Quantitative EEG Parameters for Prediction of Outcome in Severe Traumatic Brain Injury: Development Study

2017 ◽  
Vol 49 (4) ◽  
pp. 248-257 ◽  
Author(s):  
Antti Tolonen ◽  
Mika O. K. Särkelä ◽  
Riikka S. K. Takala ◽  
Ari Katila ◽  
Janek Frantzén ◽  
...  
Keyword(s):  
Traumatic Brain Injury ◽  
Brain Injury ◽  
Prognostic Value ◽  
Outcome Prediction ◽  
Characteristic Curve ◽  
Quantitative Eeg ◽  
University Hospital ◽  
Alpha Power ◽  
Continuous Eeg ◽  
Severe Tbi

Monitoring of quantitative EEG (QEEG) parameters in the intensive care unit (ICU) can aid in the treatment of traumatic brain injury (TBI) patients by complementing visual EEG review done by an expert. We performed an explorative study investigating the prognostic value of 59 QEEG parameters in predicting the outcome of patients with severe TBI. Continuous EEG recordings were done on 28 patients with severe TBI in the ICU of Turku University Hospital. We computed a set of QEEG parameters for each patient, and correlated these to patient outcome, measured by dichotomized Glasgow Outcome Scale (GOS) at a follow-up visit between 6 and 12 months, using area under receiver operating characteristic curve (AUC) as a nonlinear correlation measure. For 17 of the 59 QEEG parameters (28.8%), the AUC differed significantly from 0.5, most of these parameters measured EEG power or variability. The best QEEG parameters for outcome prediction were alpha power (AUC = 0.87, P < .01) and variability of the relative fast theta power (AUC = 0.84, P < .01). The results of this study indicate that QEEG parameters provide useful information for predicting outcome in severe TBI. Novel QEEG parameters with potential in outcome prediction were found, the prognostic value of these parameters should be confirmed in later studies. The results also provide further evidence of the usefulness of parameters studied in preexisting studies.

scholarly journals Predicting outcome in patients with moderate to severe traumatic brain injury using electroencephalography

Critical Care ◽  
2019 ◽  
Vol 23 (1) ◽  
Author(s):  
Marjolein E. Haveman ◽  
Michel J. A. M. Van Putten ◽  
Harold W. Hom ◽  
Carin J. Eertman-Meyer ◽  
Albertus Beishuizen ◽  
...  
Keyword(s):  
Traumatic Brain Injury ◽  
Brain Injury ◽  
Random Forest ◽  
Outcome Prediction ◽  
Training Set ◽  
Arterial Blood ◽  
Continuous Eeg ◽  
Severe Tbi ◽  
Validation Set ◽  
The Impact

Abstract Background Better outcome prediction could assist in reliable quantification and classification of traumatic brain injury (TBI) severity to support clinical decision-making. We developed a multifactorial model combining quantitative electroencephalography (qEEG) measurements and clinically relevant parameters as proof of concept for outcome prediction of patients with moderate to severe TBI. Methods Continuous EEG measurements were performed during the first 7 days of ICU admission. Patient outcome at 12 months was dichotomized based on the Extended Glasgow Outcome Score (GOSE) as poor (GOSE 1–2) or good (GOSE 3–8). Twenty-three qEEG features were extracted. Prediction models were created using a Random Forest classifier based on qEEG features, age, and mean arterial blood pressure (MAP) at 24, 48, 72, and 96 h after TBI and combinations of two time intervals. After optimization of the models, we added parameters from the International Mission for Prognosis And Clinical Trial Design (IMPACT) predictor, existing of clinical, CT, and laboratory parameters at admission. Furthermore, we compared our best models to the online IMPACT predictor. Results Fifty-seven patients with moderate to severe TBI were included and divided into a training set (n = 38) and a validation set (n = 19). Our best model included eight qEEG parameters and MAP at 72 and 96 h after TBI, age, and nine other IMPACT parameters. This model had high predictive ability for poor outcome on both the training set using leave-one-out (area under the receiver operating characteristic curve (AUC) = 0.94, specificity 100%, sensitivity 75%) and validation set (AUC = 0.81, specificity 75%, sensitivity 100%). The IMPACT predictor independently predicted both groups with an AUC of 0.74 (specificity 81%, sensitivity 65%) and 0.84 (sensitivity 88%, specificity 73%), respectively. Conclusions Our study shows the potential of multifactorial Random Forest models using qEEG parameters to predict outcome in patients with moderate to severe TBI.

