Recovery Of Consciousness In Patients Research Articles

Connectivity of EEG and fMRI network in the resting state in healthy people and patients with post-traumatic disorder of consciousness

Recovery of consciousness in patients with post-comatose unconscious states after severe traumatic brain injury and the search for their objective markers are among the urgent medical and social problems. To clarify the information content and the degree of consistency of changes in hemodynamic and bioelectrical parameters, in this work we carried out comparative studies of fMRI networks and EEG connectivity at rest in healthy subjects, as well as in patients with post-traumatic disorders of consciousness before and after therapeutic rhythmic transcranial magnetic stimulation (rTMS). It was shown that the characteristics of the functional connectivity of fMRI and EEG at rest are among the informative markers of neuroplasticity during depression of consciousness. A certain topographic correspondence between the fMRI networks and the EEG integral connectivity pattern at rest was established, regardless of the modification of the latter assessment: in the continuous recording mode or pseudo-EP. At the same time, the method of independent fMRI components more clearly reveals the features of the state of individual neural networks, and the indicators of EEG functional connectivity (range 1–15 Hz) are more informative in assessing the integral neural network characteristics and their changes during treatment.

Transcutaneous auricular vagal nerve stimulation for consciousness recovery in patients with prolonged disorders of consciousness (TAVREC): study protocol for a multicenter, triple-blind, randomized controlled trial in China

IntroductionProlonged disorders of consciousness (pDoC) are a catastrophic condition following brain injury with few therapeutic options. Transcutaneous auricular vagal nerve stimulation (taVNS), a safe, non-invasive intervention modulating thalamo-cortical connectivity and...

Resting-State EEG Signature of Early Consciousness Recovery in Comatose Patients with Traumatic Brain Injury.

Resting-state electroencephalography (rsEEG) is usually obtained to assess seizures in comatose patients with traumatic brain injury (TBI). We aim to investigate rsEEG measures and their prediction of early recovery of consciousness in patients with TBI. This is a retrospective study of comatose patients with TBI who were admitted to a trauma center (October 2013 to January 2022). Demographics, basic clinical data, imaging characteristics, and EEGs were collected. We calculated the following using 10-min rsEEGs: power spectral density, permutation entropy (complexity measure), weighted symbolic mutual information (wSMI, global information sharing measure), Kolmogorov complexity (Kolcom, complexity measure), and heart-evoked potentials (the averaged EEG signal relative to the corresponding QRS complex on electrocardiography). We evaluated the prediction of consciousness recovery before hospital discharge using clinical, imaging, and rsEEG data via a support vector machine. We studied 113 of 134 (84%) patients with rsEEGs. A total of 73 (65%) patients recovered consciousness before discharge. Patients who recovered consciousness were younger (40 vs. 50years, p = 0.01). Patients who recovered also had higher Kolcom (U = 1688, p = 0.01), increased beta power (U = 1,652 p = 0.003) with higher variability across channels (U = 1534, p = 0.034) and epochs (U = 1711, p = 0.004), lower delta power (U = 981, p = 0.04), and higher connectivity across time and channels as measured by wSMI in the theta band (U = 1636, p = 0.026; U = 1639, p = 0.024) than those who did not recover. The area under the receiver operating characteristic curve for rsEEG was higher than that for clinical data (using age, motor response, pupil reactivity) and higher than that for the Marshall computed tomography classification (0.69 vs. 0.66 vs. 0.56, respectively; p < 0.001). We describe the rsEEG signature in recovery of consciousness prior to discharge in comatose patients with TBI. rsEEG measures performed modestly better than the clinical and imaging data in predicting recovery.

Increased Adrenocorticotropic Hormone Levels Predict Recovery of Consciousness in Patients With Disorders of Consciousness.

