e\u003cp\u003eAlthough high-resolution PRx monitoring has demonstrated strong prognostic significance in patients with TBI, its clinical implementation requires continuous waveform recording and advanced signal-processing infrastructure, and resources are often limited to specialized neurocritical care units. As a more practical alternative, the low-frequency pressure reactivity index (LPRx), which is derived from minute-by-minute averaged arterial and intracranial pressure signals, has been proposed to estimate cerebral autoregulation using standard intensive care monitoring systems.\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e Although slightly less sensitive than its high-resolution counterpart, LPRx has demonstrated comparable associations with patient outcomes, enabling the wider adoption of autoregulation-based assessments across different care settings.\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e,\u003cspan additionalcitationids=\"CR7 CR8\" citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e–\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\u003cp\u003eIn this study, we utilized the LPRx as a practical and accessible surrogate for assessing cerebral autoregulation in patients with TBI. We aimed to examine LPRx dynamics in relation to clinical outcomes and treatment interventions with the goal of advancing individualized, physiology-driven approaches in neurocritical care.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cb\u003eStudy Participants and Setting\u003c/b\u003e\u003c/p\u003e\u003cp\u003eWe conducted a retrospective analysis of 35 consecutive patients with TBI who underwent surgery at the National Taiwan University Hospital (NTUH) and its Yunlin branch between January 2022 and December 2024. Surgical procedures included decompressive craniotomy or craniectomy with or without hematoma evacuation, accompanied by ICP monitoring or external ventricular drain (EVD) placement. Prehospital and surgical care adhered to the contemporary TBI management guidelines.\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\u003cp\u003eEligible patients were 18 years or older and had sustained a moderate-to-severe TBI requiring neurosurgical intervention. All patients were admitted to the intensive care unit (ICU) for postoperative care, during which arterial blood pressure (ABP) and ICP were continuously monitored, allowing for subsequent analysis of LPRx. Inclusion also required a signed proxy informed consent obtained from the patient's legal representative or next of kin upon admission. Patients were excluded if they had a history of neurological disorders, such as brain tumors, stroke, previous head trauma, meningitis, known substance use disorders, or a prior history of brain surgery. Patients whose injuries were deemed unsurvivable at presentation, who were pregnant at the time of admission, or who had a do-not-resuscitate order authorized by their families were also excluded. Furthermore, those without sufficient quality physiological data, defined as fewer than 24 hours of valid ICP and CPP recordings, or those lacking essential clinical information, were excluded from the analysis.\u003c/p\u003e\u003cp\u003eAll patients were admitted to the ICU for postoperative care, where ABP, ICP, oxygen saturation, and body temperature were continuously monitored. Standard ICU management includes prophylactic antibiotics, antiepileptic drugs, and early initiation of enteral nutrition. Hourly neurological assessments, including the Glasgow Coma Scale (GCS) score and evaluation of pupil size and light reflex, were performed. Specific treatment decisions were made at the discretion of the attending neurosurgeons.\u003c/p\u003e\u003cp\u003eTo explore the clinical and physiological correlates of outcomes, patients were categorized into groups based on 6-month survival (survivors vs. non-survivors) and 6-month functional outcome, as determined by the Glasgow Outcome Scale Extended (GOSE), and dichotomized into favorable outcomes (GOSE 5–8) and unfavorable outcomes (GOSE 1–4). These groupings were used for the subsequent comparative and statistical analyses.\u003c/p\u003e\u003cp\u003e This study was approved by the National Taiwan University Hospital Research Ethics Committee (#202408094RINE) and conducted in accordance with the Declaration of Helsinki. All patients provided general consent upon admission for the use of their anonymized medical data for academic purposes. Data were extracted from electronic medical records in a de-identified format, and patient privacy was maintained throughout the study.\u003c/p\u003e\u003cp\u003e\u003cb\u003eManagement of Increased Intracranial Pressure\u003c/b\u003e\u003c/p\u003e\u003cp\u003e A standardized, stepwise treatment strategy was employed to control elevated ICP in accordance with contemporary neurocritical care guidelines and institutional protocols. The primary therapeutic goal was to maintain ICP \u0026lt; 22 mmHg and CPP \u0026gt; 50 mmHg throughout the critical monitoring period.\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\u003cp\u003eInitial management included elevating the head of the bed to 30°, ensuring neutral neck positioning, and providing adequate sedation and analgesia, typically with agents such as fentanyl and midazolam. In patients exhibiting signs of agitation or sympathetic hyperactivity, deeper sedation or intermittent neuromuscular blockade was administered at the discretion of the treating surgeon. For patients with EVDs, intermittent cerebrospinal fluid drainage was initiated when ICP exceeded the target range. Continuous ABP monitoring was performed using radial artery transducers calibrated at the tragus level to accurately reflect cerebral perfusion.\u003c/p\u003e\u003cp\u003eWhen the ICP remained persistently above the threshold values for more than 10 minutes despite initial measures, osmotic therapy was administered. This included intravenous boluses of 20% mannitol (0.5–1.0 g/kg over 15–20 minutes), repeated as needed based on clinical response and serum osmolality monitoring. Hypertonic saline solutions were considered alternatives or adjuncts when renal function was impaired. Fever control, electrolyte balance, and maintenance of euvolemia were concurrently ensured as part of a comprehensive approach to ICP management.