Frontiers in NeurologyPub Date : 2025-03-03eCollection Date: 2024-01-01DOI: 10.3389/fneur.2024.1502668
G Assenza, B Sancetta, L Ricci, C Vico, F Narducci, M Boscarino, J Lanzone, P Menna, C Liguori, F Izzi, N B Mercuri, V Di Lazzaro, M Tombini
{"title":"Cenobamate modulates EEG cortical activity and connectivity in individuals with drug-resistant epilepsy: a pharmaco-EEG study.","authors":"G Assenza, B Sancetta, L Ricci, C Vico, F Narducci, M Boscarino, J Lanzone, P Menna, C Liguori, F Izzi, N B Mercuri, V Di Lazzaro, M Tombini","doi":"10.3389/fneur.2024.1502668","DOIUrl":"10.3389/fneur.2024.1502668","url":null,"abstract":"<p><strong>Objective: </strong>Quantitative electroencephalography (qEEG) metrics are demonstrated to correlate with and predict clinical response in individuals with epilepsy. Cenobamate is an effective anti-seizure medication recently approved as an add-on therapy for individuals with epilepsy, but its effects on qEEG are unknown. We aimed to evaluate the modulation of qEEG metrics induced by cenobamate and its relationship with clinical response.</p><p><strong>Methods: </strong>We performed a prospective study with a cohort of 18 individuals with epilepsy (8 women, 47 ± 16 years old) and 25 healthy subjects (HS). They underwent a 19-channel EEG before and 6 months after cenobamate administration. Power spectral density (PSD) and phase locking value (PLV) for delta, theta, alpha, beta, and gamma frequency bands were calculated. Correlation analysis and analysis of covariance exhibited significant cenobamate-induced changes in qEEG and their relationship with seizure frequency changes. A regression analysis was performed to evaluate the association with clinical responders.</p><p><strong>Results: </strong>A total of 11 out of 16 individuals with epilepsy (69%, with 2 dropping out) were cenobamate responders (≥50% seizure frequency reduction). Cenobamate did not modify any PSD parameter but induced significant changes in PLV levels (<i>p</i> < 0.01). A decrease in PLV correlated with seizure reduction (<i>p</i> < 0.03). Regression analysis showed a strong association between PLV modulation and cenobamate responsiveness (a sensitivity of 0.75, a specificity of 0.84, and an accuracy of 0.81).</p><p><strong>Conclusion: </strong>Cenobamate induces an EEG connectivity modulation that is highly associated with cenobamate clinical response.</p><p><strong>Significance: </strong>Connectivity analysis of pharmaco-EEG can provide new hints toward the development of innovative biomarkers and precision medicine in individuals with epilepsy.</p>","PeriodicalId":12575,"journal":{"name":"Frontiers in Neurology","volume":"15 ","pages":"1502668"},"PeriodicalIF":2.7,"publicationDate":"2025-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11911179/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143648119","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Frontiers in NeurologyPub Date : 2025-03-03eCollection Date: 2025-01-01DOI: 10.3389/fneur.2025.1510115
Zhen-Yu Wang, Fei Chen, Hai-Hua Sun, Hua-Liang Li, Jian-Bin Hu, Zhen-Yu Dai, Shu Wang
{"title":"No reliable gray matter alterations in idiopathic dystonia.","authors":"Zhen-Yu Wang, Fei Chen, Hai-Hua Sun, Hua-Liang Li, Jian-Bin Hu, Zhen-Yu Dai, Shu Wang","doi":"10.3389/fneur.2025.1510115","DOIUrl":"10.3389/fneur.2025.1510115","url":null,"abstract":"<p><strong>Background: </strong>The structural brain abnormalities associated with idiopathic dystonia (ID) remain inadequately understood. Previous voxel-based morphometry (VBM) studies examining whole-brain gray matter (GM) volume alterations in patients with ID have reported inconsistent and occasionally contradictory findings.</p><p><strong>Methods: </strong>We performed a coordinate-based meta-analysis (CBMA) using the latest seed-based d mapping with permutation of subject images (SDM-PSI) technique to identify consistent GM alterations in patients with ID at the whole-brain level. Additionally, meta-regression analyses were conducted to explore the potential moderating effects of age, gender, and disease duration on GM volume.