Impaired cerebral autoregulation detected in early prevasospasm period is associated with unfavorable outcome after spontaneous subarachnoid hemorrhage: an observational prospective pilot study.

BACKGROUND: Subarachnoid hemorrhage (SAH) patients with cerebral autoregulation (CA) impairment at an early post-SAH period are at high risk of unfavorable outcomes due to delayed cerebral ischemia (DCI) or other complications. Limited evidence exists for an association between early-stage CA impairments and SAH patient outcomes. The objective of this prospective study was to explore associations between CA impairments detected in early post-SAH snapshot examinations and patient outcomes. METHODS: The pilot observational study included 29 SAH patients whose CA status was estimated 2-3 days after spontaneous aneurysm rupture and a control group of 15 healthy volunteers for comparison. Inflatable leg recovery boots (reboots.com, Germany) were used for the safe controlled generation of arterial blood pressure (ABP) changes necessary for reliable CA examination. At least 5 inflation‒deflation cycles of leg recovery boots with a 2-3 min period were used during examinations. CA status was assessed according to the delay time (∆TCBFV) measured between ABP(t) and cerebral blood flow velocity (CBFV(t)) signals during artificially induced ABP changes at boot deflation cycle. CBFV was measured in middle cerebral artery by using transcranial Doppler device. RESULTS: Statistically significant differences in ∆TCBFV were found between SAH patients with unfavorable outcomes (∆TCBFV = 1.37 ± 1.23 s) and those with favorable outcomes (∆TCBFV = 2.86 ± 0.99 s) (p < 0.001). Early assessment of baroreflex sensitivity (BRS) during the deflation cycle showed statistically significant differences between the DCI and non-DCI patient groups (p = 0.039). CONCLUSIONS: A relatively small delay of ∆TCBFV <1.6 s between CBFV(t) and ABP(t) waves could be an early warning sign associated with unfavorable outcomes in SAH patients. The BRS during boot deflation can be used as a biomarker for the prediction of DCI. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT06028906. Registered 31 August 2023 - Retrospectively registered, https://www. CLINICALTRIALS: gov/study/NCT06028906 .

Feasibility of the optimal cerebral perfusion pressure value identification without a delay that is too long.

Optimal cerebral perfusion pressure (CPPopt)-targeted treatment of traumatic brain injury (TBI) patients requires 2-8 h multi-modal monitoring data accumulation to identify CPPopt value for individual patient. Minimizing the time required for monitoring data accumulation is needed to improve the efficacy of CPPopt-targeted therapy. A retrospective analysis of multimodal physiological monitoring data from 87 severe TBI patients was performed by separately representing cerebrovascular autoregulation (CA) indices in relation to CPP, arterial blood pressure (ABP), and intracranial pressure (ICP) to improve the existing CPPopt identification algorithms. Machine learning (ML)-based algorithms were developed for automatic identification of informative data segments that were used for reliable CPPopt, ABPopt, ICPopt and the lower/upper limits of CA (LLCA/ULCA) identification. The reference datasets of the informative data segments and, artifact-distorted segments, and the datasets of different clinical situations were used for training the ML-based algorithms, allowing us to choose the appropriate individualized CPP-, ABP- or ICP-guided management for 79% of the full monitoring time for the studied population. The developed ML-based algorithms allow us to recognize informative physiological ABP/ICP variations within 24 min intervals with an accuracy up to 79% (compared to the initial accuracy of 74%) and use these segments for timely optimal value identification or CA limits determination in CPP, ABP or ICP data. Prospective clinical studies are needed to prove the efficiency of the developed algorithms.

Optimal Cerebral Perfusion Pressure: Targeted Treatment for Severe Traumatic Brain Injury.

Identification of individual therapy targets is critical for traumatic brain injury (TBI) patients. Clinical outcomes depend on cerebrovascular autoregulation (CA) impairment. Here, we compare the effectiveness of optimal cerebral perfusion pressure (CPPopt)-targeted therapy in younger (<45 years of age) and elderly (≥45 years of age) TBI patients. Single-center multi-modal invasive arterial blood pressure(t), intracranial pressure (ICP)(t), cerebral perfusion pressure CPP(t), and CPPopt(t) monitoring (n = 81) was performed. ICM+ software was used for continuous CPPopt(t) status assessment by identification of pressure reactivity index (PRx). The most significant prognostic factors were age, Glasgow Coma Scale, serum glucose, and duration of longest CA ompairment event (LCAI) when PRx(t) >0.5 within 24 h after admission. The modeled accuracies for favorable and unfavorable outcome prediction were 86.5% and 90.9%, respectively. Age above 45 years and averaged ICP during all monitoring time above 21.3 mm Hg was associated with unfavorable outcome of an individual patient. Averaged CPP values close to CPPopt were associated with a better outcome in younger patients. Averaged ΔCPPopt <-5.0 mm Hg, averaged PRx >0.36, and LCAI >100 min were significantly associated with mortality for the younger patients. The critical values of averaged PRx >0.26 and LCAI >61 min were significantly associated with mortality for the elderly group. Autoregulation-guided treatment was important for individual TBI management, especially in younger patients. Further randomized multi-center studies are needed to prove final benefit.