\u003c/p\u003e\u003cp\u003e\u003cb\u003eData Collection of LPRx\u003c/b\u003e\u003c/p\u003e\u003cp\u003ePhysiological monitoring data were retrospectively collected from the electronic ICU systems at NTUH and its Yunlin branch. For each patient, invasive ABP and ICP values were recorded at 1-minute intervals from the time of postoperative admission until discontinuation of invasive monitoring. All measurements were acquired using a standard ICU bedside Philips IntelliVue patient monitoring system (Philips Healthcare, Andover, MA, USA) and were subsequently archived in a centralized clinical data management system. Data collection began immediately after surgery and continued throughout the intensive care monitoring period, typically spanning the first several days of critical care.\u003c/p\u003e\u003cp\u003eMinute-by-minute recordings of the ABP and ICP were extracted in a de-identified format for subsequent analysis. These signals were used to compute the LPRx, defined as the moving Pearson correlation coefficient between 20 consecutive 1-minute averages of ABP and ICP, recalculated every minute\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e. This windowed approach enabled dynamic, overlapping assessments of cerebral autoregulation with a level of temporal resolution sufficient for clinical interpretation while minimizing the technical demands of high-frequency waveform acquisition.\u003c/p\u003e\u003cp\u003eArtifacts resulting from patient movement, nursing care, or technical interruptions were visually inspected and manually excluded from the analysis. The calculated LPRx values were then used in downstream analyses to assess autoregulatory trends, derive surrogate indicators of cerebral perfusion optimization, and explore their associations with clinical outcomes.\u003c/p\u003e\u003cp\u003e\u003cb\u003eOptimal CPP\u003c/b\u003e\u003c/p\u003e\u003cp\u003eFor each patient, monitoring data were segmented into CPP bins at 5 mmHg intervals within the 40–120 mmHg range. The corresponding mean LPRx values were aggregated within each bin. We then fitted a second-degree polynomial curve (quadratic regression) to the binned CPP-LPRx data using SPSS. The CPP value corresponding to the nadir of the resulting U-shaped curve (i.e., the point of the lowest LPRx) was identified as CPPopt, reflecting the pressure range most associated with a preserved autoregulatory function.\u003c/p\u003e\u003cp\u003e\u003cb\u003eAssessment of LPRx During Osmotic Therapy Infusion\u003c/b\u003e\u003c/p\u003e\u003cp\u003eTo evaluate the influence of osmotic therapy on cerebral autoregulation, we analyzed the changes in LPRx following the administration of osmotic therapy. For each dosing event, the LPRx values were derived from minute-by-minute recordings of ABP and ICP, which were continuously collected using standardized bedside monitors. Osmotic therapy infusion events were included only if the patients were free from routine nursing care, physiotherapy, or other potential sources of hemodynamic disturbances during the monitoring period.\u003c/p\u003e\u003cp\u003eThe temporal profile of each osmotic therapy was divided into two epochs: a 20-minute pre-infusion period, designated as the baseline phase, and a 40-minute post-infusion segment (from 20 to 60 minutes after initiation of therapy), representing the treatment phase. This post-treatment window was selected to capture the delayed hemodynamic effects of osmotic therapy, as described in previous studies.\u003c/p\u003e\u003cp\u003eLPRx was computed as the moving Pearson correlation coefficient between 20 consecutive 1-minute averaged ABP and ICP values, updated every minute. Thus, each dosing event was characterized by two sets of LPRx measurements: baseline and post-infusion. These values were aggregated across all interventions for each patient over the intensive care monitoring.\u003c/p\u003e\u003ch2\u003eData Analysis\u003c/h2\u003e\u003cp\u003eStatistical analyses were performed using IBM SPSS Statistics for Windows (version 29.0; IBM Corp., Armonk, NY). Since most physiological variables, including LPRx and CPPopt, were not normally distributed, they were summarized as median values with interquartile ranges (IQRs) and compared between groups using non-parametric tests.\u003c/p\u003e\u003cp\u003eTo evaluate the relationship between cerebral autoregulation and clinical parameters, median LPRx and CPPopt values for each patient were calculated across the entire monitoring period. The patients were stratified based on outcome groups and levels of autoregulatory function. Comparisons between groups were performed using the Mann–Whitney U test for two-group analyses.\u003c/p\u003e\u003cp\u003eTo examine the effects of osmotic therapy on cerebral autoregulation, generalized estimating equations (GEE) were employed to model LPRx as a response variable, with the intervention phase (baseline vs. treatment) as the primary predictor. The model accounted for within-subject correlations arising from repeated measurements over time and multiple dosing events. Statistical significance was set at a two-tailed \u003cem\u003ep\u003c/em\u003e-value \u0026lt; 0.05.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cb\u003eDemographic, Clinical, and Monitoring Data\u003c/b\u003e\u003c/p\u003e\u003cp\u003eA total of 35 patients with TBI were included in the analysis. Of these, 26 (74.3%) survived and nine (25.7%) did not. When stratified by 6-month outcomes, eight patients (22.9%) had favorable outcomes, whereas 27 (77.1%) had unfavorable outcomes.\u003c/p\u003e\u003cp\u003eNo statistically significant differences were observed in demographic characteristics or underlying diseases between survivors and non-survivors or between the favorable and unfavorable outcome groups. Age, sex, and weight were comparable across all groups. A detailed summary of the demographic and clinical variables is provided in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eDemographic, Clinical, and Monitoring Characteristics of the Study Cohort, Stratified by Survival and Functional Outcome\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"7\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariables\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSurvivors\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNon-survivors\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eFavorable\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eUnfavorable\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e26 (74.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e9 (25.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e8 (22.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e27 (77.