Transcranial Doppler Combined With Quantitative Electroencephalography Brain Function Monitoring for Estimating the Prognosis of Patients With Posterior Circulation Cerebral Infarction

Posterior circulation cerebral infarction (PCCI) can lead to deceased infratentorial cerebral blood flow (CBF) and metabolism. Neural activity is closely related to regional cerebral blood flow both spatially and temporally. Transcranial Doppler (TCD) combined with quantitative electroencephalography (QEEG) is a technique that evaluates neurovascular coupling and involves synergy between the metabolic and vascular systems. This study aimed to monitor brain function using TCD-QEEG and estimate the efficacy of TCD-QEEG for predicting the prognosis of patients with PCCI. We used a TCD-QEEG recording system to perform quantitative brain function monitoring; we recorded the related clinical variables simultaneously. The data were analyzed using a Cox proportional hazards regression model. Receiver-operating characteristic (ROC) curve analysis was used to evaluate the cut-off for the diastolic flow velocity (VD) and (delta + theta)/(alpha + beta) ratio (DTABR). The area under the ROC curve (AUROC) was calculated to assess the predictive validity of the study variables. Forty patients (aged 63.7 ± 9.9 years; 30 men) were assessed. Mortality at 90 days was 40%. The TCD indicators of VD [hazard ratio (HR) 0.168, confidence interval (CI) 0.047–0.597, p = 0.006] and QEEG indicators of DTABR (HR 12.527, CI 1.637–95.846, p = 0.015) were the independent predictors of the clinical outcomes. The AUROC after combination of VD and DTABR was 0.896 and showed better predictive accuracy than the Glasgow Coma Scale score (0.75), VD (0.76), and DTABR (0.781; all p < 0.05). TCD-QEEG provides a good understanding of the coupling mechanisms in the brain and can improve our ability to predict the prognosis of patients with PCCI.

Simultaneous comparison of depth of sedation performance between SedLine and BIS during general anesthesia using custom passive interface hardware: study protocol for a prospective, non-blinded, non-randomized trial

Background Intraoperative brain function monitoring with processed electroencephalogram (EEG) indices, such as the bispectral index (BIS) and patient state index (PSI), may improve characterization of the depth of sedation or anesthesia when compared to conventional physiologic monitors, such as heart rate and blood pressure. However, the clinical assessment of anesthetic depth may not always agree with available processed EEG indices. To concurrently compare the performance of BIS and SedLine monitors, we present a data collection system using shared individual generic sensors connected to a custom-built passive interface box. Methods This prospective, non-blinded, non-randomized study will enroll 100 adult American Society of Anesthesiologists (ASA) class I-III patients presenting for elective procedures requiring general anesthesia. BIS and SedLine electrodes will be placed preoperatively according to manufacturer recommendations and their respective indices tracked throughout anesthesia induction, maintenance and emergence. The concordance between processed EEG indices and clinical assessments of anesthesia depth will be analyzed with chi-square and kappa statistic. Discussion Prior studies comparing brain function monitoring devices have applied both sensors on the forehead of study subjects simultaneously. With limited space and common sensor locations between devices, it is not possible to place both commercial sensor arrays according to the manufacturer’s recommendations, thus compromising the validity of these comparisons. This trial utilizes a custom interface allowing signals from sensors to be shared between BIS and SedLine monitors to provide an accurate comparison. Our results will also characterize the degree of agreement between processed EEG indices and clinical assessments of anesthetic depth as determined by the anesthesiologists’ interpretations of acute changes in blood pressure and heart rate as well as the administration, or change to the continuous delivery, of medications at these timepoints. Patient factors (such as burst suppression state or low power EEG conditions from aging brain), surgical conditions (such as use of electrocautery), artifacts (such as electromyography), and anesthesia medications and doses (such as end-tidal concentration of volatile anesthetic or hypnotic infusion dose) that lead to lack of agreement will be explored as well. Trial registration Clinical Trials (ClinicalTrials.gov), NCT03865316. Registered on 4 February 2019 – retrospectively registered. Sponsor: Masimo Corporation.

Transcranial Doppler combined with quantitative electroencephalography brain function monitoring for estimating the prognosis of patients with posterior circulation cerebral infarction

Background: Posterior circulation cerebral infarction (PCCI) leads to decreased cerebral blood flow (CBF) and metabolism. Neural activity is closely related to regional CBF both spatially and temporally. Transcranial Doppler (TCD) combined with quantitative electroencephalography (QEEG) can evaluate neurovascular coupling and involves synergy between the metabolic and vascular systems. This study aimed to monitor brain function using TCD-QEEG and estimate its efficacy in predicting the prognosis of patients with PCCI.Methods: We used TCD-QEEG to perform quantitative brain function monitoring; we recorded the related clinical variables simultaneously. The data were analyzed using a Cox proportional hazards regression model. Receiver-operating characteristic (ROC) curve analysis was used to evaluate the cut-off for the diastolic flow velocity (VD) and (delta+theta)/(alpha+beta) ratio (DTABR). The area under the ROC curve (AUROC) was calculated to assess the predictive validity of the study variables. Results: Forty patients (aged 63.7±9.9 years; 30 men) were assessed. Mortality at 90 days was 40%. The TCD indicators of VD (hazards ratio [HR] 0.168, confidence interval [CI] 0.047–0.597, p=0.006), and QEEG indicators of DTABR (HR 12.527, CI 1.637–95.846, p=0.015) were the independent predictors of the clinical outcomes. The AUROC after the combination of VD and DTABR was 0.896 and showed better predictive accuracy than the Glasgow Coma Scale score (0.75), VD (0.76), and DTABR (0.781; all p<0.05).Conclusion: TCD-QEEG provides a good understanding of the coupling mechanisms in the brain and can improve our ability to predict the prognosis of patients with PCCI.