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Lanzone J, Motolese F, Ricci L, Tecchio F, Tombini M, Zappasodi F, Cruciani A, Capone F, Di Lazzaro V, Assenza G. Quantitative measures of the resting EEG in stroke: a systematic review on clinical correlation and prognostic value. Neurol Sci 2023; 44:4247-4261. [PMID: 37542545 DOI: 10.1007/s10072-023-06981-9] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2022] [Accepted: 07/26/2023] [Indexed: 08/07/2023]
Abstract
OBJECT Quantitative electroencephalography (qEEG) has shown promising results as a predictor of clinical impairment in stroke. We systematically reviewed published papers that focus on qEEG metrics in the resting EEG of patients with mono-hemispheric stroke, to summarize current knowledge and pave the way for future research. METHODS Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, we systematically searched the literature for papers that fitted our inclusion criteria. Rayyan QCRR was used to allow deduplication and collaborative blinded paper review. Due to multiple outcomes and non-homogeneous literature, a scoping review approach was used to address the topic. RESULTS Or initial search (PubMed, Embase, Google scholar) yielded 3200 papers. After proper screening, we selected 71 papers that fitted our inclusion criteria and we developed a scoping review thar describes the current state of the art of qEEG in stroke. Notably, among selected papers 53 (74.3%) focused on spectral power; 11 (15.7%) focused on symmetry indexes, 17 (24.3%) on connectivity metrics, while 5 (7.1%) were about other metrics (e.g. detrended fluctuation analysis). Moreover, 42 (58.6%) studies were performed with standard 19 electrodes EEG caps and only a minority used high-definition EEG. CONCLUSIONS We systematically assessed major findings on qEEG and stroke, evidencing strengths and potential pitfalls of this promising branch of research.
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Affiliation(s)
- J Lanzone
- Istituti Clinici Scientifici Maugeri IRCCS, Neurorehabilitation Department of the Milano Institute, Milan, Italy.
| | - F Motolese
- Department of Medicine and Surgery, Unit of Neurology, Neurophysiology, Neurobiology and Psichiatry, Università Campus Bio-Medico di Roma, Via Alvaro del Portillo, 21, 00128, Rome, Italy
- Fondazione Policlinico Universitario Campus Bio-Medico, Via Alvaro del Portillo, 200, 00128, Roma, Italy
| | - L Ricci
- Department of Medicine and Surgery, Unit of Neurology, Neurophysiology, Neurobiology and Psichiatry, Università Campus Bio-Medico di Roma, Via Alvaro del Portillo, 21, 00128, Rome, Italy
- Fondazione Policlinico Universitario Campus Bio-Medico, Via Alvaro del Portillo, 200, 00128, Roma, Italy
| | - F Tecchio
- Laboratory of Electrophysiology for Translational Neuroscience LET'S, Institute of Cognitive Sciences and Technologies ISTC, Consiglio Nazionale Delle Ricerche CNR, Rome, Italy
| | - M Tombini
- Department of Medicine and Surgery, Unit of Neurology, Neurophysiology, Neurobiology and Psichiatry, Università Campus Bio-Medico di Roma, Via Alvaro del Portillo, 21, 00128, Rome, Italy
- Fondazione Policlinico Universitario Campus Bio-Medico, Via Alvaro del Portillo, 200, 00128, Roma, Italy
| | - F Zappasodi
- Department of Neuroscience, Imaging and Clinical Sciences and Institute for Advanced Biomedical Technologies, 'Gabriele D'Annunzio' University, Chieti, Italy
| | - A Cruciani
- Department of Medicine and Surgery, Unit of Neurology, Neurophysiology, Neurobiology and Psichiatry, Università Campus Bio-Medico di Roma, Via Alvaro del Portillo, 21, 00128, Rome, Italy
- Fondazione Policlinico Universitario Campus Bio-Medico, Via Alvaro del Portillo, 200, 00128, Roma, Italy
| | - F Capone
- Department of Medicine and Surgery, Unit of Neurology, Neurophysiology, Neurobiology and Psichiatry, Università Campus Bio-Medico di Roma, Via Alvaro del Portillo, 21, 00128, Rome, Italy
- Fondazione Policlinico Universitario Campus Bio-Medico, Via Alvaro del Portillo, 200, 00128, Roma, Italy
| | - V Di Lazzaro
- Department of Medicine and Surgery, Unit of Neurology, Neurophysiology, Neurobiology and Psichiatry, Università Campus Bio-Medico di Roma, Via Alvaro del Portillo, 21, 00128, Rome, Italy