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eDemographics\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge, mean, year\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e65.00\u0026thinsp;\u0026plusmn;\u0026thinsp;4.347\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e70.33\u0026thinsp;\u0026plusmn;\u0026thinsp;7.721\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.557\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e59.00\u0026thinsp;\u0026plusmn;\u0026thinsp;9.59\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e68.56\u0026thinsp;\u0026plusmn;\u0026thinsp;3.97\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.380\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMales, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e18 (69.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5 (55.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.456\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e7 (87.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e16 (59.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.139\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWeight, mean, kilogram\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e61.22\u0026thinsp;\u0026plusmn;\u0026thinsp;1.92\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e64.07\u0026thinsp;\u0026plusmn;\u0026thinsp;3.14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.453\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e61.11\u0026thinsp;\u0026plusmn;\u0026thinsp;4.48\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e62.20\u0026thinsp;\u0026plusmn;\u0026thinsp;1.70\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.825\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eInitial white blood cell count, mean\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e12.39\u0026thinsp;\u0026plusmn;\u0026thinsp;0.98\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e11.93\u0026thinsp;\u0026plusmn;\u0026thinsp;1.48\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.802\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e12.63\u0026thinsp;\u0026plusmn;\u0026thinsp;1.72\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e12.16\u0026thinsp;\u0026plusmn;\u0026thinsp;0.93\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.816\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eInitial blood sugar, mean\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e169.50\u0026thinsp;\u0026plusmn;\u0026thinsp;11.57\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e161.00\u0026thinsp;\u0026plusmn;\u0026thinsp;14.98\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.659\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e155.63\u0026thinsp;\u0026plusmn;\u0026thinsp;17.54\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e170.78\u0026thinsp;\u0026plusmn;\u0026thinsp;11.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.477\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eUnderlying disease\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHypertension\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e11 (42.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3 (33.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.636\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3 (37.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e11 (40.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.869\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDiabetes mellitus\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e7 (26.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3 (33.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.714\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2 (25.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e8 (29.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.802\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCoronary artery disease\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1 (3.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2 (22.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.094\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0 (0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e3 (11.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.331\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHemodialysis\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1 (3.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0 (0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.556\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0 (0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1 (3.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.586\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eNeurological status\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eInitial GCS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e7.5 (6\u0026ndash;10)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5 (3-7.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e0.022\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e7 (6\u0026ndash;12)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e7 (5\u0026ndash;9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.563\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eInitial E\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.5 (1\u0026ndash;3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1 (1\u0026ndash;1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.089\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.5 (1-2.75)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1 (1\u0026ndash;3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.694\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eInitial M\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5 (4\u0026ndash;5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3 (1-4.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e0.019\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e4.5 (4-5.75)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e4 (3\u0026ndash;5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.463\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eInitial V\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1 (1\u0026ndash;3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1 (1\u0026ndash;1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.074\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1 (1-3.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1 (1\u0026ndash;2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.675\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eOverall monitoring period\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal monitoring time, day\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4.38\u0026thinsp;\u0026plusmn;\u0026thinsp;0.30\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4.10\u0026thinsp;\u0026plusmn;\u0026thinsp;0.66\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.705\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3.68\u0026thinsp;\u0026plusmn;\u0026thinsp;0.45\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e4.50\u0026thinsp;\u0026plusmn;\u0026thinsp;1.69\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.159\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eICP, median, mmHg\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e8 (6.8\u0026ndash;12.