Early and persistent impaired percent alpha variability on continuous electroencephalography monitoring as predictive of poor outcome after traumatic brain injury

2002 ◽  
Vol 97 (1) ◽  
pp. 84-92 ◽  
Author(s):  
Paul M. Vespa ◽  
W. John Boscardin ◽  
David A. Hovda ◽  
David L. McArthur ◽  
Marc R. Nuwer ◽  
...  
Keyword(s):  
Traumatic Brain Injury ◽  
Brain Injury ◽  
Eeg Monitoring ◽  
Content Type ◽  
Poor Outcome ◽  
Continuous Electroencephalography ◽  
Continuous Eeg ◽  
Continuous Eeg Monitoring ◽  
Severe Tbi ◽  
Fine Print

Object. Early prediction of outcomes in patients after they suffer traumatic brain injury (TBI) is often nonspecific and based on initial imaging and clinical findings alone, without direct physiological testing. Improved outcome prediction is desirable for ethical, social, and financial reasons. The goal of this study was to determine the usefulness of continuous electroencephalography (EEG) monitoring in determining prognosis early after TBI, while the patient is in the intensive care unit. Methods. The authors hypothesized that the reduced percentage of alpha variability (PAV) in continuous EEG tracings indicates a poor prognosis. Prospective continuous EEG monitoring was performed in 89 consecutive patients with moderate to severe TBI (Glasgow Coma Scale [GCS] Scores 3–12) from 0 to 10 days after injury. The PAV was calculated daily, and the time course and trends of the PAV were analyzed in comparison with the patient's Glasgow Outcome Scale (GOS) score at the time of discharge. In patients with GCS scores of 8 or lower, a PAV value of 0.1 or lower is highly predictive of a poor outcome or death (positive predictive value 86%). The determinant PAV value was obtained by Day 3 after injury. Persistent PAV values of 0.1 or lower over several days or worsening of the PAV to a value of 0.1 or lower indicated a high likelihood of poor outcome (GOS Scores 1 and 2). In comparison with the combination of traditional initial clinical indicators of outcome (GCS score, pupillary response to light, patient age, results of computerized tomography scanning, and early hypotension or hypoxemia), the early PAV value during the initial 3 days after injury independently improved prognostic ability (p < 0.01). Conclusions. Continuous EEG monitoring performed with particular attention paid to the PAV is a sensitive and specific method of prognosis that can indicate outcomes in patients with moderate to severe TBI within 3 days postinjury.

scholarly journals 187 Early Post-Traumatic Seizures are Associated with Valproic Acid Plasma Concentrations and UGT1A6/CYP2C9 Genetic Polymorphisms in Patients with Severe Traumatic Brain Injury

Neurosurgery ◽  
2017 ◽  
Vol 64 (CN_suppl_1) ◽  
pp. 249-250
Author(s):  
Yirui Sun ◽  
Jian Yu ◽  
Qiang Yuan ◽  
Jin Hu
Keyword(s):  
Traumatic Brain Injury ◽  
Valproic Acid ◽  
Brain Injury ◽  
Genetic Polymorphisms ◽  
Severe Traumatic Brain Injury ◽  
Plasma Concentrations ◽  
Eeg Monitoring ◽  
Continuous Eeg ◽  
Severe Tbi ◽  
Post Traumatic