- Fondazione Policlinico Universitario Campus Bio-Medico, Via Alvaro del Portillo, 200, 00128, Roma, Italy
| | - G Assenza
- Department of Medicine and Surgery, Unit of Neurology, Neurophysiology, Neurobiology and Psichiatry, Università Campus Bio-Medico di Roma, Via Alvaro del Portillo, 21, 00128, Rome, Italy
- Fondazione Policlinico Universitario Campus Bio-Medico, Via Alvaro del Portillo, 200, 00128, Roma, Italy
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Jiang M, Niu Z, Liu G, Huang H, Li X, Su Y. Quantitative EEG and brain network analysis: predicting awakening from early coma after cardiopulmonary resuscitation. Neurol Res 2023; 45:969-978. [PMID: 37643397 DOI: 10.1080/01616412.2023.2252281] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2023] [Accepted: 08/21/2023] [Indexed: 08/31/2023]
Abstract
OBJECTIVE For patients in early coma after cardiopulmonary resuscitation (CPR), quantitative electroencephalogram (EEG) and brain network analysis was performed to identify relevant indicators of awakening. METHODS A prospective cohort study was conducted on comatose patients after CPR in the neuro-critical care unit. The included patients received clinical evaluation. The bedside high-density (64-lead) EEG monitoring was performed for visual grading and calculation of power spectrum and brain network parameters. A 3-month prognostic assessment was performed and the patients were dichotomized into the awakening group and the unawakening group. RESULTS A total of 25 patients were included. The awakening group had higher GCS score, more slow wave pattern and reactive EEG than the unawakening group (P = 0.003, P < 0.001, P < 0.001, respectively). Compared with the unawakening group, (1) the awakening group had significantly higher absolute and relative θ power and slow/fast band ratio of the whole brain (P < 0.05), (2) the awakening group had stronger connection based on coherence, phase synchronization, phase lag index and cross-correlation (P < 0.05), (3) the awakening group had higher small-worldness, clustering coefficient and average path length based on graph theory (P < 0.05). CONCLUSIONS The power spectrum and brain network characteristics in patients in early coma after CPR have predictive value for recovery.
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Affiliation(s)
- Mengdi Jiang
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China
- Currently working at Department of Neurology, Beijing Hospital, National Center of Gerontology, Beijing, China
| | - Zikang Niu
- State Key Laboratory of Cognitive Neuroscience and Learning and IDG/McGovern, Beijing Normal University, Beijing, China
| | - Gang Liu
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Huijin Huang
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Xiaoli Li
- State Key Laboratory of Cognitive Neuroscience and Learning and IDG/McGovern, Beijing Normal University, Beijing, China
| | - Yingying Su
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China
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Wang Y, Ren J, Yao Z, Wang W, Wang S, Duan J, Li Z, Zhang H, Zhang R, Wang X. Clinical Impact and Risk Factors of Intensive Care Unit-Acquired Nosocomial Infection: A Propensity Score-Matching Study from 2018 to 2020 in a Teaching Hospital in China. Infect Drug Resist 2023; 16:569-579. [PMID: 36726386 PMCID: PMC9885966 DOI: 10.2147/idr.s394269] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2022] [Accepted: 01/05/2023] [Indexed: 01/27/2023] Open
Abstract