</p><p><strong>Results: </strong>The CBMA incorporated 27 VBM studies, comprising 32 datasets with a total of 840 patients with ID and 834 healthy controls. Our analysis did not identify consistent or reliable GM alterations in patients with ID. The robustness of these findings was confirmed through a jackknife sensitivity analysis. Meta-regression analyses revealed that disease duration significantly influenced GM volume in the right insula.</p><p><strong>Conclusion: </strong>Based on the best practice guidelines for CBMA, we utilized the most recent SDM-PSI algorithm to perform a new CBMA that included a larger group of individuals with ID. However, in contrast to previous CBMAs, we did not observe any consistent alterations in GM in ID. The findings suggest that using GM volume assessed by VBM as an imaging marker for ID may not be reliable. This could be attributed to ID being a functional disorder, or the inconsistency in GM alterations may be influenced by demographic and clinical variations, differences in imaging protocols and analysis methods, or small sample sizes. It is imperative to control for subject characteristics, employ standardized VBM methodologies, and enhance sample sizes in future research.</p>","PeriodicalId":12575,"journal":{"name":"Frontiers in Neurology","volume":"16 ","pages":"1510115"},"PeriodicalIF":2.7,"publicationDate":"2025-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11911186/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143648123","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Frontiers in NeurologyPub Date : 2025-03-03eCollection Date: 2025-01-01DOI: 10.3389/fneur.2025.1556026
Lei Zhang, Ben Li Li, Shuo Wei, Hong Wei Hu, Hong Fu Chen, Yue Chao Fan, Hui Zhang, Pei Zhi Ji
{"title":"Clinical efficacy of surgery for patients with Chiari malformation type I with syringomyelia: posterior fossa decompression versus posterior fossa decompression with resection of tonsils.","authors":"Lei Zhang, Ben Li Li, Shuo Wei, Hong Wei Hu, Hong Fu Chen, Yue Chao Fan, Hui Zhang, Pei Zhi Ji","doi":"10.3389/fneur.2025.1556026","DOIUrl":"10.3389/fneur.2025.1556026","url":null,"abstract":"<p><strong>Background: </strong>The optimal surgical approach for treating Chiari malformation type I (CM-I) with syringomyelia remains a topic of debate. Key areas of controversy include the extent of decompressive craniectomy, the necessity of subarachnoid exploration, and whether to excise the herniated tonsils. In this study, we present our perspectives on these contentious issues through a retrospective analysis of the clinical efficacy of posterior fossa decompression with resection of tonsils (PFDRT) compared to posterior fossa decompression (PFD).</p><p><strong>Methods: </strong>We conducted a retrospective analysis of clinical data from 162 patients diagnosed with CM-I and syringomyelia who underwent surgical intervention at the Affiliated Hospital of Xuzhou Medical University between January 2017 and December 2022. Among these, 58 patients underwent PFD, while 104 received PFDRT. The efficacy of the treatments was evaluated using the Chicago Chiari Deformity Prognosis Scale (CCOS) at 6 months post-surgery, with scores ranging from 13 to 16 indicating a favorable prognosis. Furthermore, the improvement of syringomyelia was assessed through magnetic resonance imaging (MRI) at the six-month follow-up.</p><p><strong>Results: </strong>Six months post-surgery, according to the Chiari Clinical Outcome Scale (CCOS) score, the improved rates for the PFD and PFDRT groups were 56.9 and 78.8%, respectively. Additionally, the recovery rates for syringomyelia in these groups were 55.2 and 76%, respectively. Statistically significant differences were observed in both the rates of favorable prognosis and syringomyelic improvement between the two groups (<i>p</i> < 0.05). The incidence of complications, including fever, cerebrospinal fluid leakage, intracranial infection, and incision infection, did not differ significantly between the groups (<i>p</i> > 0.05).