Abstract INTRODUCTION Seizure is a common complication for severe traumatic brain injury (TBI). Valproic acid (VPA) is a first-line antiepileptic drug, though its metabolism is affected by genetic polymorphisms and varies between individuals. The aim of this study was to investigate such association and to explore its influence on the occurrence of early post-traumatic seizure. METHODS A case control study was conducted from 2012 to 2016 recruiting adult patients with severe TBI. Continuous electroencephalograph (EEG) monitoring was performed for 7 days. Genetic polymorphisms in UGT1A6, UGT2B7, CYP2C9, and CYP2C19 were analyzed in association with daily VPA plasma concentrations, adjusted dosages, and occurrence seizures. RESULTS >Among the 395 recruited patients, eight-three (21%) had early post-traumatic seizure, of which 30 (36.14%) were non-convulsive. Most seizures were first detected on day 1 (34.94%) and day 2 (46.99%) after injury. Patients with seizure had longer ICU length of stay and relatively lower VPA plasma concentrations. Patients with UGT1A6_19T>G/541A>G/552A>C double heterozygosities or CYP2C9 extensive metabolizers (EMs) initially had lower adjusted VPA plasma concentrations (power >0.99) and accordingly require higher VPA dosages during later time of treatment (power >0.99). The odds ratio indicated a higher risk of early post-traumatic seizure occurrence in male patients (OR 1.96, 95% CI 1.01-3.81, P = 0.043), age over 65 (OR 2.13, 95% CI 1.01-4.48), and with UGT1A6_19T>G/541A>G/552A>C double heterozygosities (OR 2.38, 95% CI 1.11-5.10, P = 0.02). CONCLUSION Continuous EEG monitoring are necessary to detect both convulsive and non-convulsive early post-traumatic seizures in severe TBI patients. UGT1A6/CYP2C9 polymorphisms have influence on VPA metabolism. UGT1A6_19T>G/541A>G/552A>C double heterozygositie is associated with occurrence of early post-traumatic seizures in addition to patients' age and gender. Further investigations with larger sample size are required to confirm the difference.

scholarly journals External validation of the rotterdam computed tomography score in the prediction of mortality in severe traumatic brain injury

2017 ◽  
Vol 08 (S 01) ◽  
pp. S023-S026 ◽  
Author(s):  
Jose D. Charry ◽  
Jesus D. Falla ◽  
Juan D. Ochoa ◽  
Miguel A. Pinzón ◽  
Jorman H. Tejada ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Traumatic Brain Injury ◽  
Brain Injury ◽  
Injury Severity ◽  
External Validation ◽  
Public Health Problem ◽  
University Hospital ◽  
Prognostic Models ◽  
Prediction Of Mortality ◽  
Severe Tbi

ABSTRACT Introduction: Traumatic brain injury (TBI) is a public health problem. It is a pathology that causes significant mortality and disability in Colombia. Different calculators and prognostic models have been developed to predict the neurological outcomes of these patients. The Rotterdam computed tomography (CT) score was developed for prognostic purposes in TBI. We aimed to examine the accuracy of the prognostic discrimination and prediction of mortality of the Rotterdam CT score in a cohort of trauma patients with severe TBI in a university hospital in Colombia. Materials and Methods: We analyzed 127 patients with severe TBI treated in a regional trauma center in Colombia over a 2-year period. Bivariate and multivariate analyses were used. The discriminatory power of the score, its accuracy, and precision were assessed by logistic regression and as the area under the receiver operating characteristic curve. Shapiro–Wilk, Chi-square, and Wilcoxon tests were used to compare the real outcomes in the cohort against the predicted outcomes. Results: The median age of the patient cohort was 33 years, and 84.25% were male. The median injury severity score was 25, the median Glasgow Coma Scale motor score was 3, the basal cisterns were closed in 46.46% of the patients, and a midline shift of >5 mm was seen in 50.39%. The 6-month mortality was 29.13%, and the Rotterdam CT score predicted a mortality of 26% (P < 0.0001) (area under the curve: 0.825; 95% confidence interval: 0.745–0.903). Conclusions: The Rotterdam CT score predicted mortality at 6 months in patients with severe head trauma in a university hospital in Colombia. The Rotterdam CT score is useful for predicting early death and the prognosis of patients with TBI.