Purpose Nosocomial infection (NI) is associated with poor prognosis. The present study assessed the clinical and microbiological characteristics of NI patients in the intensive care unit (ICU) and investigated the clinical impact and risk factors for NI in ICU patients. Patients and Methods An observational study was conducted in an adult general ICU. The electronic medical records of all patients admitted to the ICU for >2 days from 2018-2020 were analyzed retrospectively. Multivariate regression models were used to analyze the risk factors for NI in ICU patients. Propensity score-matching (PSM) was used to control the confounding factors between the case and control groups, thus analyzing the clinical impact of NIs. Results The present study included 2425 patient admissions, of which 231 (9.53%) had NI. Acinetobacter baumannii (33.0%) was the most common bacteria. Long-term immunosuppressive therapy, disturbance of consciousness, blood transfusion, multiple organ dysfunction syndromes (MODS), treatment with three or more antibiotics, mechanical ventilation (MV), tracheotomy, the urinary catheter (UC), nasogastric catheter, and central venous catheter (CVC) were risk factors for NI in the ICU patients. After PSM, patients with NI had a prolonged length of stay (LOS) in the ICU and hospital, significant hospitalization expenses (all p<0.001), increased mortality (p=0.027), and predicted mortality (p=0.007). The differences in the ICU and hospital LOSs among three pathogens were statistically significant (p<0.001); the results of the Escherichia coli infection group were lower than the other two pathogenic groups. Conclusion NI was associated with poor outcomes. The risk factors for NI identified in this study provided further insight into preventing NI.
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Affiliation(s)
- Yanhui Wang
- College of Pharmacy, Shanxi Medical University, Taiyuan, Shanxi, People’s Republic of China
| | - Jian Ren
- Department of Pharmacy, Second Hospital of Shanxi Medical University, Taiyuan, Shanxi, People’s Republic of China
| | - Zhiqing Yao
- College of Pharmacy, Shanxi Medical University, Taiyuan, Shanxi, People’s Republic of China
| | - Wei Wang
- Intensive Care Unit, Second Hospital of Shanxi Medical University, Taiyuan, Shanxi, People’s Republic of China
| | - Siyang Wang
- Department of Pharmacy, Second Hospital of Shanxi Medical University, Taiyuan, Shanxi, People’s Republic of China
| | - Junfang Duan
- Intensive Care Unit, Second Hospital of Shanxi Medical University, Taiyuan, Shanxi, People’s Republic of China
| | - Zhen Li
- College of Pharmacy, Chonnam National University, Gwangju, Korea
| | - Huizi Zhang
- College of Pharmacy, Shanxi Medical University, Taiyuan, Shanxi, People’s Republic of China
| | - Ruiqin Zhang
- Department of Pharmacy, Second Hospital of Shanxi Medical University, Taiyuan, Shanxi, People’s Republic of China,Correspondence: Ruiqin Zhang; Xiaoru Wang, Email ;
| | - Xiaoru Wang
- Intensive Care Unit, Second Hospital of Shanxi Medical University, Taiyuan, Shanxi, People’s Republic of China
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Su Y, Teng J, Tian F, Jing J, Huang H, Pan S, Jiang W, Wang F, Zhang L, Zhang Y, Zhang M, Liu L, Cao J, Hu H, Li W, Liang C, Ma L, Meng X, Tian L, Wang C, Wang L, Wang Y, Wang Z, Wang Z, Xie Z, You M, Yuan J, Zeng C, Zeng L, Zhang L, Zhang X, Zhang Y, Zhao B, Zhou S, Zhou Z. The development of neurocritical care in China from the perspective of evaluation and treatment of critical neurological diseases. Front Neurol 2023; 14:1114204. [PMID: 36895910 PMCID: PMC9990414 DOI: 10.3389/fneur.2023.1114204] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2022] [Accepted: 01/12/2023] [Indexed: 02/23/2023] Open
Abstract
Objective To understand the varieties, evaluation, treatment, and prognosis of severe neurological diseases using the third NCU survey in China. Design A cross-sectional questionnaire study. The study was completed in three main steps: filling in the questionnaire, sorting out the survey data, and analyzing the survey data. Results Of 206 NCUs, 165 (80%) provided relatively complete information. It was estimated that 96,201 patients with severe neurological diseases were diagnosed and treated throughout the year, with an average fatality rate of 4.1%. The most prevalent severe neurological disease was cerebrovascular disease (55.2%). The most prevalent comorbidity was hypertension (56.7%). The most prevalent complication was hypoproteinemia (24.2%). The most common nosocomial infection was hospital-acquired pneumonia (10.6%). The GCS, APACHE II, EEG, and TCD were the most commonly used (62.4-95.2%). The implementation rate of the five nursing