Multimodal Prediction of 3- and 12-Month Outcomes in ICU Patients with Acute Disorders of Consciousness.

BACKGROUND: In intensive care unit (ICU) patients with coma and other disorders of consciousness (DoC), outcome prediction is key to decision-making regarding prognostication, neurorehabilitation, and management of family expectations. Current prediction algorithms are largely based on chronic DoC, whereas multimodal data from acute DoC are scarce. Therefore, the Consciousness in Neurocritical Care Cohort Study Using Electroencephalography and Functional Magnetic Resonance Imaging (i.e. CONNECT-ME; ClinicalTrials.gov identifier: NCT02644265) investigates ICU patients with acute DoC due to traumatic and nontraumatic brain injuries, using electroencephalography (EEG) (resting-state and passive paradigms), functional magnetic resonance imaging (fMRI) (resting-state) and systematic clinical examinations. METHODS: We previously presented results for a subset of patients (n = 87) concerning prediction of consciousness levels in the ICU. Now we report 3- and 12-month outcomes in an extended cohort (n = 123). Favorable outcome was defined as a modified Rankin Scale score ≤ 3, a cerebral performance category score ≤ 2, and a Glasgow Outcome Scale Extended score ≥ 4. EEG features included visual grading, automated spectral categorization, and support vector machine consciousness classifier. fMRI features included functional connectivity measures from six resting-state networks. Random forest and support vector machine were applied to EEG and fMRI features to predict outcomes. Here, random forest results are presented as areas under the curve (AUC) of receiver operating characteristic curves or accuracy. Cox proportional regression with in-hospital death as a competing risk was used to assess independent clinical predictors of time to favorable outcome. RESULTS: Between April 2016 and July 2021, we enrolled 123 patients (mean age 51 years, 42% women). Of 82 (66%) ICU survivors, 3- and 12-month outcomes were available for 79 (96%) and 77 (94%), respectively. EEG features predicted both 3-month (AUC 0.79 [95% confidence interval (CI) 0.77-0.82]) and 12-month (AUC 0.74 [95% CI 0.71-0.77]) outcomes. fMRI features appeared to predict 3-month outcome (accuracy 0.69-0.78) both alone and when combined with some EEG features (accuracies 0.73-0.84) but not 12-month outcome (larger sample sizes needed). Independent clinical predictors of time to favorable outcome were younger age (hazard ratio [HR] 1.04 [95% CI 1.02-1.06]), traumatic brain injury (HR 1.94 [95% CI 1.04-3.61]), command-following abilities at admission (HR 2.70 [95% CI 1.40-5.23]), initial brain imaging without severe pathological findings (HR 2.42 [95% CI 1.12-5.22]), improving consciousness in the ICU (HR 5.76 [95% CI 2.41-15.51]), and favorable visual-graded EEG (HR 2.47 [95% CI 1.46-4.19]). CONCLUSIONS: Our results indicate that EEG and fMRI features and readily available clinical data predict short-term outcome of patients with acute DoC and that EEG also predicts 12-month outcome after ICU discharge.

Subclinical Epileptiform Activity in Dementia with Lewy Bodies.

BACKGROUND: Patients with dementia with Lewy bodies (DLB) have a higher probability of seizures than in normal aging and in other types of neurodegenerative disorders. Depositions of α-synuclein, a pathological hallmark of DLB, can induce network excitability, which can escalate into seizure activity. Indicator of seizures are epileptiform discharges as observed using electroencephalography (EEG). However, no studies have so far investigated the occurrence of interictal epileptiform discharges (IED) in patients with DLB. OBJECTIVES: To investigate if IED as measured with ear-EEG occurs with a higher frequency in patients with DLB compared to healthy controls (HC). METHODS: In this longitudinal observational exploratory study, 10 patients with DLB and 15 HC were included in the analysis. Patients with DLB underwent up to three ear-EEG recordings, each lasting up to 2 days, over a period of 6 months. RESULTS: At baseline, IED were detected in 80% of patients with DLB and in 46.7% of HC. The spike frequency (spikes or sharp waves/24 hours) was significantly higher in patients with DLB as compared to HC with a risk ratio of 2.52 (CI, 1.42-4.61; P-value = 0.001). Most IED occurred at night. CONCLUSIONS: Long-term outpatient ear-EEG monitoring detects IED in most patients with DLB with an increased spike frequency compared to HC. This study extends the spectrum of neurodegenerative disorders in which epileptiform discharges occurs at an elevated frequency. It is possible that epileptiform discharges are, therefore, a consequence of neurodegeneration. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Detection of subclinical epileptiform discharges in Alzheimer's disease using long-term outpatient EEG monitoring.