</p><p><strong>Conclusion: </strong>Our findings indicate that PFDRT yields superior outcomes in syringomyelia improvement and favorable prognoses compared to PFD, while maintaining comparable postoperative complication rates.</p>","PeriodicalId":12575,"journal":{"name":"Frontiers in Neurology","volume":"16 ","pages":"1556026"},"PeriodicalIF":2.7,"publicationDate":"2025-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11912941/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143648074","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"The clinical value of the neutrophil-to-lymphocyte ratio, systemic immune-inflammation index, monocyte-to-lymphocyte ratio and platelet-to-lymphocyte ratio for predicting the severity of patients with autoimmune encephalitis.","authors":"Xin Zhao, Fen Wu, Shunfeng Zhao, Wenna Chen, Wei Si, Yuanrui Li, Dengke Zhang, Jing Wang, Ningning Wang, Lina Sun, Zhiyu Sun, Haoxiao Chang, Ganqin Du","doi":"10.3389/fneur.2025.1498007","DOIUrl":"https://doi.org/10.3389/fneur.2025.1498007","url":null,"abstract":"<p><strong>Background: </strong>The systemic inflammation index (SII), neutrophil-to-lymphocyte ratio (NLR), monocyte-to-lymphocyte ratio (MLR) and platelet-to-lymphocyte ratio (PLR) are inflammatory markers in peripheral blood, which have been proven to be associated with some central nervous system diseases. We aimed to evaluate the association of SII, NLR MLR and PLR with the severity of autoimmune encephalitis (AE) and to compare the predictive value of those biomarkers in the early identification of ICU admission.</p><p><strong>Methods: </strong>This retrospective study was conducted in three medical centers in China. We included 176 patients diagnosed with AE and 200 age and gender-matched healthy controls and correlated their demographic and clinical data. The SII, NLR, MLR and PLR levels were calculated from the blood routine tests. The severity of the patients was evaluated by the Clinical Assessment Scale for Autoimmune Encephalitis (CASE) and the modified Rankin Scale (mRS) at admission, and the patients were divided into two groups according to the ICU admission.</p><p><strong>Results: </strong>The SII, NLR, MLR and PLR were significantly higher in AE patients than that in HCs (<0.001 for all). The SII and NLR were positively correlated with the CASE score (<i>r</i> = 0.243, <i>p</i> = 0.001; <i>r</i> = 0.237, <i>p</i> = 0.002) and the mRS score (<i>r</i> = 0.185, <i>p</i> = 0.014; <i>r</i> = 0.185, <i>p</i> = 0.014) in AE patients. The MLR and PLR were only positively correlated with the CASE score (<i>r</i> = 0.242, <i>p</i> = 0.001; <i>r</i> = 0.158, <i>p</i> = 0.036). The SII and NLR of the ICU group were significantly higher than that of the non-ICU group. The result of receiver operating characteristic (ROC) analysis showed that NLR was the best predictor of ICU admission for AE patients (AUC = 0.701). NLR and MLR had similar predictive ability (AUC = 0.654; AUC = 0.608) and were superior to PLR. The optimal NLR cut-off value for the incidence of ICU was 3.906.</p><p><strong>Conclusion: </strong>Increased SII, NLR, MLR and PLR at admission are positively correlated with the CASE score of AE patients. Among the four indexes, the NLR is the best predictor of ICU admission, which may be helpful for clinicians to monitor disease progression and identify potentially severe patients of AE.</p>","PeriodicalId":12575,"journal":{"name":"Frontiers in Neurology","volume":"16 ","pages":"1498007"},"PeriodicalIF":2.7,"publicationDate":"2025-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11906310/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143648131","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Frontiers in NeurologyPub Date : 2025-02-28eCollection Date: 2025-01-01DOI: 10.3389/fneur.2025.1521001
Yoon Gi Chung, Jaeso Cho, Young Ho Kim, Hyun Woo Kim, Hunmin Kim, Yong Seo Koo, Seo-Young Lee, Young-Min Shon