evaluation techniques reached 55.8-90.9%. Routinely raising the head of the bed by 30°, endotracheal intubation and central venous catheterization were the mostprevalent treatment strategies (97.6, 94.5, and 90.3%, respectively). Traditional tracheotomy, invasive mechanical ventilation and nasogastric tube feeding (75.8, 95.8, and 95.8%, respectively) were more common than percutaneous tracheotomy, non-invasive mechanical ventilation and nasogastric tube insertion (57.6, 57.6, and 66.7%, respectively). Body surface hypothermia brain protection technology was more commonly used than intravascular hypothermia technology (67.3 > 6.1%). The rates of minimally invasive hematoma removal and ventricular puncture were only 40.0 and 45.5%, respectively. Conclusion In addition to traditional recognized basic life assessment and support technology, it is necessary to the use of promote specialized technology for neurological diseases, according to the characteristics of critical neurological diseases.
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Affiliation(s)
- Yingying Su
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Junfang Teng
- Department of Neurology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Fei Tian
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Jing Jing
- Department of Neurology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Huijin Huang
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Suyue Pan
- Department of Neurology, Nanfang Hospital of Southern Medical University, Guangzhou, China
| | - Wen Jiang
- Department of Neurology, Xijing Hospital Fourth Military Medical University, Xi'an, China
| | - Furong Wang
- Department of Neurology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Le Zhang
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, China
| | - Yan Zhang
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Meng Zhang
- Department of Neurology, Daping Hospital, The Army Military Medical University, Chongqing, China
| | - Liping Liu
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Jie Cao
- Department of Neurology, The First Hospital of Jilin University, Changchun, China
| | - Huaiqiang Hu
- Department of Neurology, The 960(th) Hospital of Joint Logistics Support, PLA, Jinan, China
| | - Wei Li
- Department of Neurology, Daping Hospital, The Army Military Medical University, Chongqing, China
| | - Cheng Liang
- Department of Neurology, The Second Hospital of Lanzhou University, Lanzhou, China
| | - Liansheng Ma
- Department of Neurology, The First Hospital of Shanxi Medical University, Taiyuan, China
| | - Xuegang Meng
- Department of Neurology, The Xinjiang Uygur Autonomous Region People's Hospital, Urumqi, China
| | - Linyu Tian
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, China
| | - Changqing Wang
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Lihua Wang
- Department of Neurology, The Second Affiliated Hospital, Harbin Medical University, Harbin, China
| | - Yan Wang
- Department of Neurology, Tangshan People's Hospital of Hebei Province, Tangshan, China
| | - Zhenhai Wang
- Neurology Center, General Hospital of Ningxia Medical University, Yinchuan, China
| | - Zhiqiang Wang
- Department of Neurology, The First Affiliated Hospital of Fujian Medical University, Fuzhou, China
| | - Zunchun Xie
- Department of Neurology, The First Affiliated Hospital of Nanchang University, Nanchang, China
| | - Mingyao You
- Department of Neurology, The Affiliated Hospital of Guizhou Medical University, Guiyang, China
| | - Jun Yuan
- Department of Neurology, Inner Mongolia People's Hospital, Hohhot, China
| | - Chaosheng Zeng
- Department of Neurology, The Second Affiliated Hospital of Hainan Medical University, Haikou, China
| | - Li Zeng
- Department of Neurology, The Affiliated Hospital of Guangxi Medical University, Nanning, China
| | - Lei Zhang
- Department of Neurology, The First People's Hospital of Yunnan Province, Kunming, China
| | - Xin Zhang
- Department of Neurology, Nanjing Drum Tower Hospital, Nanjing, China
| | - Yongwei Zhang
- Department of Neurovascular Center, Changhai Hospital, Naval Medical University, Shanghai, China
