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Meletti S, Cuccurullo C, Orlandi N, Borzì G, Bigliardi G, Maffei S, Del Giovane C, Cuoghi Costantini R, Giovannini G, Lattanzi S. Prediction of epilepsy after stroke: Proposal of a modified SeLECT 2.0 score based on posttreatment stroke outcome. Epilepsia 2024. [PMID: 39235830 DOI: 10.1111/epi.18114] [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: 03/30/2024] [Revised: 08/22/2024] [Accepted: 08/22/2024] [Indexed: 09/06/2024]
Abstract
OBJECTIVE The SeLECT 2.0 score is a prognostic model of epilepsy after ischemic stroke. We explored whether replacing the severity of stroke at admission with the severity of stroke after treatment at 72 h from onset could improve the predictive accuracy of the score. METHODS We retrospectively identified consecutive adults with acute first-ever neuroimaging-confirmed ischemic stroke who were admitted to the Stroke Unit of the Ospedale Civile Baggiovara (Modena, Italy) and treated with intravenous thrombolysis and/or endovascular treatment. Study outcome was the occurrence of at least one unprovoked seizure presenting >7 days after stroke. RESULTS Participants included in the analysis numbered 1094. The median age of the subjects was 74 (interquartile range [IQR] = 64-81) years, and 595 (54.4%) were males. Sixty-five (5.9%) subjects developed unprovoked seizures a median of 10 (IQR = 6-27) months after stroke. The median values of the original and modified SeLECT2.0 scores were 3 (IQR = 2-4) and 2 (IQR = 1-3). The modified SeLECT 2.0 score showed better discrimination for the prediction of poststroke epilepsy at 36, 48, and 60 months after stroke compared to the original score according to the area under time-dependent receiver operating characteristic curves. The modified SeLECT 2.0 score had higher values of Harrell C and Somers D parameters and lower values of Akaike and Bayesian information criteria than the original score. The modified SeLECT 2.0 score produced more accurate risk predictions compared to the SeLECT 2.0 score at all evaluated time points from 12 to 60 months after stroke according to the Net Reclassification Index. SIGNIFICANCE Replacing baseline with posttreatment stroke severity may improve the ability of the SeLECT 2.0 score to predict poststroke epilepsy.
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Affiliation(s)
- Stefano Meletti
- Neurology Unit, OCB Hospital, AOU Modena, Modena, Italy
- Department of Biomedical, Metabolic, and Neural Science, Center for Neuroscience and Neurotechnology, University of Modena and Reggio Emilia, Modena, Italy
| | - Claudia Cuccurullo
- Neurology and Stroke Unit, Ospedale del Mare Hospital, ASL Napoli 1, Naples, Italy
| | - Niccolò Orlandi
- Neurology Unit, OCB Hospital, AOU Modena, Modena, Italy
- Department of Biomedical, Metabolic, and Neural Science, Center for Neuroscience and Neurotechnology, University of Modena and Reggio Emilia, Modena, Italy
| | - Giuseppe Borzì
- Neurology Unit, OCB Hospital, AOU Modena, Modena, Italy
- Stroke Unit, OCB Hospital, AOU Modena, Modena, Italy
| | - Guido Bigliardi
- Neurology Unit, OCB Hospital, AOU Modena, Modena, Italy
- Stroke Unit, OCB Hospital, AOU Modena, Modena, Italy
| | - Stefania Maffei
- Neurology Unit, OCB Hospital, AOU Modena, Modena, Italy
- Stroke Unit, OCB Hospital, AOU Modena, Modena, Italy
| | - Cinzia Del Giovane
- Department of Medical and Surgical Sciences for Children and Adults, University of Modena and Reggio Emilia, Modena, Italy
| | - Riccardo Cuoghi Costantini
- Department of Medical and Surgical Sciences for Children and Adults, University of Modena and Reggio Emilia, Modena, Italy
| | | | - Simona Lattanzi
- Neurological Clinic, Department of Experimental and Clinical Medicine, Marche Polytechnic University, Ancona, Italy
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Bu J, Yin H, Ren N, Zhu H, Xu H, Zhang R, Zhang S. Structural and functional changes in the default mode network in drug-resistant epilepsy. Epilepsy Behav 2024; 151:109593. [PMID: 38157823 DOI: 10.1016/j.yebeh.2023.109593] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/07/2023] [Revised: 11/25/2023] [Accepted: 12/07/2023] [Indexed: 01/03/2024]
Abstract
PURPOSE To investigate brain network properties and connectivity abnormalities of the default mode network (DMN) in drug-resistant epilepsy (DRE). The study was based on probabilistic fiber tracking and functional connectivity (FC) analysis, to explore the structural and functional connectivity patterns change between frontal lobe epilepsy (FLE) and temporal lobe epilepsy (TLE). METHODS A total of 33 DRE patients (18 TLE and 15 FLE) and 30 healthy controls (HCs) were recruited. The volume fraction of the septal brain region of the DMN in DRE was calculated using FreeSurfer. The FC analysis was performed using Data Processing and Analysis for Brain Imaging in MATLAB. The structural connections between brain regions of the DMN were calculated based on probabilistic fiber tracking. RESULTS The left precuneus (PCUN) volumes in epilepsy groups were lower than that in HCs. Compared with FLE, TLE showed reduced FC between the left hippocampus (HIP) and PCUN/medial frontal gyrus, and between the right inferior parietal lobule (IPL) and right superior temporal gyrus. Compared with HCs, FLE showed increased FCs between the right IPL and occipital lobe, and between the left superior frontal gyrus (SFG) and bilateral superior temporal gyrus. In terms of structural connectivity, TLE exhibited increased connectivity strength between the left SFG and left PCUN, and showed reduced connection strength between the left HIP and left posterior cingulate gyrus/left PCUN, when compared with the FLE. CONCLUSIONS TLE and FLE patients showed structural and functional changes in the DMN. Compared with FLE patients, the TLE patients showed reduced structural and functional connection strengths between the left HIP and PCUN. These alterations in connection strengths holds promise for the identification of TLE and FLE.