The potential influence of pituitary-related hormones (including both pituitary gland and target gland hormones) on functional recovery after traumatic brain injury has been observed. However, the relationship between these hormones and the recovery of consciousness in patients with disorders of consciousness (DOC) remains unclear. In this retrospective and observational study, 208 patients with DOC were recruited. According to the Glasgow Outcome Scale (GOS) scores after 6 months, patients with DOC were categorized into two subgroups: a favorable prognosis subgroup (n = 38) comprising those who regained consciousness (GOS score ≥3), and a poor prognosis subgroup (n = 156) comprising those who remained in DOC (GOS score <3). Comparative analyses of pituitary-related hormone levels between the two subgroups were conducted. Further, a binary logistic regression analysis was conducted to assess the predictive value of pituitary-related hormones for the patients' prognosis. The favorable prognosis subgroup showed a significant increase in adrenocorticotropic hormone (ACTH) levels (p = 0.036). Moreover, higher ACTH levels and shorter days since injury were significantly associated with a better prognosis, with odds ratios (ORs) of 0.928 (95% confidence interval [CI] = 0.873-0.985, p = 0.014) and 1.015 (95% CI = 1.005-1.026, p = 0.005), respectively. A subsequent receiver operating characteristic (ROC) analysis demonstrated the potential to predict patients' prognosis with an area under the curve value of 0.78, an overall accuracy of 75.5%, a sensitivity of 77.5%, and a specificity of 66.7%. Our findings indicate that ACTH levels could serve as a clinically valuable and convenient predictor for patients' prognosis.

237 SeeMe: An Automated Methodology to Detect Early Signs of Recovery After Acute Brain Injury

INTRODUCTION: Assessing the functional state of the brain and predicting recovery after acute brain injury (ABI) remains a major unsolved problem. At present, physicians make predictions using clinical examination, traditional scoring systems, and statistical models, which have significant shortcomings and lack the ability to forecast recovery on an individual basis. METHODS: SeeMe is based on analyzing subtle facial expressions in response to auditory commands (i.e., “open your eyes,” “make a smile”) over time and compares the results to a pre-stimulus baseline. These subtle motions are often not detectable by the naked eye. We enrolled 26 comatose ABI patients and 16 healthy volunteers to test this tool. Command-evoked eye-opening movements were compared to clinical observation and the JFK Coma Recovery Scale-Revised (CRS-R). RESULTS: In our study, 22 of 26 (85%) patients recovered consciousness during hospitalization after ABI. On average, SeeMe detected command-evoked eye opening ∼9 days before clinical assessment using the CRS-R and ∼3 days before blinded human raters who observed the recorded videos using the naked eye.Using the optimally identified decision threshold, SeeMe demonstrated the following performance metrics on ABI patients with no eye opening to command (auditory CRS subscale = 2): sensitivity = 74.1%, specificity = 66.6%, positive predictive value = 16.8%, and negative predictive value = 96.6%. CONCLUSIONS: These findings demonstrate the high predictive performance of SeeMe in assessing consciousness in ABI patients and provide a quantitative tool for studying neural circuits and developing novel therapeutic approaches. SeeMe's ability to detect low-amplitude motor movements opens new avenues for understanding and facilitating recovery of consciousness in patients with ABI.

Common Data Element for Disorders of Consciousness: Recommendations from the Working Group on Therapeutic Interventions.

Over the past 30years, there have been significant advances in the understanding of the mechanisms associated with loss and recovery of consciousness following severe brain injury. This work has provided a strong grounding for the development of novel restorative therapeutic interventions. Although all interventions are aimed at modulating and thereby restoring brain function, the landscape of existing interventions encompasses a very wide scope of techniques and protocols. Despite vigorous research efforts, few approaches have been assessed with rigorous, high-quality randomized controlled trials. As a growing number of exploratory interventions emerge, it is paramount to develop standardized approaches to reporting results. The successful evaluation of novel interventions depends on implementation of shared nomenclature and infrastructure. To address this gap, the Neurocritical Care Society's Curing Coma Campaign convened nine working groups and charged them with developing common data elements (CDEs). Here, we report the work of the Therapeutic Interventions Working Group. The working group reviewed existing CDEs relevant to therapeutic interventions within the National Institutes of Health National Institute of Neurological Disorders and Stroke database and reviewed the literature for assessing key areas of research in the intervention space. CDEs were then proposed, iteratively discussed and reviewed, classified, and organized in a case report form (CRF). We developed a unified CRF, including CDEs and key design elements (i.e., methodological or protocol parameters), divided into five sections: (1) patient information, (2) general study information, (3) behavioral interventions, (4) pharmacological interventions, and (5) device interventions. The newly created CRF enhances systematization of future work by proposing a portfolio of measures that should be collected in the development and implementation of studies assessing novel interventions intended to increase the level of consciousness or rate of recovery of consciousness in patients with disorders of consciousness.