| | - Bin Zhao
- Department of Neurology, Tianjin Medical University General Hospital, Tianjin, China
| | - Saijun Zhou
- Department of Neurology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Zhonghe Zhou
- Department of Neurology, General Hospital of Northern Theater Command, Shenyang, China
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Bistriceanu CE, Danciu FA, Cuciureanu DI. Cortical connectivity in stroke using signals from resting-state EEG: a review of current literature. Acta Neurol Belg 2022; 123:351-357. [PMID: 36190646 DOI: 10.1007/s13760-022-02102-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2022] [Accepted: 09/20/2022] [Indexed: 11/25/2022]
Abstract
INTRODUCTION Stroke is considered a substantial cause of disability worldwide and many researches are focused on rehabilitative interventions. Functional magnetic resonance imaging studies centered on brain networks after stroke describe affected functional connectivity between areas within the default mode, sensorimotor, visual, fronto-parietal and executive networks. Recent studies renewed the perspective of utilizing electroencephalography to describe markers of cortical activity in stroke and recovery neurophysiological processes. METHODS We included in our research studies realized on patients that had an ischemic or hemorrhagic stroke that performed electroencephalography and had an analysis of connectivity indices. Resting-state electroencephalography has the advantage of including patients with any neurological deficit and it is easier to perform than the task-based variant. The changes in resting-state EEG networks after stroke are important to determine a relationship between frequency cortical activity and spatial conformation of a network. From conventional to quantitative EEG analysis in stroke, these techniques are improved with additional brain connectivity tools that lead to a better characterization between injured areas and other intra- and inter-hemispheric areas. RESULTS There are studies that underline the disruptions in local networks in a frequency-dependent modality after stroke, while other results are focused on bilateral changes in resting-state cortical networks, independent of the side of the lesions. CONCLUSIONS Many studies found alterations in various connectivity measures after stroke with the help of EEG, but the clinical significance of these findings is a field of increasing interest in research area.
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Affiliation(s)
- Cătălina Elena Bistriceanu
- Elytis Hospital Hope, Iasi, Romania.
- Neurology Department, Faculty of Medicine, "Grigore T. Popa" University of Medicine and Pharmacy, Iasi, Romania.
| | | | - Dan Iulian Cuciureanu
- Prof. Dr. N. Oblu" Neurosurgery Clinical Emergency Hospital, Iasi, Romania
- Neurology Department, Faculty of Medicine, "Grigore T. Popa" University of Medicine and Pharmacy, Iasi, Romania
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Xu F, Li J, Dong G, Li J, Chen X, Zhu J, Hu J, Zhang Y, Yue S, Wen D, Leng J. EEG decoding method based on multi-feature information fusion for spinal cord injury. Neural Netw 2022; 156:135-151. [DOI: 10.1016/j.neunet.2022.09.016] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2022] [Revised: 09/13/2022] [Accepted: 09/15/2022] [Indexed: 10/14/2022]
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Functional Connectivity Increases in Response to High-Definition Transcranial Direct Current Stimulation in Patients with Chronic Disorder of Consciousness. Brain Sci 2022; 12:brainsci12081095. [PMID: 36009158 PMCID: PMC9405975 DOI: 10.3390/brainsci12081095] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2022] [Revised: 08/10/2022] [Accepted: 08/16/2022] [Indexed: 11/17/2022] Open
Abstract
Highlights Functional connectivity induced by HD-tDCS in DLPFC has different trends in CRS-R score improvers and non-improvers. An increase in theta PLV in the left frontal–parietooccipital region was significantly associated with CRS-R changes. DOC patients with increased PLV of the alpha band in the intra-bifrontal region have a better prognosis than those without.