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Affiliation(s)
- Jinxin Bu
- Department of Functional Neurosurgery, Affiliated Nanjing Brain Hospital of Nanjing Medical University, Nanjing 210029, Jiangsu, China
| | - Hangxing Yin
- Department of Neurology, Affiliated Nanjing Brain Hospital of Nanjing Medical University, Nanjing 210029, Jiangsu, China
| | - Nanxiao Ren
- Department of Functional Neurosurgery, Affiliated Nanjing Brain Hospital of Nanjing Medical University, Nanjing 210029, Jiangsu, China
| | - Haitao Zhu
- Department of Functional Neurosurgery, Affiliated Nanjing Brain Hospital of Nanjing Medical University, Nanjing 210029, Jiangsu, China
| | - Honghao Xu
- Department of Functional Neurosurgery, Affiliated Nanjing Brain Hospital of Nanjing Medical University, Nanjing 210029, Jiangsu, China
| | - Rui Zhang
- Department of Functional Neurosurgery, Affiliated Nanjing Brain Hospital of Nanjing Medical University, Nanjing 210029, Jiangsu, China.
| | - Shugang Zhang
- Department of Neurology, Affiliated Nanjing Brain Hospital of Nanjing Medical University, Nanjing 210029, Jiangsu, China.
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Lu D, Wang Y, Yang Y, Zhang H, Fan X, Chen S, Wei P, Shan Y, Zhao G. Thyroid function and epilepsy: a two-sample Mendelian randomization study. Front Hum Neurosci 2024; 17:1295749. [PMID: 38298204 PMCID: PMC10827972 DOI: 10.3389/fnhum.2023.1295749] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2023] [Accepted: 12/27/2023] [Indexed: 02/02/2024] Open
Abstract
Background Thyroid hormones (THs) play a crucial role in regulating various biological processes, particularly the normal development and functioning of the central nervous system (CNS). Epilepsy is a prevalent neurological disorder with multiple etiologies. Further in-depth research on the role of thyroid hormones in epilepsy is warranted. Methods Genome-wide association study (GWAS) data for thyroid function and epilepsy were obtained from the ThyroidOmics Consortium and the International League Against Epilepsy (ILAE) Consortium cohort, respectively. A total of five indicators of thyroid function and ten types of epilepsy were included in the analysis. Two-sample Mendelian randomization (MR) analyses were conducted to investigate potential causal relations between thyroid functions and various epilepsies. Multiple testing correction was performed using Bonferroni correction. Heterogeneity was calculated with the Cochran's Q statistic test. Horizontal pleiotropy was evaluated by the MR-Egger regression intercept. The sensitivity was also examined by leave-one-out strategy. Results The findings indicated the absence of any causal relationship between abnormalities in thyroid hormone and various types of epilepsy. The study analyzed the odds ratio (OR) between thyroid hormones and various types of epilepsy in five scenarios, including free thyroxine (FT4) on focal epilepsy with hippocampal sclerosis (IVW, OR = 0.9838, p = 0.02223), hyperthyroidism on juvenile absence epilepsy (IVW, OR = 0.9952, p = 0.03777), hypothyroidism on focal epilepsy with hippocampal sclerosis (IVW, OR = 1.0075, p = 0.01951), autoimmune thyroid diseases (AITDs) on generalized epilepsy in all documented cases (weighted mode, OR = 1.0846, p = 0.0346) and on childhood absence epilepsy (IVW, OR = 1.0050, p = 0.04555). After Bonferroni correction, none of the above results showed statistically significant differences. Conclusion This study indicates that there is no causal relationship between thyroid-related disorders and various types of epilepsy. Future research should aim to avoid potential confounding factors that might impact the study.