{"title":"Data transformation of unstructured electroencephalography reports by natural language processing: improving data usability for large-scale epilepsy studies.","authors":"Yoon Gi Chung, Jaeso Cho, Young Ho Kim, Hyun Woo Kim, Hunmin Kim, Yong Seo Koo, Seo-Young Lee, Young-Min Shon","doi":"10.3389/fneur.2025.1521001","DOIUrl":"https://doi.org/10.3389/fneur.2025.1521001","url":null,"abstract":"<p><strong>Introduction: </strong>Electroencephalography (EEG) is a popular technique that provides neurologists with electrographic insights and clinical interpretations. However, these insights are predominantly presented in unstructured textual formats, which complicates data extraction and analysis. In this study, we introduce a hierarchical algorithm aimed at transforming unstructured EEG reports from pediatric patients diagnosed with epilepsy into structured data using natural language processing (NLP) techniques.</p><p><strong>Methods: </strong>The proposed algorithm consists of two distinct phases: a deep learning-based text classification followed by a series of rule-based keyword extraction procedures. First, we categorized the EEG reports into two primary groups: normal and abnormal. Thereafter, we systematically identified the key indicators of cerebral dysfunction or seizures, distinguishing between focal and generalized seizures, as well as identifying the epileptiform discharges and their specific anatomical locations. For this study, we retrospectively analyzed a dataset comprising 17,172 EEG reports from 3,423 pediatric patients. Among them, we selected 6,173 normal and 6,173 abnormal reports confirmed by neurologists for algorithm development.</p><p><strong>Results: </strong>The developed algorithm successfully classified EEG reports into 1,000 normal and 1,000 abnormal reports, and effectively identified the presence of cerebral dysfunction or seizures within these reports. Furthermore, our findings revealed that the algorithm translated abnormal reports into structured tabular data with an accuracy surpassing 98.5% when determining the type of seizures (focal or generalized). Additionally, the accuracy for detecting epileptiform discharges and their respective locations exceeded 88.5%. These outcomes were validated through both internal and external assessments involving 800 reports from two different medical institutions.</p><p><strong>Discussion: </strong>Our primary focus was to convert EEG reports into structured datasets, diverging from the traditional methods of formulating clinical notes or discharge summaries. We developed a hierarchical and streamlined approach leveraging keyword selections guided by neurologists, which contributed to the exceptional performance of our algorithm. Overall, this methodology enhances data accessibility as well as improves the potential for further research and clinical applications in the field of pediatric epilepsy management.</p>","PeriodicalId":12575,"journal":{"name":"Frontiers in Neurology","volume":"16 ","pages":"1521001"},"PeriodicalIF":2.7,"publicationDate":"2025-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11906308/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143648094","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Corrigendum: Neural circuit mechanisms of acupuncture effect: where are we now?","authors":"Xuesong Wang, Jia Wang, Rui Han, Chaochao Yu, Feng Shen","doi":"10.3389/fneur.2025.1576213","DOIUrl":"https://doi.org/10.3389/fneur.2025.1576213","url":null,"abstract":"<p><p>[This corrects the article DOI: 10.3389/fneur.2024.1399925.].</p>","PeriodicalId":12575,"journal":{"name":"Frontiers in Neurology","volume":"16 ","pages":"1576213"},"PeriodicalIF":2.7,"publicationDate":"2025-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11908377/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143648090","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Frontiers in NeurologyPub Date : 2025-02-28eCollection Date: 2025-01-01DOI: 10.3389/fneur.2025.1533558
Kun Dai, Hong-Rong Zhang, Shuai-Yu Ren, Ming-Pei Zhao, Neng Wang, Hong-Zhi Gao, De-Zhi Kang, Zong-Qing Zheng