Abstract High-definition transcranial direct current stimulation (HD-tDCS) has been shown to play an important role in improving consciousness in patients with disorders of consciousness (DOCs), but its neuroelectrophysiological evidence is still lacking. To better explain the electrophysiological mechanisms of the effects of HD-tDCS on patients with DOCs, 22 DOC patients underwent 10 anodal HD-tDCS sessions of the left dorsolateral prefrontal cortex (DLPFC). This study used the Coma Recovery Scale-Revised (CRS-R) to assess the level of consciousness in DOC patients. According to whether the CRS-R score increased before and after stimulation, DOC patients were divided into a responsive group and a non-responsive group. By comparing the differences in resting-state EEG functional connectivity between different frequency bands and brain regions, as well as the relationship between functional connectivity values and clinical scores, the electrophysiological mechanism of the clinical effects of HD-tDCS was further explored. The change of the phase locking value (PLV) on the theta frequency band in the left frontal–parietooccipital region was positively correlated with the change in the CRS-R scores. As the number of interventions increased, we observed that in the responsive group, the change in PLV showed an upward trend, and the increase in the PLV appeared in the left frontal–parietooccipital region at 4–8 Hz and in the intra-bifrontal region at 8–13 Hz. In the non-responsive group, although the CRS-R scores did not change after stimulation, the PLV showed a downward trend, and the decrease in the PLV appeared in the intra-bifrontal region at 8–13 Hz. In addition, at the three-month follow-up, patients with increased PLV in the intra-bifrontal region at 8–13 Hz after repeated HD-tDCS stimulation had better outcomes than those without. Repeated anodal stimulation of the left DLPFC with HD-tDCS resulted in improved consciousness in some patients with DOCs. The increase in functional connectivity in the brain regions may be associated with the improvement of related awareness after HD-tDCS and may be a predictor of better long-term outcomes.
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Huang H, Su Y, Niu Z, Liu G, Li X, Jiang M. Comatose Patients After Cardiopulmonary Resuscitation: An Analysis Based on Quantitative Methods of EEG Reactivity. Front Neurol 2022; 13:877406. [PMID: 35720067 PMCID: PMC9205205 DOI: 10.3389/fneur.2022.877406] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2022] [Accepted: 05/10/2022] [Indexed: 11/13/2022] Open
Abstract
Objective Every year, approximately 50–110/1,00,000 people worldwide suffer from cardiac arrest, followed by hypoxic-ischemic encephalopathy after cardiopulmonary resuscitation (CPR), and approximately 40–66% of patients do not recover. The purpose of this study was to identify the brain network parameters and key brain regions associated with awakening by comparing the reactivity characteristics of the brain networks between the awakening and unawakening groups of CPR patients after coma, thereby providing a basis for further awakening interventions. Method This study involved a prospective cohort study. Using a 64-electrode electroencephalography (EEG) wireless 64A system, EEG signals were recorded from 16 comatose patients after CPR in the acute phase (<1 month) from 2019 to 2020. MATLAB (2017b) was used to quantitatively analyze the reactivity (power spectrum and entropy) and brain network characteristics (coherence and phase lag index) after pain stimulation. The patients were divided into an awakening group and an unawakening group based on their ability to execute commands or engage in repeated and continuous purposeful behavior after 3 months. The above parameters were compared to determine whether there were differences between the two groups. Results (1) Power spectrum: the awakening group had higher gamma, beta and alpha spectral power after pain stimulation in the frontal and parietal lobes, and lower delta and theta spectral power in the bilateral temporal and occipital lobes than the unawakening group. (2) Entropy: after pain stimulation, the awakening group had higher entropy in the frontal and parietal lobes and lower entropy in the temporal occipital lobes than the unawakening group. (3) Connectivity: after pain stimulation, the awakening group had stronger gamma and beta connectivity in nearly the whole brain, but weaker theta and delta connectivity in some brain regions (e.g., the frontal-occipital lobe and parietal-occipital lobe) than the unawakening group. Conclusion After CPR, comatose patients were more likely to awaken if there was a higher stimulation of fast-frequency band spectral power, higher entropy, stronger whole-brain connectivity and better retention of frontal-parietal lobe function after pain stimulation.