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Affiliation(s)
- Di Lu
- Department of Neurosurgery, Xuanwu Hospital, Capital Medical University, Beijing, China
- Clinical Research Center for Epilepsy, Capital Medical University, Beijing, China
| | - Yunming Wang
- Department of Neurosurgery, Xuanwu Hospital, Capital Medical University, Beijing, China
- Clinical Research Center for Epilepsy, Capital Medical University, Beijing, China
| | - Yanfeng Yang
- Department of Neurosurgery, Xuanwu Hospital, Capital Medical University, Beijing, China
- Clinical Research Center for Epilepsy, Capital Medical University, Beijing, China
| | - Huaqiang Zhang
- Department of Neurosurgery, Xuanwu Hospital, Capital Medical University, Beijing, China
- Clinical Research Center for Epilepsy, Capital Medical University, Beijing, China
| | - Xiaotong Fan
- Department of Neurosurgery, Xuanwu Hospital, Capital Medical University, Beijing, China
- Clinical Research Center for Epilepsy, Capital Medical University, Beijing, China
| | - Sichang Chen
- Department of Neurosurgery, Xuanwu Hospital, Capital Medical University, Beijing, China
- Clinical Research Center for Epilepsy, Capital Medical University, Beijing, China
| | - Penghu Wei
- Department of Neurosurgery, Xuanwu Hospital, Capital Medical University, Beijing, China
- Clinical Research Center for Epilepsy, Capital Medical University, Beijing, China
- Beijing Municipal Geriatric Medical Research Center, Beijing, China
| | - Yongzhi Shan
- Department of Neurosurgery, Xuanwu Hospital, Capital Medical University, Beijing, China
- Clinical Research Center for Epilepsy, Capital Medical University, Beijing, China
| | - Guoguang Zhao
- Department of Neurosurgery, Xuanwu Hospital, Capital Medical University, Beijing, China
- Clinical Research Center for Epilepsy, Capital Medical University, Beijing, China
- Beijing Municipal Geriatric Medical Research Center, Beijing, China
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Guan M, Xie Y, Li C, Zhang T, Ma C, Wang Z, Ma Z, Wang H, Fang P. Rich-club reorganization of white matter structural network in schizophrenia patients with auditory verbal hallucinations following 1 Hz rTMS treatment. Neuroimage Clin 2023; 40:103546. [PMID: 37988997 PMCID: PMC10701084 DOI: 10.1016/j.nicl.2023.103546] [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: 11/12/2023] [Revised: 11/17/2023] [Accepted: 11/17/2023] [Indexed: 11/23/2023]
Abstract
The human brain comprises a large-scale structural network of regions and interregional pathways, including a selectively defined set of highly central and interconnected hub regions, often referred to as the "rich club", which may play a pivotal role in the integrative processes of the brain. A quintessential symptom of schizophrenia, auditory verbal hallucinations (AVH) have shown a decrease in severity following low-frequency repetitive transcranial magnetic stimulation (rTMS). However, the underlying mechanism of rTMS in treating AVH remains elusive. This study investigated the effect of low-frequency rTMS on the rich-club organization within the brain in patients diagnosed with schizophrenia who experience AVH using diffusion tensor imaging data. Through by constructing structural connectivity networks, we identified several critical rich hub nodes, which constituted a rich-club subnetwork, predominantly located in the prefrontal cortices. Notably, our findings revealed enhanced connection strength and density within the rich-club subnetwork following rTMS treatment. Furthermore, we found that the decreased connectivity within the subnetwork components, including the rich-club subnetwork, was notably enhanced in patients following rTMS treatment. In particular, the increased connectivity strength of the right median superior frontal gyrus, which functions as a critical local bridge, with the right postcentral gyrus exhibited a significant correlation with improvements in both positive symptoms and AVH. These findings provide valuable insights into the role of rTMS in inducing reorganizational changes within the rich-club structural network in schizophrenia and shed light on potential mechanisms through which rTMS may alleviate AVH.
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Affiliation(s)
- Muzhen Guan
- Department of Mental Health, Xi'an Medical College, Xi'an, China.
| | - Yuanjun Xie
- Military Medical Psychology School, Fourth Military Medical University, Xi'an, China; Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, China.
| | - Chenxi Li
- Military Medical Psychology School, Fourth Military Medical University, Xi'an, China
| | - Tian Zhang
- Military Medical Psychology School, Fourth Military Medical University, Xi'an, China
| | - Chaozong Ma
- Military Medical Psychology School, Fourth Military Medical University, Xi'an, China
| | - Zhongheng Wang
- Department of Psychiatry, Xijing Hospital, Fourth Military Medical University, Xi'an, China
| | - Zhujing Ma
- Department of Psychiatry, Xijing Hospital, Fourth Military Medical University, Xi'an, China
| | - Huaning Wang
- Department of Psychiatry, Xijing Hospital, Fourth Military Medical University, Xi'an, China.
| | - Peng Fang
- Military Medical Psychology School, Fourth Military Medical University, Xi'an, China.
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