BACKGROUND: In patients with Alzheimer's disease (AD) without clinical seizures, up to half have epileptiform discharges on long-term in-patient electroencephalography (EEG) recordings. Long-term in-patient monitoring is obtrusive, and expensive as compared to outpatient monitoring. No studies have so far investigated if long-term outpatient EEG monitoring is able to identify epileptiform discharges in AD. Our aim is to investigate if epileptiform discharges as measured with ear-EEG are more common in patients with AD compared to healthy elderly controls (HC). METHODS: In this longitudinal observational study, 24 patients with mild to moderate AD and 15 age-matched HC were included in the analysis. Patients with AD underwent up to three ear-EEG recordings, each lasting up to two days, within 6 months. RESULTS: The first recording was defined as the baseline recording. At baseline, epileptiform discharges were detected in 75.0% of patients with AD and in 46.7% of HC (p-value = 0.073). The spike frequency (spikes or sharp waves/24 h) was significantly higher in patients with AD as compared to HC with a risk ratio of 2.90 (CI: 1.77-5.01, p < 0.001). Most patients with AD (91.7%) showed epileptiform discharges when combining all ear-EEG recordings. CONCLUSIONS: Long-term ear-EEG monitoring detects epileptiform discharges in most patients with AD with a three-fold increased spike frequency compared to HC, which most likely originates from the temporal lobes. Since most patients showed epileptiform discharges with multiple recordings, elevated spike frequency should be considered a marker of hyperexcitability in AD.

Multimodal prediction of residual consciousness in the intensive care unit: the CONNECT-ME study.

Functional MRI (fMRI) and EEG may reveal residual consciousness in patients with disorders of consciousness (DoC), as reflected by a rapidly expanding literature on chronic DoC. However, acute DoC is rarely investigated, although identifying residual consciousness is key to clinical decision-making in the intensive care unit (ICU). Therefore, the objective of the prospective, observational, tertiary centre cohort, diagnostic phase IIb study 'Consciousness in neurocritical care cohort study using EEG and fMRI' (CONNECT-ME, NCT02644265) was to assess the accuracy of fMRI and EEG to identify residual consciousness in acute DoC in the ICU. Between April 2016 and November 2020, 87 acute DoC patients with traumatic or non-traumatic brain injury were examined with repeated clinical assessments, fMRI and EEG. Resting-state EEG and EEG with external stimulations were evaluated by visual analysis, spectral band analysis and a Support Vector Machine (SVM) consciousness classifier. In addition, within- and between-network resting-state connectivity for canonical resting-state fMRI networks was assessed. Next, we used EEG and fMRI data at study enrolment in two different machine-learning algorithms (Random Forest and SVM with a linear kernel) to distinguish patients in a minimally conscious state or better (≥MCS) from those in coma or unresponsive wakefulness state (≤UWS) at time of study enrolment and at ICU discharge (or before death). Prediction performances were assessed with area under the curve (AUC). Of 87 DoC patients (mean age, 50.0 ± 18 years, 43% female), 51 (59%) were ≤UWS and 36 (41%) were ≥ MCS at study enrolment. Thirty-one (36%) patients died in the ICU, including 28 who had life-sustaining therapy withdrawn. EEG and fMRI predicted consciousness levels at study enrolment and ICU discharge, with maximum AUCs of 0.79 (95% CI 0.77-0.80) and 0.71 (95% CI 0.77-0.80), respectively. Models based on combined EEG and fMRI features predicted consciousness levels at study enrolment and ICU discharge with maximum AUCs of 0.78 (95% CI 0.71-0.86) and 0.83 (95% CI 0.75-0.89), respectively, with improved positive predictive value and sensitivity. Overall, both machine-learning algorithms (SVM and Random Forest) performed equally well. In conclusion, we suggest that acute DoC prediction models in the ICU be based on a combination of fMRI and EEG features, regardless of the machine-learning algorithm used.