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Affiliation(s)
- Huijin Huang
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Yingying Su
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China
- *Correspondence: Yingying Su
| | - Zikang Niu
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern, Beijing Normal University, Beijing, China
- Zikang Niu
| | - Gang Liu
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China
- Gang Liu
| | - Xiaoli Li
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern, Beijing Normal University, Beijing, China
| | - Mengdi Jiang
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China
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Han J, Chen C, Zheng S, Yan X, Wang C, Wang K, Hu Y. High-Definition Transcranial Direct Current Stimulation of the Dorsolateral Prefrontal Cortex Modulates the Electroencephalography Rhythmic Activity of Parietal Occipital Lobe in Patients With Chronic Disorders of Consciousness. Front Hum Neurosci 2022; 16:889023. [PMID: 35712532 PMCID: PMC9196904 DOI: 10.3389/fnhum.2022.889023] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2022] [Accepted: 05/10/2022] [Indexed: 11/13/2022] Open
Abstract
BackgroundDisorders of consciousness (DOC) are a spectrum of pathologies affecting one’s ability to interact with the external world. At present, High-Definition Transcranial Direct Current Stimulation (HD-tDCS) is used in many patients with DOC as a non-invasive treatment, but electrophysiological research on the effect of HD-tDCS on patients with DOC is limited.ObjectivesTo explore how HD-tDCS affects the cerebral cortex and examine the possible electrophysiological mechanisms underlying the effects of HD-tDCS on the cerebral cortex.MethodsA total of 19 DOC patients were assigned to HD-tDCS stimulation. Each of them underwent 10 anodal HD-tDCS sessions of the left dorsolateral prefrontal cortex (DLPFC) over 5 consecutive days. Coma Recovery Scale-Revision (CRS-R) scores were recorded to evaluate the consciousness level before and after HD-tDCS, while resting-state electroencephalography (EEG) recordings were obtained immediately before and after single and multiple HD-tDCS stimuli. Depending on whether the CRS-R score increased after stimulation, we classified the subjects into responsive (RE) and non-responsive (N-RE) groups and compared the differences in power spectral density (PSD) between the groups in different frequency bands and brain regions, and also examined the relationship between PSD values and CRS-R scores.ResultsFor the RE group, the PSD value of the parieto-occipital region increased significantly in the 6–8 Hz frequency band after multiple stimulations by HD-tDCS. After a single stimulation, an increase in PSD was observed at 10–13 and 13–30 Hz. In addition, for all subjects, a positive correlation was observed between the change in PSD value in the parieto-occipital region at 10–13 and 6–8 Hz frequency band and the change in CRS-R score after a single stimulation.ConclusionRepeated anodal HD-tDCS of the left DLPFC can improve clinical outcomes in patients with DOC, and HD-tDCS-related increased levels of consciousness were associated with increased parieto-occipital PSD.