Effect of Acupuncture on Recovery of Consciousness in Patients with Acute Traumatic Brain Injury: A Multi-Institutional Cohort Study.

Traumatic brain injury (TBI) causes cognitive dysfunction and long-term impairments. This study aims to examine the effectiveness of acupuncture on the recovery of consciousness in TBI patients. This is a retrospective, multi-institutional cohort study. We enrolled patients with newly diagnosed TBI from 1 January 2007 to 3 August 2021, aged 20 years and older, from the Chang Gung Research Database (CGRD). The outcome was defined based on the difference between the first and last Glasgow Coma Scale (GCS). A total of 2163 TBI patients were analyzed, and 237 (11%) received acupuncture in the treatment period. Generally, the initial GCS was lower in the acupuncture users (11 vs. 14). For the results of our study, a higher proportion of acupuncture patients achieved significant improvement (GCS differences ≥ 3) compared to non-acupuncture users (46.0% vs. 22.4%, p-value < 0.001). The acupuncture users had a 2.11 times higher chance of achieving a significant improvement when considering all assessable covariates (adjusted odds ratio (aOR) 2, 11, 95% confidence interval [CI]: 1.31-3.40; p-value = 0.002). Using 1:1 propensity score matching (PSM), the acupuncture users still had better outcomes than the non-acupuncture users (45.3% vs. 32.9%, p-value = 0.020). In conclusion, this study suggests that acupuncture treatment may be beneficial for TBI patients.

Optimising recovery of consciousness after coma. From bench to bedside and vice versa

BackgroundSeveral methods have been proposed to foster recovery of consciousness in patients with disorders of consciousness (DoC). ObjectiveCritically assess pharmacological and non-pharmacological treatments for patients with chronic DoC. MethodsA narrative mini-review, and critical analysis of the scientific literature on the various proposed therapeutic approaches, with particular attention to level of evidence, risk-benefit ratio, and feasibility. Results and discussionPersonalised sensory stimulation, median nerve stimulation, transcranial direct current stimulation (tDCS), amantadine and zolpidem all have favourable risk-benefit ratios and are easy to implement in clinical practice. These treatments should be proposed to every patient with chronic DoC. Comprehensive patient management should also include regular lifting, pain assessment and treatment, attempts to restore sleep and circadian rhythms, implementation of rest periods, comfort and nursing care, and a rehabilitation program with a multi-disciplinary team with expertise in this field. More invasive treatments may cause adverse effects and require further investigation to confirm preliminary, encouraging results and to better define responders’ intervention parameters. Scientific studies are essential and given the severity of the disability and handicap that results from DoC, research in this area should aim to develop new therapeutic approaches.

A predictive model for consciousness recovery of comatose patients after acute brain injury.