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e12 (7-16.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.145\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e10 (6.25\u0026ndash;13.75)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e9 (7\u0026ndash;13)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.89\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eICP\u0026thinsp;\u0026gt;\u0026thinsp;20 (median % time)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.75 (0.5-4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6.8 (0.6\u0026ndash;31.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.163\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.05 (0.46\u0026ndash;5.38)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.87 (0.49\u0026ndash;6.78)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.753\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMean arterial pressure, median, mmHg\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e86 (80.67\u0026ndash;88.75)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e79.67 (76.67\u0026ndash;92.67)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.497\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e87.83 (84.33-89.00)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e82.33 (77.67\u0026ndash;88.67)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.099\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCerebral perfusion pressure, median, mmHg\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e73.5 (69.67\u0026ndash;82.17)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e72.17 (65.83-79.00)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.257\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e81.00 (71.58\u0026ndash;82.33)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e73.33 (69.00-81.33)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.223\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLPRx, median\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.036 (-0.164-0.159)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.102 (0.037\u0026ndash;0.303)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.105\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026ndash;0.083 (\u0026ndash;0.257\u0026thinsp;\u0026minus;\u0026thinsp;0.044)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.071 (\u0026ndash;0.012\u0026ndash;0.227)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e\u003cb\u003e0.028\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLPRx\u0026thinsp;\u0026gt;\u0026thinsp;0 (median % time)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e52.74 (38.53\u0026ndash;64.57)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e59.56 (53.32\u0026ndash;69.32)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.131\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e43.41 (31.44\u0026ndash;54.52)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e56.12 (48.66\u0026ndash;65.18)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e\u003cb\u003e0.025\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLPRx\u0026thinsp;\u0026gt;\u0026thinsp;0.2 (median % time)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e35.77 (26.58\u0026ndash;45.03)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e40.86 (35.07\u0026ndash;56.35)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.083\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e28.00 (20.56\u0026ndash;34.15)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e39.62 (30.91\u0026ndash;51.69)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e\u003cb\u003e0.013\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLPRx\u0026thinsp;\u0026gt;\u0026thinsp;0.3 (median % time)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e26.19 (20.38\u0026ndash;38.22)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e33.42 (27.02\u0026ndash;50.02)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e22.08 (15.47\u0026ndash;25.32)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e31.94 (22.35\u0026ndash;45.31)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e\u003cb\u003e0.017\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"7\"\u003eE\u0026thinsp;=\u0026thinsp;eye; GCS\u0026thinsp;=\u0026thinsp;Glasgow coma scale; ICP\u0026thinsp;=\u0026thinsp;intracranial pressure; LPRx\u0026thinsp;=\u0026thinsp;low-frequency pressure reactivity index; M\u0026thinsp;=\u0026thinsp;motor; V\u0026thinsp;=\u0026thinsp;verbal\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eAt admission, the median initial GCS score was significantly lower in non-survivors (5 [IQR: 3\u0026ndash;7.5]) than in survivors (7.5 [IQR: 6\u0026ndash;10]) (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.022). Among the GCS components, motor response showed a notable distinction, with survivors demonstrating higher scores (median M\u0026thinsp;=\u0026thinsp;5 [IQR: 4\u0026ndash;5]) than non-survivors (median M\u0026thinsp;=\u0026thinsp;3 [IQR: 1\u0026ndash;4.5]; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.019). Eye-opening and verbal response scores also tended to be lower in the non-survivors, although the differences were not statistically significant. When stratified by 6-month outcomes, there were no significant differences in the initial GCS scores between the favorable and unfavorable outcome groups.\u003c/p\u003e\u003cp\u003eThe duration of physiological monitoring was similar across the groups. Likewise, mean arterial pressure and CPP were comparable between survivors and non-survivors, as well as between favorable and unfavorable outcome groups. Although ICP and the percentage of time spent above the 20-mmHg threshold tended to be higher in non-survivors, these differences were not statistically significant.\u003c/p\u003e\u003cp\u003eIn contrast, LPRx values were more impaired in patients with unfavorable functional outcomes. Specific.ally, the median LPRx was higher in non-survivors than in survivors, and the proportion of monitoring time with LPRx\u0026thinsp;\u0026gt;\u0026thinsp;0, \u0026gt;0.2, and \u0026gt;\u0026thinsp;0.3 was consistently greater in the non-survivors group. While trends toward higher LPRx were observed among non-survivors, statistical significance was reached only in the comparison between the favorable and unfavorable outcome groups. These differences were significant for median LPRx (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.028), LPRx\u0026thinsp;\u0026gt;\u0026thinsp;0 (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.025), LPRx\u0026thinsp;\u0026gt;\u0026thinsp;0.2 (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.013), and LPRx\u0026thinsp;\u0026gt;\u0026thinsp;0.3 (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.017).