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Affiliation(s)
- Jinying Han
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Hefei, China
- Collaborative Innovation Center of Neuropsychiatric Disorders and Mental Health, Hefei, China
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China
- The School of Mental Health and Psychological Sciences, Anhui Medical University, Hefei, China
| | - Chen Chen
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Hefei, China
- Collaborative Innovation Center of Neuropsychiatric Disorders and Mental Health, Hefei, China
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China
- The School of Mental Health and Psychological Sciences, Anhui Medical University, Hefei, China
| | - Shuang Zheng
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Hefei, China
- Collaborative Innovation Center of Neuropsychiatric Disorders and Mental Health, Hefei, China
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China
- The School of Mental Health and Psychological Sciences, Anhui Medical University, Hefei, China
| | - Xiaoxiang Yan
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Changqing Wang
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Kai Wang
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Hefei, China
- Collaborative Innovation Center of Neuropsychiatric Disorders and Mental Health, Hefei, China
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China
- The School of Mental Health and Psychological Sciences, Anhui Medical University, Hefei, China
- Hefei Comprehensive National Science Center, Institute of Artificial Intelligence, Hefei, China
- *Correspondence: Kai Wang,
| | - Yajuan Hu
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Hefei, China
- Collaborative Innovation Center of Neuropsychiatric Disorders and Mental Health, Hefei, China
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China
- The School of Mental Health and Psychological Sciences, Anhui Medical University, Hefei, China
- Yajuan Hu,
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Holker R, Susan S. Computer-Aided Diagnosis Framework for ADHD Detection Using Quantitative EEG. Brain Inform 2022. [DOI: 10.1007/978-3-031-15037-1_19] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/15/2022] Open
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Sarasso S, Casali AG, Casarotto S, Rosanova M, Sinigaglia C, Massimini M. Consciousness and complexity: a consilience of evidence. Neurosci Conscious 2021; 2021:niab023. [PMID: 38496724 PMCID: PMC10941977 DOI: 10.1093/nc/niab023] [Citation(s) in RCA: 32] [Impact Index Per Article: 10.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2021] [Revised: 06/19/2021] [Accepted: 07/29/2021] [Indexed: 03/19/2024] Open
Abstract
Over the last years, a surge of empirical studies converged on complexity-related measures as reliable markers of consciousness across many different conditions, such as sleep, anesthesia, hallucinatory states, coma, and related disorders. Most of these measures were independently proposed by researchers endorsing disparate frameworks and employing different methods and techniques. Since this body of evidence has not been systematically reviewed and coherently organized so far, this positive trend has remained somewhat below the radar. The aim of this paper is to make this consilience of evidence in the science of consciousness explicit. We start with a systematic assessment of the growing literature on complexity-related measures and identify their common denominator, tracing it back to core theoretical principles and predictions put forward more than 20 years ago. In doing this, we highlight a consistent trajectory spanning two decades of consciousness research and provide a provisional taxonomy of the present literature. Finally, we consider all of the above as a positive ground to approach new questions and devise future experiments that may help consolidate and further develop a promising field where empirical research on consciousness appears to have, so far, naturally converged.
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Affiliation(s)
- Simone Sarasso
- Department of Biomedical and Clinical Sciences ‘L. Sacco’, University of Milan, Milan 20157, Italy
| | - Adenauer Girardi Casali
- Instituto de Ciência e Tecnologia, Universidade Federal de São Paulo, Sao Jose dos Campos, 12247-014, Brazil
| | - Silvia Casarotto
- Department of Biomedical and Clinical Sciences ‘L. Sacco’, University of Milan, Milan 20157, Italy
- IRCCS Fondazione Don Carlo Gnocchi ONLUS, Milan 20148, Italy
| | - Mario Rosanova
- Department of Biomedical and Clinical Sciences ‘L. Sacco’, University of Milan, Milan 20157, Italy
| | | | - Marcello Massimini
- Department of Biomedical and Clinical Sciences ‘L. Sacco’, University of Milan, Milan 20157, Italy
- IRCCS Fondazione Don Carlo Gnocchi ONLUS, Milan 20148, Italy
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Quantitative EEG and Brain Network Analyses in Patients with Early Consciousness Disorder Following Acute Large Hemispheric Infarction. Neurocrit Care 2020; 33:360-361. [DOI: 10.1007/s12028-020-01067-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2020] [Accepted: 07/24/2020] [Indexed: 10/23/2022]
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