{"title":"Unveiling BID: a key biomarker in apoptosis post-intracerebral hemorrhage.","authors":"Kun Dai, Hong-Rong Zhang, Shuai-Yu Ren, Ming-Pei Zhao, Neng Wang, Hong-Zhi Gao, De-Zhi Kang, Zong-Qing Zheng","doi":"10.3389/fneur.2025.1533558","DOIUrl":"https://doi.org/10.3389/fneur.2025.1533558","url":null,"abstract":"<p><strong>Background: </strong>Apoptosis plays a significant role in secondary brain injury following intracerebral hemorrhage (ICH). Currently, the mechanisms related to cell apoptosis after cerebral hemorrhage are still under investigation.</p><p><strong>Methods: </strong>We identified differentially expressed genes (DEGs) between human ICH patients and normal individuals from the GEO database and conducted GO and KEGG functional enrichment analyses on these DEGs. We then constructed a PPI network and used the MECDE algorithm to identify key genes potentially involved in apoptosis after ICH. Additionally, we identified miRNAs that might regulate apoptotic genes in an mRNA-miRNA interaction network. Finally, we validated the bioinformatics results in a rat ICH model.</p><p><strong>Results: </strong>In the human ICH model, 645 DEGs were identified. GO and KEGG analyses indicated that these DEGs are primarily involved in immune response, inflammatory response, and apoptosis. GSEA analysis showed significant enrichment of DEGs in the apoptotic process. By comparing with apoptosis-related genes in the MSigDB database, we identified 110 apoptosis-related genes among the 645 DEGs. Further PPI and MOCDE analyses of these apoptosis-related genes revealed that BID might be a key gene involved in apoptosis after ICH, which was validated within the rat model of ICH. The mRNA-miRNA interactions network construction suggested that miR1225-3p may be an important miRNA involved in regulating BID expression after ICH.</p><p><strong>Conclusion: </strong>BID plays a critical role in the regulation of apoptosis following intracerebral hemorrhage and serves as a key biomarker in the apoptotic process after hemorrhage.</p>","PeriodicalId":12575,"journal":{"name":"Frontiers in Neurology","volume":"16 ","pages":"1533558"},"PeriodicalIF":2.7,"publicationDate":"2025-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11907958/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143648037","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Changes in cerebral cortex activation during upright standing tasks in individuals with chronic neck pain: an fNIRS study.","authors":"Chongwu Xiao, Qianfei Liang, Yugang Yang, Mingyu Mo, Weixiong Li, Huade Chen, Yaobin Long, Jinjun Huang","doi":"10.3389/fneur.2025.1531314","DOIUrl":"https://doi.org/10.3389/fneur.2025.1531314","url":null,"abstract":"<p><strong>Introduction: </strong>Studies show that individuals with chronic neck pain (CNP) exhibit postural control deficits, potentially contributing to persistent and recurrent pain. However, the neural mechanisms underlying these deficits in CNP remain unexplored despite their importance for developing effective rehabilitation strategies. Therefore, this study aimed to investigate the neural activity during postural control using functional near-infrared spectroscopy (fNIRS), providing insights into the central mechanism underlying postural control deficits in individuals with CNP.</p><p><strong>Methods: </strong>In this cross-sectional study, 10 individuals with CNP (CNP group) and 10 healthy controls (HC group) were assessed under three conditions: Task 1, standing on a force plate with eyes open and both feet; Task 2, standing on a force plate with eyes closed and both feet; Task 3, standing on a force plate with eyes closed and one foot. Cerebral cortex hemodynamic reactions, including bilateral prefrontal cortex (PFC), dorsolateral prefrontal cortex (DLPFC), pre-motor cortex and supplementary motor area (PMC/SMA), primary motor cortex (M1), and primary somatosensory cortex (S1) were measured using fNIRS. Balance parameters, including the sway area, total sway length, mean velocity, and center of pressure (COP) amplitude in the anterior-posterior (AP) and medial-lateral (ML) directions, were measured using a force plate.