\u003c/p\u003e\u003cp\u003e\u003cb\u003eTemporal Trends in LPRx and Their Associations with Mortality and Long-Term Functional Outcome\u003c/b\u003e\u003c/p\u003e\u003cp\u003eTo assess the temporal pattern of cerebral autoregulation in relation to outcomes, we compared daily median LPRx values between survivors and non-survivors, as well as between patients with favorable and unfavorable 6-month functional outcomes. Non-survivors consistently exhibited higher LPRx values across all seven days; however, none of these comparisons reached statistical significance. Mann\u0026ndash;Whitney U tests yielded p-values ranging from 0.090 on day 4 to 0.857 on day 7 (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ea).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eWhen stratified by functional outcomes, a similar trend of higher LPRx values was observed in the group with poor outcomes. Notably, statistically significant differences were identified on days 1 (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.031), 3 (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.019), and 4 (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.036), indicating that impaired cerebral autoregulation during the early post-injury period was more strongly associated with long-term neurological disability than with in-hospital mortality. These findings are visually summarized in the accompanying chart, which shows persistently higher median LPRx values in the poor outcome group (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eb).\u003c/p\u003e\u003cp\u003e\u003cb\u003eAssociation Between Decompressive Craniectomy and LPRx\u003c/b\u003e\u003c/p\u003e\u003cp\u003eTo evaluate the influence of decompressive craniectomy on cerebral autoregulation, the daily median LPRx values were compared between the patients who underwent craniectomy (Group 1) and those who did not (Group 0). Throughout the seven-day monitoring period, no statistically significant differences in LPRx were observed between the two groups on any day (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ec).\u003c/p\u003e\u003cp\u003e\u003cb\u003eAssociation Between ICP and LPRx\u003c/b\u003e\u003c/p\u003e\u003cp\u003eTo examine the relationship between ICP and cerebral autoregulation, median LPRx was plotted across ICP bins at 5 mm Hg intervals. The analysis revealed a U-shaped pattern with a nadir at approximately 10 mmHg, suggesting an optimal autoregulatory function near this pressure level. As ICP increased beyond 15 mmHg, LPRx progressively increased, indicating worsening cerebral autoregulation. This trend became especially pronounced at ICP levels\u0026thinsp;\u0026ge;\u0026thinsp;25 mmHg, where median PRx increased steeply, reflecting impaired cerebral autoregulation. These findings support the concept of pressure-dependent vulnerability of cerebral autoregulation, emphasizing the clinical relevance of maintaining ICP within an optimal range (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eAssociation Between Optimal CPP and LPRx\u003c/b\u003e\u003c/p\u003e\u003cp\u003eTo evaluate the relationship between CPPopt and cerebral autoregulation, the median LPRx was plotted across the CPPopt intervals. Unlike the U-shaped pattern observed for ICP, no consistent or statistically significant relationship was observed between CPPopt and LPRx (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). The median LPRx remained relatively stable across the CPPopt range of 50\u0026ndash;90 mmHg, with wider variability at the extremes. These findings suggest that within the studied range, CPPopt alone may not reliably predict autoregulatory function as indexed by LPRx, highlighting the complexity of individualized cerebral hemodynamics in TBI.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eEffect of Osmotic Therapy on Cerebral Autoregulation\u003c/b\u003e\u003c/p\u003e\u003cp\u003eTo evaluate the effect of mannitol treatment on cerebral autoregulation, a GEE model was applied using repeated LPRx measurements from 35 patients. Each treatment was administered as an individual visit, and the patients were observed across multiple time points using both pre- and post-infusion data. A total of 957 valid observations are included in the model. The estimated mean difference in LPRx between the pre- and post-mannitol phases was 0.004, which was not statistically significant (Wald χ\u0026sup2; = 0.074, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.786).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eAlthough PRx-based CPPopt has been proposed as a promising individualized target for TBI management, its clinical applicability remains limited. In this study, CPPopt could only be derived for 32% of the monitoring period, reflecting its limited availability in real-time clinical scenarios. This observation is consistent with prior reports, in which the yield of CPPopt generally ranged from 50 to 97%.\u003csup\u003e4,6,10\u0026ndash;13\u003c/sup\u003e Furthermore, the recent COGiTATE trial demonstrated that even under protocol-driven CPPopt-guided management, concordance between actual CPP and the individualized target (\u0026plusmn;\u0026thinsp;5 mmHg) was achieved only 46.5% of the time.\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e These findings underscore the dynamic nature of autoregulation and the challenge of aligning treatment goals with rapidly fluctuating physiological targets. Notably, in the trial, alerts for CPP deviation were generated only six times daily, a frequency that was likely insufficient to inform meaningful and responsive bedside interventions. A more recent approach has been proposed using the lower limit of reactivity derived from PRx trends to define the threshold below which autoregulation becomes impaired.\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e Although this strategy improved the feasibility and target availability, it provided only a range rather than a precise goal for the intervention. The need for continuous estimation and the inherent uncertainty in defining a single actionable CPP target further question the clinical utility of PRx-based optimization strategies in routine neurocritical care.