Predicting the consciousness recovery for comatose patients with acute brain injury is an important issue. Although some efforts have been made in the study of prognostic assessment methods, it is still unclear which factors can be used to establish model to directly predict the probability of consciousness recovery. We aimed to establish a model using clinical and neuroelectrophysiological indicators to predict consciousness recovery of comatose patients after acute brain injury. The clinical data of patients with acute brain injury admitted to the neurosurgical intensive care unit of Xiangya Hospital of Central South University from May 2019 to May 2022, who underwent electroencephalogram (EEG) and auditory mismatch negativity (MMN) examinations within 28 days after coma onset, were collected. The prognosis was assessed by Glasgow Outcome Scale (GOS) at 3 months after coma onset. The least absolute shrinkage and selection operator (LASSO) regression analysis was applied to select the most relevant predictors. We combined Glasgow coma scale (GCS), EEG, and absolute amplitude of MMN at Fz to develop a predictive model using binary logistic regression and then presented by a nomogram. The predictive efficiency of the model was evaluated with AUC and verified by calibration curve. The decision curve analysis (DCA) was used to evaluate the clinical utility of the prediction model. A total of 116 patients were enrolled for analysis, of which 60 had favorable prognosis (GOS ≥ 3). Five predictors, including GCS (OR = 13.400, P < 0.001), absolute amplitude of MMN at Fz site (FzMMNA, OR = 1.855, P = 0.038), EEG background activity (OR = 4.309, P = 0.023), EEG reactivity (OR = 4.154, P = 0.030), and sleep spindles (OR = 4.316, P = 0.031), were selected in the model by LASSO and binary logistic regression analysis. This model showed favorable predictive power, with an AUC of 0.939 (95% CI: 0.899-0.979), and calibration. The threshold probability of net benefit was between 5% and 92% in the DCA. This predictive model for consciousness recovery in patients with acute brain injury is based on a nomogram incorporating GCS, EEG background activity, EEG reactivity, sleep spindles, and FzMMNA, which can be conveniently obtained during hospitalization. It provides a basis for care givers to make subsequent medical decisions.

Enhanced brain parcellation via abnormality inpainting for neuroimage-based consciousness evaluation of hydrocephalus patients by lumbar drainage

Brain network analysis based on structural and functional magnetic resonance imaging (MRI) is considered as an effective method for consciousness evaluation of hydrocephalus patients, which can also be applied to facilitate the ameliorative effect of lumbar cerebrospinal fluid drainage (LCFD). Automatic brain parcellation is a prerequisite for brain network construction. However, hydrocephalus images usually have large deformations and lesion erosions, which becomes challenging for ensuring effective brain parcellation works. In this paper, we develop a novel and robust method for segmenting brain regions of hydrocephalus images. Our main contribution is to design an innovative inpainting method that can amend the large deformations and lesion erosions in hydrocephalus images, and synthesize the normal brain version without injury. The synthesized images can effectively support brain parcellation tasks and lay the foundation for the subsequent brain network construction work. Specifically, the novelty of the inpainting method is that it can utilize the symmetric properties of the brain structure to ensure the quality of the synthesized results. Experiments show that the proposed brain abnormality inpainting method can effectively aid the brain network construction, and improve the CRS-R score estimation which represents the patient’s consciousness states. Furthermore, the brain network analysis based on our enhanced brain parcellation method has demonstrated potential imaging biomarkers for better interpreting and understanding the recovery of consciousness in patients with secondary hydrocephalus.

Predicting Long-Term Recovery of Consciousness in Prolonged Disorders of Consciousness Based on Coma Recovery Scale-Revised Subscores: Validation of a Machine Learning-Based Prognostic Index.

Prognosis of prolonged Disorders of Consciousness (pDoC) is influenced by patients' clinical diagnosis and Coma Recovery Scale-Revised (CRS-R) total score. We compared the prognostic accuracy of a novel Consciousness Domain Index (CDI) with that of clinical diagnosis and CRS-R total score, for recovery of full consciousness at 6-, 12-, and 24-months post-injury. The CDI was obtained by a combination of the six CRS-R subscales via an unsupervised machine learning technique. We retrospectively analyzed data on 143 patients with pDoC (75 in Minimally Conscious State; 102 males; median age = 53 years; IQR = 35; time post-injury = 1-3 months) due to different etiologies enrolled in an International Brain Injury Association Disorders of Consciousness Special Interest Group (IBIA DoC-SIG) multicenter longitudinal study. Univariate and multivariate analyses were utilized to assess the association between outcomes and the CDI, compared to clinical diagnosis and CRS-R. The CDI, the clinical diagnosis, and the CRS-R total score were significantly associated with a good outcome at 6, 12 and 24 months. The CDI showed the highest univariate prediction accuracy and sensitivity, and regression models including the CDI provided the highest values of explained variance. A combined scoring system of the CRS-R subscales by unsupervised machine learning may improve clinical ability to predict recovery of consciousness in patients with pDoC.