Local networks from different parts of the human cerebral cortex generate and share the same population dynamic.

A major goal of neuroscience is to reveal mechanisms supporting collaborative actions of neurons in local and larger-scale networks. However, no clear overall principle of operation has emerged despite decades-long experimental efforts. Here, we used an unbiased method to extract and identify the dynamics of local postsynaptic network states contained in the cortical field potential. Field potentials were recorded by depth electrodes targeting a wide selection of cortical regions during spontaneous activities, and sensory, motor, and cognitive experimental tasks. Despite different architectures and different activities, all local cortical networks generated the same type of dynamic confined to one region only of state space. Surprisingly, within this region, state trajectories expanded and contracted continuously during all brain activities and generated a single expansion followed by a contraction in a single trial. This behavior deviates from known attractors and attractor networks. The state-space contractions of particular subsets of brain regions cross-correlated during perceptive, motor, and cognitive tasks. Our results imply that the cortex does not need to change its dynamic to shift between different activities, making task-switching inherent in the dynamic of collective cortical operations. Our results provide a mathematically described general explanation of local and larger scale cortical dynamic.

Progressive slowing of clonic phase predicts postictal generalized EEG suppression.

OBJECTIVE: Postictal generalized electroencephalography (EEG) suppression (PGES) is a surrogate marker of sudden unexpected death in epilepsy (SUDEP). It is still unclear which ictal phenomena lead to prolonged PGES and increased risk of SUDEP. Semiology features of generalized convulsive seizure (GCS type 1) have been reported as a predictor of prolonged PGES. Progressive slowing of clonic phase (PSCP) has been observed in GCSs, with gradually increasing inhibitory periods interrupting the tonic contractions. We hypothesized that PSCP is associated with prolonged PGES. METHODS: We analyzed 90 bilateral convulsive seizures in 50 consecutive patients (21 female; age: 11-62 years, median: 31 years) recruited to video-EEG monitoring. Five raters, blinded to all other data, independently assessed the presence of PSCP. PGES and seizure semiology were evaluated independently. We determined inter-rater agreement (IRA) for the presence of PSCP, and we evaluated its association, as well as that of other ictal features, with the occurrence of PGES, prolonged PGES (≥20 s) and very prolonged PGES (≥50 s) using multivariate logistic regression analysis. RESULTS: We found substantial IRA for the presence of PSCP (percent agreement: 80%; beyond-chance agreement coefficient: .655). PSCP was an independent predictor of the occurrence of PGES and prolonged PGES (p < .001). All seizures with very prolonged PGES had PSCP. GCS type 1 was an independent predictor of occurrence of PGES (p = .02) and prolonged PGES (p = .03) but not of very prolonged PGES. Only half of the seizures with very prolonged PGES were GCS type 1. SIGNIFICANCE: PSCP predicts prolonged PGES, emphasizing the importance of gradually increasing inhibitory phenomena at the end of the seizures. Our findings shed more light on the ictal phenomena leading to increased risk of SUDEP. These phenomena may provide basis for algorithms implemented into wearable devices for identifying GCS with increased risk of SUDEP.

[Wearable devices for automated seizure detection].

The International League Against Epilepsy and the International Federation of Clinical Neurophysiology developed a clinical practice guideline on the use of automated seizure detection with wearable devices. They recommend using clinically validated devices for automated detection of generalized tonic-clonic seizures and focal to bilateral tonic-clonic seizures, especially in unsupervised patients, where alarms can result in rapid intervention. In this review, we investigate the published evidence behind the guideline, and we outline the need for future research.