</p><p><strong>Results: </strong>In Tasks 1 and 2, no differences were observed between both groups in balance parameters. However, the CNP group exhibited significantly higher activation in the left PMC/SMA (<i>F</i> = 4.788, <i>p</i> = 0.042) and M1 (<i>F</i> = 9.598, <i>p</i> = 0.006) in Task 1 and lower activation in the left (<i>F</i> = 4.952, <i>p</i> = 0.039) and right (<i>F</i> = 6.035, <i>p</i> = 0.024) PFC in Task 2 compared to that of the HC group. In Task 3, the CNP group exhibited a significantly larger COP amplitude in the AP direction (<i>F</i> = 7.057, <i>p</i> = 0.016) compared to that of the HC group. Additionally, activation in the right M1 (<i>F</i> = 7.873, <i>p</i> = 0.012) was significantly higher than in the HC group. Correlation analysis in Task 3 revealed stronger associations between the parameters in the CNP group.</p><p><strong>Conclusion: </strong>Our findings suggest that individuals with CNP exhibit distinct patterns of cerebral cortex activities and postural control deficits. The PFC, M1, and PMC/SMA were involved in maintaining upright standing balance, and cerebral cortex changes associated with upright standing balance provide a more sensitive indicator of postural control deficits than peripheral balance parameters in individuals with CNP.</p>","PeriodicalId":12575,"journal":{"name":"Frontiers in Neurology","volume":"16 ","pages":"1531314"},"PeriodicalIF":2.7,"publicationDate":"2025-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11906313/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143648073","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Frontiers in NeurologyPub Date : 2025-02-27eCollection Date: 2025-01-01DOI: 10.3389/fneur.2025.1512913
Yingjie Zhao, Rui Zhang, Pan Li, Zhen Zhang, Huan Yu, Zhaoya Su, Yandong Xia, Aiguo Meng
{"title":"A new nomogram for predicting 90-day outcomes of intravenous thrombolysis in patients with acute ischaemic stroke.","authors":"Yingjie Zhao, Rui Zhang, Pan Li, Zhen Zhang, Huan Yu, Zhaoya Su, Yandong Xia, Aiguo Meng","doi":"10.3389/fneur.2025.1512913","DOIUrl":"10.3389/fneur.2025.1512913","url":null,"abstract":"<p><strong>Background: </strong>The aim of this study was to construct and validate a new nomogram to predict the risk of poor outcome in patients with acute ischemic stroke (AIS) after intravenous thrombolytic therapy (IVT).</p><p><strong>Methods: </strong>A total of 425 patients who received IVT within 4.5 h of stroke onset were included in a retrospective study. All the patients were divided into training (70%, <i>n</i> = 298) and validation cohorts (30%, <i>n</i> = 127). Poor outcome (defined as a 90-day modified Rankin Scale score 3-5) was the primary outcome. Logistic regression was used for analysis of independent risk factors for poor outcome in patients with AIS. Nomograms of poor outcome in AIS patients were constructed using R software. Discrimination and calibration of the models were assessed using area under the receiver operating characteristic (ROC) curve (AUC) and calibration plots.</p><p><strong>Results: </strong>Multifactorial logistic regression analysis showed that SII (OR = 1.001, 95% CI: 1.000-1.002, <i>p</i> = 0.008), SIRI (OR = 1.584, 95% CI: 1.122-2.236, <i>p</i> = 0.009), NIHSS (OR = 1.101, 95% CI: 1.044-1.160, <i>p</i> < 0.001), and history of diabetes mellitus (OR = 2.582, 95% CI: 1.285-5.188, <i>p</i> = 0.008) were the independent risk factors for the occurrence of poor outcome in AIS patients. The poor outcome nomogram for AIS patients was constructed based on the above independent risk factors. The training and validation cohort AUCs of the nomogram were 0.854 (95% CI: 0.807-0.901) and 0.855 (95% CI: 0.783-0.927), respectively. The prediction models were well calibrated in both the training and validation cohorts. The net benefit of the nomograms was better when the threshold probability ranges were 4.28-66.4% and 4.01-67.8% for the training and validation cohorts, respectively.