The temporal dynamics of Large-Scale brain network changes in disorders of consciousness: A Microstate-Based study.

The resting-state brain is composed of several discrete networks, which remain stable for 10-100 ms. These functional microstates are considered the building blocks of spontaneous consciousness. Electroencephalography (EEG) microstate analysis may provide insight into the altered brain dynamics underlying consciousness recovery in patients with disorders of consciousness (DOC). We aimed to analyze microstates in the resting-state EEG source space in patients with DOC, the relationship between state-specific features and consciousness levels, and the corresponding patterns of microstates and functional networks. We obtained resting-state EEG data from 84 patients with DOC (27 in a minimally conscious state [MCS] and 57 in a vegetative state [VS] or with unresponsive wakefulness syndrome). We conducted a microstate analysis of the resting-state (EEG) source space and developed a state-transition analysis protocol for patients with DOC. We identified seven microstates with distinct spatial distributions of cortical activation. Multivariate pattern analyses revealed that different functional connectivity patterns were associated with source-level microstates. There were significant differences in the microstate properties, including spatial activation patterns, temporal dynamics, state shifts, and connectivity construction, between the MCS and VS groups. Our findings suggest that consciousness depends on complex dynamics within the brain and may originate from the anterior cortex.

Quantitative analysis of early-stage EEG reactivity predicts awakening and recovery of consciousness in patients with severe brain injury

BackgroundDecisions of withdrawal of life-sustaining therapy for patients with severe brain injury are often based on prognostic evaluations such as analysis of electroencephalography (EEG) reactivity (EEG-R). However, EEG-R usually relies on visual assessment, which requires neurophysiological expertise and is prone to inter-rater variability. We hypothesised that quantitative analysis of EEG-R obtained 3 days after patient admission can identify new markers of subsequent awakening and consciousness recovery. MethodsIn this prospective observational study of patients with severe brain injury requiring mechanical ventilation, quantitative EEG-R was assessed using standard 11-lead EEG with frequency-based (power spectral density) and functional connectivity-based (phase-lag index) analyses. Associations between awakening in the intensive care unit (ICU) and reactivity to auditory and nociceptive stimulations were assessed with logistic regression. Secondary outcomes included in-ICU mortality and 3-month Coma Recovery Scale-Revised (CRS-R) score. ResultsOf 116 patients, 86 (74%) awoke in the ICU. Among quantitative EEG-R markers, variation in phase-lag index connectivity in the delta frequency band after noise stimulation was associated with awakening (adjusted odds ratio=0.89, 95% confidence interval: 0.81–0.97, P=0.02 corrected for multiple tests), independently of age, baseline severity, and sedation. This new marker was independently associated with improved 3-month CRS-R (adjusted β=−0.16, standard error 0.075, P=0.048), but not with mortality (adjusted odds ratio=1.08, 95% CI: 0.99–1.18, P=0.10). ConclusionsAn early-stage quantitative EEG-R marker was independently associated with awakening and 3-month level of consciousness in patients with severe brain injury. This promising marker based on functional connectivity will need external validation before potential integration into a multimodal prognostic model.

Pharmacologic Therapies to Promote Recovery of Consciousness.

Pharmacologic interventions are commonly used to support rehabilitation efforts of patients with disorders of consciousness (DoC). The 2018 practice guidelines recommend amantadine in adults with traumatic DoC to promote functional recovery, though several other stimulants are used off-label in clinical practice and trials, such as methylphenidate, bromocriptine, levodopa, and zolpidem. Differences in the mechanisms of action, adverse effects, pharmacokinetics, and drug-drug interactions should be considered when selecting the best agent for each individual patient. Overall, pharmacologic stimulants may provide a safe and inexpensive pathway to increased functionality and participation in rehabilitation. This article provides a concise summary of scientific evidence supporting the use of pharmacologic therapies to stimulate recovery of consciousness in patients with DoC.