scholarly journals Incidence of seizures on continuous EEG monitoring following traumatic brain injury in children

2015 ◽  
Vol 16 (2) ◽  
pp. 167-176 ◽  
Author(s):  
Brent R. O’Neill ◽  
Michael H. Handler ◽  
Suhong Tong ◽  
Kevin E. Chapman
Keyword(s):  
Traumatic Brain Injury ◽  
Brain Injury ◽  
Pediatric Population ◽  
Pediatric Trauma ◽  
Common Mechanism ◽  
Eeg Monitoring ◽  
Discharge Disposition ◽  
Continuous Eeg ◽  
Continuous Eeg Monitoring ◽  
Severe Tbi

OBJECT Seizures may cause diagnostic confusion and be a source of metabolic stress after traumatic brain injury (TBI) in children. The incidence of electroencephalography (EEG)-confirmed seizures and of subclinical seizures in the pediatric population with TBI is not well known. METHODS A routine protocol for continuous EEG (cEEG) monitoring was initiated for all patients with moderate or severe TBI at a Level 1 pediatric trauma center. Over a 3.5-year period, all patients with TBI who underwent cEEG monitoring, both according to protocol and those with mild head injuries who underwent cEEG monitoring at the discretion of the treating team, were identified prospectively. Clinical data were collected and analyzed. RESULTS Over the study period, 594 children were admitted with TBI, and 144 of these children underwent cEEG monitoring. One hundred two (71%) of these 144 children had moderate or severe TBI. Abusive head trauma (AHT) was the most common mechanism of injury (65 patients, 45%) in children with cEEG monitoring. Seizures were identified on cEEG in 43 patients (30%). Forty (93%) of these 43 patients had subclinical seizures, including 17 (40%) with only subclinical seizures and 23 (53%) with both clinical and subclinical seizures. Fifty-three percent of patients with seizures experienced status epilepticus. Age less than 2.4 years and AHT mechanism were strongly correlated with presence of seizures (odds ratios 8.7 and 6.0, respectively). Those patients with only subclinical seizures had the same risk factors as the other groups. The presence of seizures did not correlate with discharge disposition but was correlated with longer hospital stay and intensive care unit stay. CONCLUSIONS Continuous EEG monitoring identifies a significant number of subclinical seizures acutely after TBI. Children younger than 2.4 years of age and victims of AHT are particularly vulnerable to subclinical seizures, and seizures in general. Continuous EEG monitoring allows for accurate diagnosis and timely treatment of posttraumatic seizures, and may mitigate secondary injury to the traumatized brain.

Is Routine Continuous EEG for Traumatic Brain Injury Beneficial?

2017 ◽  
Vol 83 (12) ◽  
pp. 1433-1437 ◽  
Author(s):  
Lia Aquino ◽  
Christopher Y. Kang ◽  
Megan Y. Harada ◽  
Ara Ko ◽  
Amy Do-nguyen ◽  
...  
Keyword(s):  
Traumatic Brain Injury ◽  
Brain Injury ◽  
Injury Severity ◽  
Trauma Patients ◽  
Injury Score ◽  
Increased Risk ◽  
Continuous Eeg ◽  
Severe Tbi ◽  
Level I ◽  
Abbreviated Injury Score