Accuracy of high-density EEG electrode position measurement using an optical scanner compared with the photogrammetry method.

Objective: To determine the feasibility and accuracy of a handheld optical scanner to measure the three-dimensional (3D) EEG electrode coordinates in a high-density array of 256 electrodes. Methods: We compared the optical scanning with a previously validated method, based on photogrammetry. Electrode coordinates were co-registered with the MRI of the patients, and mean distance error relative to the three-dimensional MRI reconstruction was determined for each patient. We included 60 patients: 30 were measured using the photogrammetry method, and 30 age and gender matched patients were measured with the optical scanner. Results: Using the optical scanner, the mean distance error was 1.78 mm (95% confidence interval: 1.59-1.98 mm) which was significantly lower (p < 0.001) compared with the photogrammetry method (mean distance error: 2.43 mm; 95% confidence interval: 2.28-2.57 mm). The real-time scanning took 5-10 min per patient. Conclusions: The handheld optical scanner is more accurate and feasible, compared to the photogrammetry method. Significance: Measuring EEG electrode positions in high-density array, using the optical scanner is suitable for clinical implementation in EEG source imaging for presurgical evaluation.

[EEG diagnosticsof non-convulsive status epilepticus in critically ill patients].

Critically ill patients are at high risk of non-convulsive status epilepticus (NCSE). As clinical signs of NCSE are subtle and unspecific, EEG is necessary to make the diagnosis. This is a review of the terminology for EEG reporting and the criteria for NCSE in critically ill patients. We discuss the newly proposed ictal-interictal continuum, and how caution is needed when assessing EEG criteria in order to avoid both over- and undertreatment. Finally, we discuss how specific EEG findings, in combination with clinical information, can help infer treatment decision and need for continuous EEG monitoring.

Learn to interpret voltage maps: an atlas of topographies.

Describing the location of EEG abnormalities, such as interictal epileptiform discharges, is an important step in the interpretation of EEG recordings and has clinical relevance, as it is expected to point out the region of the brain generating these abnormal signals. Traditionally, the location is reported by specifying the area on the scalp where maximum negativity is located. However, this only reflects the correct localization in the brain when the cortical generator is located on the convexity (radial orientation). When the cortical generator is in the wall of a sulcus (tangential orientation), due to current flow (volume conduction), the maximum negativity is not over the generator, but at a distance from it. Voltage maps are widely available in most EEG reader software programs. Simple rules for reading voltage maps help to estimate the orientation and location of the source in the brain, avoiding false lateralization and false localization. In this seminar in epileptology, using a didactic approach, we explain how to read voltage maps and provide an atlas of voltage maps.

Automated ictal EEG source imaging: A retrospective, blinded clinical validation study.

OBJECTIVE: EEG source imaging (ESI) is a validated tool in the multimodal workup of patients with drug resistant focal epilepsy. However, it requires special expertise and it is underutilized. To circumvent this, automated analysis pipelines have been developed and validated for the interictal discharges. In this study, we present the clinical validation of an automated ESI for ictal EEG signals. METHODS: We have developed an automated analysis pipeline of ictal EEG activity, based on spectral analysis in source space, using an individual head model of six tissues. The analysis was done blinded to all other data. As reference standard, we used the concordance with the resected area and one-year postoperative outcome. RESULTS: We analyzed 50 consecutive patients undergoing epilepsy surgery (34 temporal and 16 extra-temporal). Thirty patients (60%) became seizure-free. The accuracy of the automated ESI was 74% (95% confidence interval: 59.66-85.37%). CONCLUSIONS: Automated ictal ESI has a high accuracy for localizing the seizure onset zone. SIGNIFICANCE: Automating the ESI of the ictal EEG signals will facilitate implementation of this tool in the presurgical evaluation.