\u003c/p\u003e\u003cp\u003eIn contrast to the intermittent and often sparse availability of CPPopt, PRx and its low-frequency (LPRx) can be computed continuously, typically at 1-minute intervals, enabling real-time tracking of cerebral autoregulation\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e. This low-frequency resolution enables clinicians to monitor trends in vascular reactivity over time and may offer a more responsive and practical tool in dynamic neurocritical care settings. Although LPRx has been widely studied for its prognostic relevance in TBI, the specific threshold that distinguishes favorable from unfavorable outcomes remains inconsistent across the literature. The reported cutoff values vary considerably and are likely influenced by differences in study design, timing of measurement, and patient populations.\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e,\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e,\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e,\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e,\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e Notably, in contrast to previous findings, we observed that both favorable and unfavorable outcome groups often exhibited median PRx values below the previously suggested thresholds (e.g., 0.2), calling into question the reliability of a universal prognostic cutoff value. These findings suggest that rather than a fixed numerical threshold, the overall trajectory and burden of impaired autoregulation may be more clinically informative. These considerations support the potential value of using PRx or LPRx as a dynamic and continuously available metric rather than CPPopt as a targetable surrogate in individualized TBI management.\u003c/p\u003e\u003cp\u003eConsistent with previous studies, our findings demonstrated that patients with favorable outcomes, both in terms of survival and neurological function, tended to exhibit lower LPRx values throughout the entire monitoring period. Although some of these differences were statistically significant, the overall trend supported the notion that preserved cerebral autoregulation is associated with better clinical outcomes. Furthermore, the burden of impaired autoregulation, reflected by the percentage of monitoring time spent above various LPRx thresholds (e.g., \u0026gt;\u0026thinsp;0, \u0026gt;0.2, and \u0026gt;\u0026thinsp;0.3), was greater in patients with poor functional outcomes and mortality. These observations suggest that the cumulative burden of autoregulatory failure, rather than isolated LPRx values, may be more predictive of patient trajectory. A similar concept has been discussed in recent ICP literature, where not only peak pressure values but also the duration and extent of intracranial hypertension (i.e., ICP dose) are associated with outcomes.\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e Moreover, PRx is increasingly recognized as a dynamic biomarker, and its prognostic utility varies over the clinical course. A recent study highlighted that the sensitivity of PRx for predicting poor outcomes peaked on hospital day six, after which it declined despite continued monitoring.\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e This temporal shift underscores that the interpretability and clinical relevance of PRx are not static but evolve over time. In our cohort, this time-sensitive pattern was similarly observed; early differences in the LPRx burden appeared more discriminative, suggesting a potential \"window of vulnerability\" during which autoregulatory failure may exert the greatest prognostic influence. These findings emphasize the importance of longitudinal PRx monitoring and support its role as a real-time physiological guide rather than a one-time measurement in neurocritical care decision making.\u003c/p\u003e\u003cp\u003eOur analysis of the relationship between ICP and LPRx revealed a distinct U-shaped curve, with the lowest LPRx observed at an ICP of approximately 10 mmHg. This suggests that cerebral autoregulation is mostly preserved at this pressure level. Using a threshold of PRx\u0026thinsp;\u0026gt;\u0026thinsp;0.2, which indicates impaired cerebral autoregulation, we found that ICP values below 25 mmHg were generally associated with more favorable LPRx values. This observation aligns well with current TBI guidelines, which recommend maintaining ICP below 22 mmHg. Given that elevated ICP is consistently associated with poor clinical outcomes, our findings reinforce this guideline and suggest that PRx may provide additional context by identifying when ICP falls within a range that supports intact autoregulation. More importantly, within this wide spectrum of \"acceptable\" ICP values, the critical question becomes not just how high ICP is but whether autoregulation is preserved at a given pressure in a specific clinical context. Thus, the ICP-derived PRx may offer a more nuanced and patient-specific perspective than ICP alone.\u003c/p\u003e\u003cp\u003eIn contrast, our evaluation of CPPopt derived from LPRx through pooled analysis across all patients and time points did not demonstrate a clear U-shaped relationship between CPPopt and LPRx. The absence of this expected parabolic pattern underscores the limitations of generalizing CPPopt targets across individuals and time frames. Although the theoretical CPPopt, at which LPRx is minimized, offers a compelling individualized treatment target, our data suggest that such a value cannot be consistently identified from pooled observations. This reinforces the notion that CPPopt is highly dynamic and context-specific and that population-level analyses may obscure the temporal and inter-individual variability inherent to autoregulatory functions. These findings further support the limitations of using CPPopt as a fixed or universally applicable target in clinical decision making.\u003c/p\u003e\u003cp\u003eAlthough the prognostic value of PRx in patients with TBI has been widely documented, its responsiveness to therapeutic interventions remains unexplored. In particular, whether PRx can be meaningfully modulated through clinical management has been a topic of debate. In this study, we evaluated the effects of two commonly employed interventions, decompressive craniectomy (DC) and osmotic therapy, on cerebral autoregulation, as indexed by LPRx. Interestingly, no significant association was found between the intervention and changes in LPRx across the monitoring course. This contrasts with an earlier report\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e in which PRx was observed to increase, suggesting impaired reactivity following DC treatment in the same cohort of patients. It is important to interpret these findings in this context. Their study focused on within-subject comparisons of PRx before and after surgery, a design that might not reflect the broader clinical question of whether DC contributes to the maintenance or restoration of autoregulatory function over time. In fact, as our between-group analysis suggests, patients who received DC may have avoided further deterioration of PRx had the procedure not been performed. Thus, although the derangement of PRx post-DC has been reported, such findings should not be interpreted as evidence of the intervention's overall benefit. Our results underscore the need to assess PRx trends in the context of natural disease progression and the potential counterfactual outcomes in untreated patients.