Mapping outcomes for recovery of consciousness in studies from 1986 to 2020: a scoping review protocol

IntroductionHistorically, heterogeneous outcome assessments have been used to measure recovery of consciousness in patients with disorders of consciousness (DoC) following traumatic brain injury (TBI), making it difficult to compare across...

Anterior precuneus related to the recovery of consciousness

The neural mechanism that enables the recovery of consciousness in patients with unresponsive wakefulness syndrome (UWS) remains unclear. The aim of the current study is to characterize the cortical hub regions related to the recovery of consciousness. In the current fMRI study, voxel-wise degree centrality analysis was adopted to identify the cortical hubs related to the recovery of consciousness, for which a total of 27 UWS patients were recruited, including 13 patients who emerged from UWS (UWS-E), and 14 patients who remained in UWS (UWS-R) at least three months after the experiment performance. Furthermore, other recoverable unconscious states were adopted as validation groups, including three independent N3 sleep datasets (n = 12, 9, 9 respectively) and three independent anesthesia datasets (n = 27, 14, 6 respectively). Spatial similarity of the hub characteristic with the validation groups between the UWS-E and UWS-R was compared using the dice coefficient. Finally, with the cortical regions persistently shown as hubs across UWS-E and validation states, functional connectivity analysis was further performed to explore the connectivity patterns underlying the recovery of consciousness. The results identified four cortical hubs in the UWS-E, which showed significantly higher degree centrality for UWS-E than UWS-R, including the anterior precuneus, left inferior parietal lobule, left inferior frontal gyrus, and left middle frontal gyrus, of which the degree centrality value also positively correlated with the patients’ Glasgow Outcome Scale (GOS) score that assessed global brain functioning outcome after a brain injury. Furthermore, the anterior precuneus was found with significantly higher similarity of hub characteristics as well as functional connectivity patterns between UWS-E and the validation groups. The results suggest that the recovery of consciousness may be relevant to the integrity of cortical hubs in the recoverable unconscious states, especially the anterior precuneus. The identified cortical hub regions could serve as potential treatment targets for patients with UWS.

Evaluation of structural variations in the pituitary gland, hormonal status and laboratory markers of the central nervous system functioning in patients with chronic disorders of consciousness

BACKGROUND: Consciousness is the state of being awake and aware of oneself and the environment. The disorders of consciousness result from pathologies that impair awareness. The development of effective comprehensive personalized interventions contributing to the recovery of consciousness in patients with chronic disorders of consciousness is one of the most pressing and challenging tasks in modern rehabilitation.&#x0D; AIM: The aim of this study was to understand structural problems of the pituitary gland, blood levels of gonadotropins and melatonin as well as brain damage markers in the blood and cerebrospinal fluid in patients with chronic disorders of consciousness and to analyze the levels of the above markers among different groups of patients depending on the level of impaired consciousness.&#x0D; MATERIALS AND METHODS: We examined 61 chronic disorders of consciousness patients and identified three groups depending on the level of consciousness including 24 patients with unresponsive wakefulness syndrome, 24 patients with a minus minimally conscious state, and 13 patients with minimally conscious state plus. We performed magnetic resonance imaging of chiasmatic-sellar region and determined blood serum levels of follicle-stimulating and luteinizing hormones and melatonin, as well as urinary level of 6-sulfatoxymelatonin and the content of brain derived neurotrophic factor (BDNF), apoptosis antigen (APO-1), FasL, glutamate, and S100 protein in the blood serum and cerebrospinal fluid.&#x0D; RESULTS: The patients were examined in the age ranging from 15 to 61 years old. Patient groups were homogeneous by the level of consciousness in terms of age and duration of chronic disorders of consciousness by the time of examination. The patients did not differ in the pituitary volume regardless of the level of consciousness. No significant differences were found between the groups with different levels of consciousness when studying the levels of melatonin in the blood serum and its metabolite in the urine. A peak in melatonin secretion was detected at 3 a.m. in 54.5 % of the patients, which can be considered as a favorable prognostic marker for further recovery of consciousness. Hypogonadotropic ovarian failure was found in 34 % of the patients, with normogonadotropic ovarian failure in the remaining patients. Serum APO-1 and BDNF levels were significantly higher in patients with minimally conscious state relative to those with unresponsive wakefulness syndrome. Significantly lower levels of glutamate in the cerebrospinal fluid were detected in women with unresponsive wakefulness syndrome compared to patients with minimally conscious state.&#x0D; CONCLUSIONS: Further in-depth examination and accumulation of data on patients with chronic disorders of consciousness may provide an opportunity to identify highly informative markers for predicting outcomes and to develop new effective approaches to rehabilitation of consciousness in this category of patients.