Can tendon reflexes be elicited by both stretch and vibration in man?

AIM OF STUDY: When the biceps tendon is tapped, a contraction is elicited in the biceps muscle. This also occurs with tapping of the radial bone, and it has been suggested that vibration is a stimulus for deep tendon reflexes. We investigated whether the normal stimulus for the deep tendon reflex is a sudden stretch, a phasic vibration, or both. Furthermore, we investigated the importance of forearm position for the reflex response in controls and stroke patients. METHODS: We investigated 50 neurological outpatients without clinical signs of neurological disorders in the arms. The biceps tendon and distal radius were tapped with the forearm in the midway (90°), supinated, and pronated positions. In 10 of these patients, the two reflexes were also investigated with quantitative electromyography (EMG) measurements in the 3 positions. Another 10 patients were investigated clinically when stretch of elbow was eliminated and 17 patients were examined when prestretching of the biceps tendon was avoided. Finally, we examined 32 patients that had experienced stroke. RESULTS: In 94% (47/50) of patients, after a radial tap, the biceps contraction disappeared in the supinated forearm, and the median peak-to-peak amplitude of the surface EMG response (n = 10) decreased from 1.1 to 0.2 mV (p < .01). Elimination of elbow stretch as well as pressure on the biceps tendon did not change the reflex response. In 84% (27/32) of stroke patients, after a radial tap, the biceps contraction persisted in supination in the arm with hyperreflexia. CONCLUSION: The combined clinical and EMG results are consistent with the concept that the deep tendon reflexes in man can be elicited by both stretch and phasic vibration. Clinicians should be aware that the brachioradial reflex depends on the forearm position.

Triphasic Waves Are Generated by Widespread Bilateral Cortical Networks.

PURPOSE: Triphasic waves (TWs) have been observed in the EEG recorded in patients with various types of encephalopathy, yet their genesis and significance is still debated. The aim of this study was to elucidate the localization of the cortical generators of TWs using EEG source imaging. METHODS: In 20 consecutive patients who had encephalopathy with TWs, EEG source imaging of the first negative and the positive phases of the TW was performed. Three different approaches were used: equivalent current dipoles, a distributed source model, and a recently described spatial filtration method for visualizing EEG in source space. RESULTS: Equivalent current dipole models failed to provide valid solutions. The distributed source model and the spatial filtration method suggested that TWs were generated by large, bilateral cortical networks, invariably involving the anterior frontal and the temporo-polar areas. CONCLUSIONS: Source imaging localized TWs to anterior frontal and temporo-frontal structures. Involvement of these regions is consistent with the typical pathophysiological changes of altered consciousness and cognitive changes observed in patients with TW encephalopathy.

Does continuous electroencephalography influence therapeutic decisions in neurocritical care?

OBJECTIVES: In the neurocritical care unit (neuro-ICU), the impact of continuous EEG (cEEG) on therapeutic decisions and prognostication, including outcome prediction using the Status Epilepticus Severity Score (STESS), is poorly investigated. We studied to what extent cEEG contributes to treatment decisions, and how this relates to clinical outcome and the use of STESS in neurocritical care. METHODS: We included patients admitted to the neuro-ICU or neurological step-down unit of a tertiary referral hospital between 05/2013 and 06/2015. Inclusion criteria were ≥20 h of cEEG monitoring and age ≥15 years. Exclusion criteria were primary epileptic and post-cardiac arrest encephalopathies. RESULTS: Ninety-eight patients met inclusion criteria, 80 of which had status epilepticus, including 14 with super-refractory status. Median length of cEEG monitoring was 50 h (range 21-374 h). Mean STESS was lower in patients with favorable outcome 1 year after discharge (modified Rankin Scale [mRS] 0-2) compared to patients with unfavorable outcome (mRS 3-6), albeit not statistically significant (mean STESS 2.3 ± 2.1 vs 3.6 ± 1.7, p = 0.09). STESS had a sensitivity of 80%, a specificity of 42%, and a negative predictive value of 93% for outcome. cEEG results changed treatment decisions in 76 patients, including escalation of antiepileptic treatment in 65 and reduction in 11 patients. CONCLUSION: Status Epilepticus Severity Score had a high negative predictive value but low sensitivity, suggesting that STESS should be used cautiously. Of note, cEEG results altered clinical decision-making in three of four patients, irrespective of the presence or absence of status epilepticus, confirming the clinical value of cEEG in neurocritical care.