\u003c/p\u003e\u003cp\u003eSimilarly, we found no significant differences in LPRx before and after osmotic therapy. This finding may reflect the temporally limited effect of osmotic agents such as mannitol, which are known to acutely lower ICP but may not influence long-term vascular reactivity. Additionally, prophylactic osmotic therapy has not consistently demonstrated improvements in clinical outcomes in previous trials, suggesting that its role may be more supportive than that of a transformative therapy. It is plausible that osmotic agents have other physiological effects, such as modulating blood viscosity or endothelial tone, which could influence autoregulation; however, such effects were not apparent in our analysis. These results indicate that, although both DC and osmotic therapy remain vital tools in ICP management, their direct impact on restoring cerebral autoregulation warrants further investigation in larger and more targeted studies.\u003c/p\u003e\u003cp\u003eThis study has some limitations. First, the relatively small sample size may have limited the statistical power to detect subtle effects. Second, although the use of LPRx enables continuous and practical bedside assessment, it may not capture the full temporal dynamics and sensitivity of high-frequency PRx signals. Third, as a retrospective analysis with potential variability in treatment protocols, the timing of interventions, and patient-specific factors, all of which could influence cerebral autoregulation and confound the observed associations. Lastly, while efforts have been made to evaluate the effect of therapeutic interventions such as decompressive craniectomy and osmotic therapy, the complexity of autoregulatory physiology means that other unmeasured factors may have contributed to the observed patterns.\u003c/p\u003e\u003cp\u003eDespite these limitations, our findings provide valuable insights into the application and interpretation of PRx-based monitoring for the clinical management of TBI. We demonstrated that impaired cerebral autoregulation, as indexed by LPRx, was associated with poor outcomes not only in terms of absolute values but also in relation to the duration of autoregulatory dysfunction. Although CPPopt remains a theoretically appealing individualized target for TBI, its low availability and variability limit its practicality in real-world settings. In contrast, LPRx offers a continuous, real-time measure of autoregulation and may serve as a reliable guide for individualized care. The lack of measurable improvement in LPRx following decompressive craniectomy or osmotic therapy further highlights the complexity of cerebral hemodynamics and underscores the need for more nuanced strategies to preserve or restore autoregulatory function. Future prospective studies with larger cohorts and multimodal monitoring are warranted to refine the clinical use of LPRx and to explore its potential role as a prognostic biomarker and modifiable therapeutic target.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eImpaired cerebral autoregulation, as reflected by elevated LPRx and a prolonged burden above the threshold, is associated with unfavorable outcomes in patients with TBI. Although CPPopt remains conceptually attractive, its low availability and variability limit its clinical utility. Further investigation is warranted to better understand how conventional therapies influence autoregulatory functions and whether LPRx can eventually serve as a therapeutic target in personalized TBI management.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eCompliance with Journal Instructions:\u003c/strong\u003e We confirm that the submitted manuscript complies with all the instructions to authors for the Neurocritical Care. This includes adherence to ethical standards, conflict of interest disclosures, formatting guidelines, word count limitations, figure and table requirements, and reference formatting. We have reviewed and followed all journal policies regarding manuscript preparation, submission requirements, and have ensured all authors approve the submission of this manuscript\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions:\u003c/strong\u003e Ue-Cheung Ho: Conceptualization (Equal); Data curation (Lead); Formal analysis (Lead); Methodology (Supporting); Writing – original draft (Lead). Nathan Wei: Conceptualization (Equal); Data curation (Supporting); Formal analysis (Supporting). Lu-Ting Kuo: Conceptualization (Lead); Methodology (Lead); Resources (Lead); Supervision (Lead); Writing – original draft (Supporting); Writing – review \u0026amp; editing (Lead)\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthorship Confirmation Statement:\u0026nbsp;\u003c/strong\u003eWe confirm that all authors meet the authorship requirements as outlined by Neurocritical Care. All authors agree to be accountable for all aspects of the work, ensuring the accuracy and integrity of the research.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eExclusive Submission Confirmation:\u003c/strong\u003e We confirm that this manuscript has not been published elsewhere and is not currently under consideration by another journal. This submission is original and has not been previously disseminated in any form, ensuring its exclusive consideration by Neurocritical Care.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical Statement:\u003c/strong\u003e This study was performed in compliance with local regulations, adhered to the Declaration of Helsinki, and was approved by the institutional review board of the institution of National Taiwan University Hospital (IRB number: 202408094RINE).\u0026nbsp;All patients provided general consent upon admission for the use of their anonymized medical data for academic purposes.