Spatio-temporal analysis of EEG features during consciousness recovery in patients with disorders of consciousness

ObjectiveAs consciousness recovery is not only dynamic but also involves interactions between various brain regions, elucidating the mechanism of recovery requires tracking cortical activity in spatio-temporal dimensions. MethodsWe tracked the cortical activities of 40 patients (mean age: 54.38 years; 28 males; 21 patients with minimally conscious states) with disorders of consciousness, and collected a total of 156 electroencephalographic signals. We investigated the longitudinal changes in EEG nonlinear dynamic features (i.e., approximate entropy, sample entropy, and Lempel-Ziv complexity) and relative wavelet energy along with consciousness recovery. ResultsGlobal EEG features showed a non-monotonic trend during consciousness recovery (P < 0.05). When the level of consciousness of patients was transferred to a minimally conscious state from an unresponsive wakefulness syndrome/ vegetative state, an inflection point appeared in the EEG features. The EEG feature change trends between the injured and uninjured areas were dissimilar (P < 0.05). Importantly, the degree of dissimilarity increased non-monotonically across the levels of consciousness (P < 0.05). ConclusionsEEG recovery was non-monotonic and dissimilar in spatio-temporal dimensions, with an inflection point. SignificanceThese findings further clarify the process of consciousness recovery and provide assistance in exploring the mechanism of consciousness recovery.

Нейромедіаторні механізми відновлення свідомості у пацієнтів із тяжкою черепно-мозковою травмою