Severe traumatic brain injury (TBI) is associated with increased risk for early clinical and sub-clinical seizures. The use of continuous electroencephalography (cEEG) monitoring after TBI allows for identification and treatment of seizures that may otherwise occur undetected. Benefits of “routine” cEEG after TBI remain controversial. We examined the rate of subclinical seizures identified by cEEG in TBI patients admitted to a Level I trauma center. We analyzed a cohort of trauma patients with moderate to severe TBI (head Abbreviated Injury Score ≥3) who received cEEG within seven days of admission between October 2011 and May 2015. Demographics, clinical data, injury severity, and costs were recorded. Clinical characteristics were compared between those with and without seizures as identified by cEEG. A total of 106 TBI patients with moderate to severe TBI received a cEEG during the study period. Most were male (74%) with a mean age of 55 years. Subclinical seizures were identified by cEEG in only 3.8 per cent of patients. Ninety-three per cent were on antiseizure prophylaxis at the time of cEEG. Patients who had subclinical seizures were significantly older than their counterparts (80 vs 54 years, P = 0.03) with a higher mean head Abbreviated Injury Score (5.0 vs 4.0, P = 0.01). Mortality and intensive care unit stay were similar in both groups. Of all TBI patients who were monitored with cEEG, seizures were identified in only 3.8 per cent. Seizures were more likely to occur in older patients with severe head injury. Given the high cost of routine cEEG and the low incidence of subclinical seizures, we recommend cEEG monitoring only when clinically indicated.

Prognostic significance of blood-brain barrier disruption in patients with severe nonpenetrating traumatic brain injury requiring decompressive craniectomy

2014 ◽  
Vol 121 (3) ◽  
pp. 674-679 ◽  
Author(s):  
Kwok M. Ho ◽  
Stephen Honeybul ◽  
Cheng B. Yip ◽  
Benjamin I. Silbert
Keyword(s):  
Traumatic Brain Injury ◽  
Brain Injury ◽  
Blood Brain Barrier ◽  
Decompressive Craniectomy ◽  
Prognostic Value ◽  
Prognostic Model ◽  
Long Term Outcomes ◽  
Prognostic Information ◽  
Severe Tbi

Object The authors assessed the risk factors and outcomes associated with blood-brain barrier (BBB) disruption in patients with severe, nonpenetrating, traumatic brain injury (TBI) requiring decompressive craniectomy. Methods At 2 major neurotrauma centers in Western Australia, a retrospective cohort study was conducted among 97 adult neurotrauma patients who required an external ventricular drain (EVD) and decompressive craniectomy during 2004–2012. Glasgow Outcome Scale scores were used to assess neurological outcomes. Logistic regression was used to identify factors associated with BBB disruption, defined by a ratio of total CSF protein concentrations to total plasma protein concentration > 0.007 in the earliest CSF specimen collected after TBI. Results Of the 252 patients who required decompressive craniectomy, 97 (39%) required an EVD to control intracranial pressure, and biochemical evidence of BBB disruption was observed in 43 (44%). Presence of disruption was associated with more severe TBI (median predicted risk for unfavorable outcome 75% vs 63%, respectively; p = 0.001) and with worse outcomes at 6, 12, and 18 months than was absence of BBB disruption (72% vs 37% unfavorable outcomes, respectively; p = 0.015). The only risk factor significantly associated with increased risk for BBB disruption was presence of nonevacuated intracerebral hematoma (> 1 cm diameter) (OR 3.03, 95% CI 1.23–7.50; p = 0.016). Although BBB disruption was associated with more severe TBI and worse long-term outcomes, when combined with the prognostic information contained in the Corticosteroid Randomization after Significant Head Injury (CRASH) prognostic model, it did not seem to add significant prognostic value (area under the receiver operating characteristic curve 0.855 vs 0.864, respectively; p = 0.453). Conclusions Biochemical evidence of BBB disruption after severe nonpenetrating TBI was common, especially among patients with large intracerebral hematomas. Disruption of the BBB was associated with more severe TBI and worse long-term outcomes, but when combined with the prognostic information contained in the CRASH prognostic model, this information did not add significant prognostic value.

scholarly journals Absence of electroencephalographic seizure activity in patients treated for head injury with an intracranial pressure–targeted therapy