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflicts of Interest:\u0026nbsp;\u003c/strong\u003eThe authors declare that they have no conflicts of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eUse of EQUATOR Checklist:\u003c/strong\u003e This manuscript was prepared following the STrengthening the Reporting of OBservational studies in Epidemiology (STROBE) statement.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u003c/strong\u003e We declare that we have no sources of funding.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments:\u0026nbsp;\u003c/strong\u003eWe would like to thank Editage (www.editage.com) for English language editing and journal submission support.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability:\u0026nbsp;\u003c/strong\u003eThe datasets generated during and/or analyzed during the current study are available from the corresponding author upon reasonable request.\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eCarney N, Totten AM, O\u0026rsquo;Reilly C, et al. 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Crit Care Med. 2002;30:733\u0026ndash;8. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1097/00003246-200204000-00002\u003c/span\u003e\u003cspan address=\"10.1097/00003246-200204000-00002\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAries MJH, Czosnyka M, Budohoski KP, et al. Continuous determination of optimal cerebral perfusion pressure in traumatic brain injury. Crit Care Med. 2012;40:2456\u0026ndash;63. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1097/CCM.0b013e3182514eb6\u003c/span\u003e\u003cspan address=\"10.1097/CCM.0b013e3182514eb6\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eTas J, Beqiri E, van Kaam RC, et al. 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Pressure reactivity index for early neuroprognostication in poor-grade subarachnoid hemorrhage. J Neurol Sci. 2023;450:120691. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.jns.2023.120691\u003c/span\u003e\u003cspan address=\"10.1016/j.jns.2023.120691\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZoerle T, Beqiri E, \u0026Aring;kerlund CAI, et al. Intracranial pressure monitoring in adult patients with traumatic brain injury: challenges and innovations. Lancet Neurol. 2024;23:938\u0026ndash;50. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/S1474-4422(24)00235-7\u003c/span\u003e\u003cspan address=\"10.1016/S1474-4422(24)00235-7\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eChang JJ, Kepplinger D, Metter EJ, et al. Time thresholds for using pressure reactivity index in neuroprognostication for patients with severe traumatic brain injury. Neurosurgery. 2024;95:297\u0026ndash;304. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1227/neu.0000000000002876\u003c/span\u003e\u003cspan address=\"10.1227/neu.0000000000002876\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eTimofeev I, Czosnyka M, Nortje J, et al. Effect of decompressive craniectomy on intracranial pressure and cerebrospinal compensation following traumatic brain injury. J Neurosurg. 2008;108:66\u0026ndash;73. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3171/JNS/2008/108/01/0066\u003c/span\u003e\u003cspan address=\"10.3171/JNS/2008/108/01/0066\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Traumatic Brain Injury, Pressure Reactivity Index, Cerebral Autoregulation, Decompressive Craniectomy, Osmotic Therapy","lastPublishedDoi":"10.21203/rs.3.rs-7029976/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7029976/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground/Objective\u003c/strong\u003e: Cerebral autoregulation is a critical determinant of traumatic brain injury (TBI) outcomes. Low-frequency pressure reactivity index (LPRx), from routine monitoring, dynamically assesses autoregulation; impairment (elevated LPRx) is linked to poor outcomes. However, the impact of clinical interventions on LPRx and LPRx-derived optimal CPP (CPPopt) utility are unclear. This study evaluated LPRx's prognostic value and therapeutic modifiability in TBI patients, examining its dynamics related to 6-month clinical outcomes (survival, Glasgow Outcome Scale Extended [GOSE]) and common neurocritical care interventions.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e: We conducted a retrospective analysis of 35 moderate-to-severe TBI patients undergoing neurosurgery and intensive care unit (ICU) monitoring with minute-by-minute recordings at two Taiwanese university hospitals (2022-2024). LPRx (moving Pearson correlation of 1-minute averaged arterial blood pressure/ICP) and CPPopt (nadir of LPRx-CPP curve) were calculated. Patients were stratified by 6-month survival and GOSE (favorable: GOSE 5–8; unfavorable: GOSE 1–4). LPRx relationships with outcomes, ICP, CPPopt, decompressive craniectomy, and mannitol were analyzed using non-parametric tests and generalized estimating equations (GEE).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e: Among 35 patients (26 survivors, 8 favorable outcomes), significantly higher median LPRx and a greater proportion of time with LPRx \u0026gt; thresholds (e.g., \u0026gt;0.2, p=0.013) correlated with unfavorable outcomes. Early impaired LPRx (days 1, 3, 4) was associated with unfavorable function. LPRx showed a U-shaped ICP relationship (nadir ~10 mmHg). CPPopt was derivable in only 32% of monitoring time, with no consistent LPRx relationship. Decompressive craniectomy and mannitol did not significantly alter LPRx (mannitol GEE: p=0.786).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion\u003c/strong\u003e: Impaired cerebral autoregulation (elevated LPRx) is associated with poor TBI outcomes. While CPPopt is an attractive theoretical target, its limited feasibility and inconsistent physiological correlation pose challenges to its clinical utility. LPRx offers a continuous, practical measure; however, its responsiveness to conventional therapies remains uncertain, warranting further investigation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRegistration\u003c/strong\u003e: The study design was not preregistered.\u003c/p\u003e","manuscriptTitle":"Evaluation of the Prognostic Value and Modifiability of Low-Frequency Pressure Reactivity Index in Patients with Traumatic Brain Injury","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-14 11:51:55","doi":"10.21203/rs.3.rs-7029976/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"008c4bd4-040b-4c69-b968-bc31863e0c3a","owner":[],"postedDate":"July 14th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-07-21T19:19:56+00:00","versionOfRecord":[],"versionCreatedAt":"2025-07-14 11:51:55","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7029976","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7029976","identity":"rs-7029976","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}