Somatosensory phenomena elicited by electrical stimulation of hippocampus: Insight into the ictal network.

Up to 11% of patients with mesial temporal lobe epilepsy experience somatosensory auras, although these structures do not have any somatosensory physiological representation. We present the case of a patient with left mesial temporal lobe epilepsy who had somatosensory auras on the right side of the body. Stereo-EEG recording demonstrated seizure onset in the left mesial temporal structures, with propagation to the sensory cortices, when the patient experienced the somatosensory aura. Direct electrical stimulation of both the left amygdala and the hippocampus elicited the patient's habitual, somatosensory aura, with afterdischarges propagating to sensory cortices. These unusual responses to cortical stimulation suggest that in patients with epilepsy, aberrant neural networks are established, which have an essential role in ictogenesis.

What Should a Clinician Do When Spreading Depolarizations are Observed in a Patient?

The International Conference on Spreading Depolarizations (iCSD) held in Boca Raton, Florida, in the September of 2018 devoted a section to address the question, "What should a clinician do when spreading depolarizations are observed in a patient?" Discussants represented a wide range of expertise, including neurologists, neurointensivists, neuroradiologists, neurosurgeons, and pre-clinical neuroscientists, to provide both clinical and basic pathophysiology perspectives. A draft summary of viewpoints offered was then written by a multidisciplinary writing group of iCSD members, based on a transcript of the session. Feedback of all discussants was formally collated, reviewed, and incorporated into the final document which was subsequently approved by all authors.

Diagnostic added value of electrical source imaging in presurgical evaluation of patients with epilepsy: A prospective study.

OBJECTIVE: To investigate the diagnostic added value of electrical source imaging (ESI) in presurgical evaluation of patients with drug resistant focal epilepsy. METHODS: Eighty-two consecutive patients were included. We analyzed both low density (LD) and high density (HD) EEG recordings. LD ESI was done on interictal and ictal signals recorded during long-term video-EEG monitoring (LTM), with standard 25 electrodes and age-matched template head models. HD ESI was done on shorter recordings (90-120 min), with 256 electrodes, using individual head model. The multidisciplinary team made decisions first blinded to ESI (based on all other modalities) and then discussed the results of the ESI. We considered that ESI had diagnostic added value, when it provided non-redundant information that changed the patients management plan. RESULTS: ESI had diagnostic added value in 28 patients (34%). In most cases (85.7%), these changes were related to planning of the invasive recordings. In nine out of 13 patients, invasive recordings confirmed the localization. Out of eight patients in whom the ESI source was resected, six became seizure-free. CONCLUSIONS: ESI provides non-redundant information in one third of the patients undergoing presurgical evaluation. SIGNIFICANCE: This study provides evidence for the diagnostic added value of ESI in presurgical evaluation.

Which Spreading Depolarizations Are Deleterious To Brain Tissue?

Spreading depolarizations (SDs) are profound disruptions of cellular homeostasis that slowly propagate through gray matter and present an extraordinary metabolic challenge to brain tissue. Recent work has shown that SDs occur commonly in human patients in the neurointensive care setting and have established a compelling case for their importance in the pathophysiology of acute brain injury. The International Conference on Spreading Depolarizations (iCSD) held in Boca Raton, Florida, in September of 2018 included a discussion session focused on the question of "Which SDs are deleterious to brain tissue?" iCSD is attended by investigators studying various animal species including invertebrates, in vivo and in vitro preparations, diseases of acute brain injury and migraine, computational modeling, and clinical brain injury, among other topics. The discussion included general agreement on many key issues, but also revealed divergent views on some topics that are relevant to the design of clinical interventions targeting SDs. A draft summary of viewpoints offered was then written by a multidisciplinary writing group of iCSD members, based on a transcript of the session. Feedback of all discussants was then formally collated, reviewed and incorporated into the final document. It is hoped that this report will stimulate collection of data that are needed to develop a more nuanced understanding of SD in different pathophysiological states, as the field continues to move toward effective clinical interventions.