2009 ◽  
Vol 110 (2) ◽  
pp. 300-305 ◽  
Author(s):  
Magnus Olivecrona ◽  
Bo Zetterlund ◽  
Marie Rodling-Wahlström ◽  
Silvana Naredi ◽  
Lars-Owe D. Koskinen
Keyword(s):  
Brain Injury ◽  
Intracranial Pressure ◽  
University Hospital ◽  
Targeted Treatment ◽  
Secondary Brain Injury ◽  
Eeg Monitoring ◽  
Continuous Eeg ◽  
Level Of Consciousness ◽  
Continuous Eeg Monitoring ◽  
Severe Tbi

Object The authors prospectively studied the occurrence of clinical and nonclinical electroencephalographically verified seizures during treatment with an intracranial pressure (ICP)–targeted protocol in patients with traumatic brain injury (TBI). Methods All patients treated for TBI at the Department of Neurosurgery, University Hospital Umeå, Sweden, were eligible for the study. The inclusion was consecutive and based on the availability of the electroencephalographic (EEG) monitoring equipment. Patients were included irrespective of pupil size, pupil reaction, or level of consciousness as long as their first measured cerebral perfusion pressure was > 10 mm Hg. The patients were treated in a protocol-guided manner with an ICP-targeted treatment based on the Lund concept. The patients were continuously sedated with midazolam, fentanyl, propofol, or thiopental, or combinations thereof. Five-lead continuous EEG monitoring was performed with the electrodes at F3, F4, P3, P4, and a midline reference. Sensitivity was set at 100 μV per cm and filter settings 0.5–70 Hz. Amplitude-integrated EEG recording and relative band power trends were displayed. The trends were analyzed offline by trained clinical neurophysiologists. Results Forty-seven patients (mean age 40 years) were studied. Their median Glasgow Coma Scale score at the time of sedation and intubation was 6 (range 3–15). In 8.5% of the patients clinical seizures were observed before sedation and intubation. Continuous EEG monitoring was performed for a total of 7334 hours. During this time neither EEG nor clinical seizures were observed. Conclusions Our protocol-guided ICP targeted treatment seems to protect patients with severe TBI from clinical and subclinical seizures and thus reduces the risk of secondary brain injury.

scholarly journals Disability Rating Scale in the First Few Weeks After a Severe Traumatic Brain Injury as a Predictor of 6-Month Functional Outcome

Neurosurgery ◽  
2020 ◽  
Author(s):  
Jose-Miguel Yamal ◽  
Imoigele P Aisiku ◽  
H Julia Hannay ◽  
Frances A Brito ◽  
Claudia S Robertson
Keyword(s):  
Traumatic Brain Injury ◽  
Brain Injury ◽  
Severe Traumatic Brain Injury ◽  
Clinical Decision Making ◽  
Injury Severity ◽  
Rating Scale ◽  
Characteristic Curve ◽  
Disability Rating Scale ◽  
Severe Tbi ◽  
Disability Rating

Abstract BACKGROUND An early acute marker of long-term neurological outcome would be useful to help guide clinical decision making and therapeutic effectiveness after severe traumatic brain injury (TBI). We investigated the utility of the Disability Rating Scale (DRS) as early as 1 wk after TBI as a predictor of favorable 6-mo Glasgow Outcome Scale extended (GOS-E). OBJECTIVE To determine the predictability of a favorable 6-mo GOS-E using the DRS measured during weeks 1 to 4 of injury. METHODS The study is a sub analysis of patients enrolled in the Epo Severe TBI Trial (n = 200) to train and validate L1-regularized logistic regression models. DRS was collected at weeks 1 to 4 and GOS-E at 6 mo. RESULTS The average area under the receiver operating characteristic curve was 0.82 for the model with baseline demographic and injury severity variables and week 1 DRS and increased to 0.88 when including weekly DRS until week 4. CONCLUSION This study suggests that week 1 to 4 DRS may be predictors of favorable 6-mo outcome in severe TBI patients and thus useful both for clinical prognostication as well as surrogate endpoints for adaptive clinical trials.

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