Актуальність. Одним із перспективних напрямків постішемічної корекції церебрального гомео­стазу є застосування препаратів, спрямованих на переривання швидких реакцій глутаматкальцієвого каскаду. До препаратів із глутаматблокуючою дією належить амантадин, неконкуруючий антагоніст дофамінових і NMDA-рецепторів. Він справляє стабілізуючий вплив на специфічні глутаматергічні рецептори, що переривають наростання глутаматного викиду і пригнічують глутаматну ексайтотоксичність. Подібний ефект доведено і для унікального ноотропного препарату — N-карбамоїл-метил-4-феніл-2-піролідону (фенілпірацетам). Механізми реалізації ефектів фенілпірацетаму визначаються посиленням синтезу білка і фосфоліпідів, підвищенням швидкості обороту інформаційних молекул, полімодальним впливом на широкий діапазон синаптичних систем — холінергічну, адренергічну, дофамінергічну, глутаматергічну і, найголовніше, ГАМКергічну. Мета — вивчення нейромедіаторних механізмів відновлення свідомості в пацієнтів із тяжкою черепно-мозковою травмою. Матеріали та методи. Дослідження проводили у 2010–2015 роках в ДоКТМО на базі кафедри анестезіології та інтенсивної терапії ФІПО Донецького національного медичного університету ім. М. Горького. 1-ша група (порівняння) складалася з 30 пацієнтів, які отримували терапію за стандартним протоколом. 2-га група (дослідження) складалася з 30 хворих, які отримували, крім терапії за протоколом, препарат амантадин, що застосовували в першу добу після отримання травми у вигляді інфузійного розчину в дозі 1000 мл (400 мг) на добу внутрішньовенно повільно крапельно протягом 7 діб. 3-тя група (дослідження) складалася з 32 хворих, які отримували, крім терапії за протоколом, препарат фенілпірацетам через зонд один раз на добу. Оцінювали рівень свідомості за шкалою коми Глазго. Застосовували комп’ютерний цифровий енцефалограф NIHON KOHDEN EEG-1200. Для оцінки динаміки нейрофізіологічних змін вивчали усереднені показники спектрального аналізу електроенцефалографії за 8 відведеннями, зокрема спектральну потужність із частотою 1 Гц (діяльність нейрогліальної популяції), 6–7,5 Гц (холінергічна система), 4–5 Гц (адренергічна система), 11–12 Гц (дофамінергічна система), 24–25 Гц (β2) (серотонінергічна система). Усі отримані дані оброблялися з використанням методів математичної статистики із застосуванням кореляційного аналізу. Результати. Зафіксовані нами у відповідь на застосування амантадину і фенілпірацетаму ЕЕГ-зміни (зниження δ-, підвищення α- і β1- і β2-ритмів) відображали зменшення активності глутаматергічної ней­ромедіаторної системи, що є одним із механізмів відновлення свідомості при тяжкій ЧМТ. Інтенсивна терапія із застосуванням амантадину у хворих із тяжкою черепно-мозковою травмою відновлює нейромедіаторний баланс: підвищує дофамінергічну активність, переважно в проекції стовбурових структур, активує холінергічну нейромедіаторну систему, переважно в проекції так званої когнітивної осі, що є ще одним із механізмів відновлення свідомості. У пацієнтів із тяжкою ЧМТ після введення фенілпірацетаму була зафіксована значна активація переважно серотонінергічної системи мозку з гіперпродукцією серотоніну, прискоренням процесів метаболізму в нейрогліальній популяції і помірними асиметричними ангіоспастичними ефектами, що також є одним із механізмів відновлення свідомості. Застосування додатково до стандартного протоколу лікування амантадину і фенілпірацетаму підвищувало шанс відновлення свідомості до 11 і більше балів за шкалою коми Глазго вже на 7-му добу терапії (ОR ± 95% ДІ = 5,5 (2,8–13,2) і ОR ± 95% ДІ = 0,626 (0,219–1,000) відповідно). Використання амантадину і фенілпірацетаму в гострому періоді тяжкої ЧМТ обумовлювало статистично значуще зниження ризику смерті (RR ± 95% ДІ = 0,273 (0,084–0,881) і RR ± 95% ДІ = 0,426 (0,168–1,000) відповідно).

Clinical significance of mismatch negativity in predicting the awakening of comatose patients after severe brain injury.

We assessed the clinical significance of mismatch negativity (MMN) in predicting the awakening of comatose patients with severe brain injury. The clinical data of patients with severe brain injury, admitted to the neurosurgical intensive care unit of Xiangya Hospital of Central South University from July 2018 to March 2020, who underwent auditory MMN examinations within 28 days after coma onset, were reviewed. Correlations between clinical factors and prognosis [Glasgow Outcome Scale (GCS) for 3 mo] were analyzed. Fifty-three patients were included; 37 (69.8%) had favorable outcomes. A univariate analysis revealed the Glasgow Coma Scale (GCS) and absolute MMN amplitudes at electrodes Fz and Cz were significantly correlated with prognosis. Only GCS scores and MMN amplitude at Fz were independent predictors in multivariate logistic regression analysis (area under the curve 0.744 vs. 0.753, respectively); both combined, improved accuracy to 84.6%. MMN amplitudes at Fz were dichotomized at a value of 1.08 μV with a sensitivity and specificity of 81.1% and 68.7%, respectively, for predicting comatose patients' awakening. In conclusion, MMN amplitude at Fz is a reliable prognostic indicator for comatose patients with severe brain injury; the prediction value improved when combined with GCS. Thus, an event-related potential component with a clear site and cutoff value may support prognostication in severe brain injury.NEW & NOTEWORTHY Mismatch negativity (MMN) can assess the prognosis of comatose patients after severe brain injury, especially for MMN amplitude. In addition, MMN analysis at electrode Fz best predicts recovery of consciousness in patients with severe brain injury. Importantly, a quantitative approach (cutoff value of 1.08 μV) may improve the use of MMN for prognostication.