Diagnostic yield of high-density versus low-density EEG: The effect of spatial sampling, timing and duration of recording.

OBJECTIVE: To investigate the effect of spatial sampling and of recording duration on the diagnostic yield of EEG for identification of interictal epileptiform discharges (IEDs). Previous studies demonstrated that high-density (HD) recordings increased accuracy of localization compared to low-density (LD) recordings. METHODS: We have prospectively evaluated the effect of spatial sampling and of recording duration in patients who had short-term (ST) recordings with a HD array of 256 electrodes following long-term (LT) recordings with a LD array consisting of the standard IFCN array of 25 electrodes. IED clusters were identified in four datasets: LT-LD, ST-LD (spatially down-sampled to the standard IFCN array), ST-HD and a shortened (90 minutes) epoch of LT-LD. RESULTS: Sixty consecutive patients were recruited. We identified 89 IED clusters totally. Two clusters were found by increasing spatial sampling from 25 to 256 electrodes. This modest increase was not statistically significant. Eight clusters were missed by reducing the recording duration to 90 minutes, as compared with the LT recordings (p = 0.003). CONCLUSIONS: Recording duration is more important for the diagnostic yield of EEGs than increasing spatial sampling beyond the standard IFCN electrode array. SIGNIFICANCE: The standard IFCN electrode array provides sufficient spatial sampling for identification of the IEDs.

Neurostereologic Lesion Volumes and Spreading Depolarizations in Severe Traumatic Brain Injury Patients: A Pilot Study.

BACKGROUND: Spreading depolarizations (SDs) occur in 50-60% of patients after surgical treatment of severe traumatic brain injury (TBI) and are independently associated with unfavorable outcomes. Here we performed a pilot study to examine the relationship between SDs and various types of intracranial lesions, progression of parenchymal damage, and outcomes. METHODS: In a multicenter study, fifty patients (76% male; median age 40) were monitored for SD by continuous electrocorticography (ECoG; median duration 79 h) following surgical treatment of severe TBI. Volumes of hemorrhage and parenchymal damage were estimated using unbiased stereologic assessment of preoperative, postoperative, and post-ECoG serial computed tomography (CT) studies. Neurologic outcomes were assessed at 6 months by the Glasgow Outcome Scale-Extended. RESULTS: Preoperative volumes of subdural and subarachnoid hemorrhage, but not parenchymal damage, were significantly associated with the occurrence of SDs (P's < 0.05). Parenchymal damage increased significantly (median 34 ml [Interquartile range (IQR) - 2, 74]) over 7 (5, 8) days from preoperative to post-ECoG CT studies. Patients with and without SDs did not differ in extent of parenchymal damage increase [47 ml (3, 101) vs. 30 ml (- 2, 50), P = 0.27], but those exhibiting the isoelectric subtype of SDs had greater initial parenchymal damage and greater increases than other patients (P's < 0.05). Patients with temporal clusters of SDs (≥ 3 in 2 h; n = 10 patients), which included those with isoelectric SDs, had worse outcomes than those without clusters (P = 0.03), and parenchymal damage expansion also correlated with worse outcomes (P = 0.01). In multivariate regression with imputation, both clusters and lesion expansion were significant outcome predictors. CONCLUSIONS: These results suggest that subarachnoid and subdural blood are important primary injury factors in provoking SDs and that clustered SDs and parenchymal lesion expansion contribute independently to worse patient outcomes. These results warrant future prospective studies using detailed quantification of TBI lesion types to better understand the relationship between anatomic and physiologic measures of secondary injury.