</p><p><strong>Conclusion: </strong>New nomogram includes NIHSS, SII, SIRI and diabetes as variables with the potential to predict the risk of 90-day outcomes in patients with AIS following IVT.</p>","PeriodicalId":12575,"journal":{"name":"Frontiers in Neurology","volume":"16 ","pages":"1512913"},"PeriodicalIF":2.7,"publicationDate":"2025-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11905897/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143624321","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Frontiers in NeurologyPub Date : 2025-02-27eCollection Date: 2025-01-01DOI: 10.3389/fneur.2025.1514442
Debayan Dasgupta, Cameron A Elliott, Aidan G O'Keeffe, Roman Rodionov, Kuo Li, Vejay N Vakharia, Farhan A Mirza, M Zubair Tahir, Martin M Tisdall, Anna Miserocchi, Andrew W McEvoy, Sebastien Ourselin, Rachel E Sparks, John S Duncan
{"title":"Computer-assisted stereoelectroencephalography planning: center-specific priors enhance planning.","authors":"Debayan Dasgupta, Cameron A Elliott, Aidan G O'Keeffe, Roman Rodionov, Kuo Li, Vejay N Vakharia, Farhan A Mirza, M Zubair Tahir, Martin M Tisdall, Anna Miserocchi, Andrew W McEvoy, Sebastien Ourselin, Rachel E Sparks, John S Duncan","doi":"10.3389/fneur.2025.1514442","DOIUrl":"10.3389/fneur.2025.1514442","url":null,"abstract":"<p><strong>Objectives: </strong>This study aims to refine computer-assisted planning (CAP) of SEEG implantations by adding spatial constraints from prior SEEG trajectories (\"Priors\") to improve safety and reduce manual adjustments, without increasing planning time.</p><p><strong>Methods: </strong>Retrospective validation based on 159 previously implanted trajectories (11 cases) planned by the clinical standard CAP and CAP constrained with spatial priors (\"CAP + Priors\"). Constraints included 31 target and 51 entry zones, created from 98 consecutive patients (763 implanted SEEG trajectories). Each of the 159 previously implanted trajectories was planned by two fellows, once with CAP and once with CAP + Priors, in a randomized order. The time taken to generate the initial computer-generated plan (T1) and the user-edited final plan (T2) were recorded together with the proportions of electrodes that required subsequent adjustments. Clinical implantability was assessed via a blinded review of each trajectory by five independent epilepsy neurosurgeons with expertise in SEEG implantation.</p><p><strong>Results: </strong>Expert raters considered 88.5% of trajectories implantable, with no difference in acceptability between CAP alone and CAP + Priors (<i>p</i> = 0.79). Median (IQR) T1 for CAP to produce complete automated implantation was 4.6 (0.85) min vs. CAP + Priors was 6.3 (2.6) min (<i>p</i> = 0.03). There was no significant difference in T2 (time to complete surgeon-edited plan): CAP median (IQR) 105 (22) min, and CAP + Priors median (IQR) 96 (68) min (<i>p</i> = 0.92). The CAP + Priors risk score was significantly lower than that for the previously actually implanted trajectories for the 11 plans analyzed (<i>p</i> = 0.004), and no different from CAP alone planning. A significant reduction was observed in manual adjustments required with CAP + Priors in the cingulate gyrus.</p><p><strong>Conclusion: </strong>Using spatial priors from previous implantations enhances SEEG CAP and increases the granularity of trajectory planning. This approach facilitates more standardized planning and allows for the incorporation of experience from multiple expert centers, decreasing the risk of the resultant trajectories and reducing the proportion of trajectories that require manual planning without significantly increasing planning time.</p>","PeriodicalId":12575,"journal":{"name":"Frontiers in Neurology","volume":"16 ","pages":"1514442"},"PeriodicalIF":2.7,"publicationDate":"2025-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11905814/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143624335","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}