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Quantification of EEG reactivity in comatose patients.

ABSTRACT: EEG reactivity is an important predictor of outcome in comatose patients. However, visual analysis of reactivity is prone to subjectivity and may benefit from quantitative approaches.In EEG segments recorded during reactivity testing in 59 comatose patients, 13 quantitative EEG parameters were used to compare the spectral characteristics of 1-minute segments before and after the onset of stimulation (spectral temporal symmetry). Reactivity was quantified with probability values estimated using combinations of these parameters. The accuracy of probability values as a reactivity classifier was evaluated against the consensus assessment of three expert clinical electroencephalographers using visual analysis.The binary classifier assessing spectral temporal symmetry in four frequency bands (delta, theta, alpha and beta) showed best accuracy (Median AUC: 0.95) and was accompanied by substantial agreement with the individual opinion of experts (Gwet's AC1: 65-70%), at least as good as inter-expert agreement (AC1: 55%). Probability values also reflected the degree of reactivity, as measured by the inter-experts' agreement regarding reactivity for each individual case.Automated quantitative EEG approaches based on probabilistic description of spectral temporal symmetry reliably quantify EEG reactivity.Quantitative EEG may be useful for evaluating reactivity in comatose patients, offering increased objectivity.

SUBMITTER: Hermans MC

PROVIDER: S-EPMC4885124 | biostudies-literature | 2016 Jan

REPOSITORIES: biostudies-literature

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Quantification of EEG reactivity in comatose patients.

Hermans Mathilde C MC Westover M Brandon MB van Putten Michel J A M MJAM Hirsch Lawrence J LJ Gaspard Nicolas N

Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology 20150702 1

<h4>Objective</h4>EEG reactivity is an important predictor of outcome in comatose patients. However, visual analysis of reactivity is prone to subjectivity and may benefit from quantitative approaches.<h4>Methods</h4>In EEG segments recorded during reactivity testing in 59 comatose patients, 13 quantitative EEG parameters were used to compare the spectral characteristics of 1-minute segments before and after the onset of stimulation (spectral temporal symmetry). Reactivity was quantified with pr ...[more]

PMID: 26183757

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Project description:Background We assessed the prognostic accuracy of the standardized electroencephalography (EEG) patterns (“highly malignant,” “malignant,” and “benign”) according to the EEG timing (early vs. late) and investigated the EEG features to enhance the predictive power for poor neurologic outcome at 1 month after cardiac arrest. Methods This prospective, multicenter, observational, cohort study using data from Korean Hypothermia Network prospective registry included adult patients with out-of-hospital cardiac arrest (OHCA) treated with targeted temperature management (TTM) and underwent standard EEG within 7 days after cardiac arrest from 14 university-affiliated teaching hospitals in South Korea between October 2015 and December 2018. Early EEG was defined as EEG performed within 72 h after cardiac arrest. The primary outcome was poor neurological outcome (Cerebral Performance Category score 3–5) at 1 month. Results Among 489 comatose OHCA survivors with a median EEG time of 46.6 h, the “highly malignant” pattern (40.7%) was most prevalent, followed by the “benign” (33.9%) and “malignant” (25.4%) patterns. All patients with the highly malignant EEG pattern had poor neurologic outcomes, with 100% specificity in both groups but 59.3% and 56.1% sensitivity in the early and late EEG groups, respectively. However, for patients with “malignant” patterns, 84.8% sensitivity, 77.0% specificity, and 89.5% positive predictive value for poor neurologic outcome were observed. Only 3.5% (9/256) of patients with background EEG frequency of predominant delta waves or undetermined had good neurologic survival. The combination of “highly malignant” or “malignant” EEG pattern with background frequency of delta waves or undetermined increased specificity and positive predictive value, respectively, to up to 98.0% and 98.7%. Conclusions The “highly malignant” patterns predicted poor neurologic outcome with a high specificity regardless of EEG measurement time. The assessment of predominant background frequency in addition to EEG patterns can increase the prognostic value of OHCA survivors. Trial registration KORHN-PRO, NCT02827422. Registered 11 September 2016—Retrospectively registered. Supplementary Information The online version contains supplementary material available at 10.1186/s13054-021-03823-y.

Project description:OBJECTIVES:Impaired cerebral autoregulation following neurologic injury is a predictor of poor clinical outcome. We aimed to assess the relationship between body temperature and cerebral autoregulation in comatose patients. DESIGN:Retrospective analysis of prospectively collected data. SETTING:Neurocritical care unit of the Johns Hopkins Hospital. PATIENTS:Eighty-five acutely comatose patients (Glasgow Coma Scale score of ? 8) admitted between 2013 and 2017. INTERVENTIONS:None. MEASUREMENT AND MAIN RESULTS:Cerebral autoregulation was monitored using multimodal monitoring with near-infrared spectroscopy-derived cerebral oximetry index. Cerebral oximetry index was calculated as a Pearson correlation coefficient between low-frequency changes in regional cerebral oxygenation saturation and mean arterial pressure. Patients were initially analyzed together, then stratified by temperature pattern over the monitoring period: no change (< 1°C difference between highest and lowest temperatures; n = 11), increasing (? 1°C; n = 9), decreasing (? 1°C; n = 9), and fluctuating (? 1°C difference but no sustained direction of change; n = 56). Mixed random effects models with random intercept and multivariable logistic regression analysis were used to assess the association between hourly temperature and cerebral oximetry index, as well as between temperature and clinical outcomes. Cerebral oximetry index showed a positive linear relationship with temperature (? = 0.04?±?0.10; p = 0.29). In patients where a continual increase or decrease in temperature was seen during the monitoring period, every 1°C change in temperature resulted in a cerebral oximetry index change in the same direction by 0.04?±?0.01 (p < 0.001) and 0.02?±?0.01 (p = 0.12), respectively, after adjusting for PaCO2, hemoglobin, mean arterial pressure, vasopressor and sedation use, and temperature probe location. There was no significant difference in mortality or poor outcome (modified Rankin Scale score of 4-6) between temperature pattern groups at discharge, 3, or 6 months. CONCLUSIONS:In acute coma patients, increasing body temperature is associated with worsening cerebral autoregulation as measured by cerebral oximetry index. More studies are needed to clarify the impact of increasing temperature on cerebral autoregulation in patients with acute brain injury.

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Quantification of EEG reactivity in comatose patients.

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Quantification of EEG reactivity in comatose patients.

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