Frontiers in Neurology最新文献

Immune effector cell-associated neurotoxicity syndrome (ICANS) is a common and sometimes severe complication of chimeric antigen receptor (CAR) T-cell therapy. Although our understanding has advanced considerably, ICANS remains biologically complex and clinically variable. In this review, we synthesize current evidence on how systemic immune activation, endothelial injury, disruption of the blood-brain barrier, and neuroinflammation converge to produce neurological symptoms in affected patients. We summarize emerging predictive biomarkers across plasma, cerebrospinal fluid, electroencephalography (EEG), and neuroimaging, and organize them within a temporal framework to highlight when different signals arise and how they may support earlier recognition. We also differentiate ICANS from tumor inflammation-associated neurotoxicity (TIAN), a syndrome more frequently observed in patients with central nervous system tumors, underscoring key differences in pathogenesis, presentation, and management. Finally, we discuss conceptual approaches to multimodal risk prediction and the practical challenges that currently limit clinical implementation, including assay turnaround time, generalizability across CAR constructs and disease settings, interpretability, and ethical considerations when acting on predicted risk. We propose a pragmatic roadmap that prioritizes prospective biomarker-guided studies, standardized assay platforms, and transparent modeling strategies to help move the field from observation toward safer prevention. Taken together, this integrative perspective aims to clarify the biology of ICANS, contextualize emerging biomarkers, and support more informed and safer use of CAR T-cell therapy.

Background: Withdrawal of life-sustaining treatments (WLST) is a leading cause of death in patients with severe acquired brain injuries (ABI). These decisions often occur under conditions of prognostic uncertainty and time-critical therapeutic windows and may be shaped by a complex interplay of factors. Elucidating these influences is essential to ensure that WLST decisions are made in an informed, unbiased, and transparent manner, and in alignment with wishes of the patients as well as their surrogate decision makers.

Objective: Conduct a scoping review of literature to identify, elaborate and analyze the various factors that influence decisions to WLST in adult patients with ABI. This review aims to provide a comprehensive understanding of current practices.

Methods: This scoping review, conducted according to PRISMA-ScR guidelines, examined literature on WLST in adult ABI, in whom brain death had not been declared. The search was conducted in PubMed and Web of Science, up to August 2024. Studies were screened by title/abstract and full text, with data systematically extracted. Only original, peer-reviewed articles focusing on WLST in adult severe ABI patients were included. N = 2,963 independent papers were initially found, of which N = 2,881 were excluded. A final count of N = 81 independent papers were included.

Results: Demographic factors (age, sex, race, socioeconomic status, etc.; n = 50), prognosis and clinical factors (n = 59), family preferences (n = 28), physician-related factors and institutional context (n = 31), formal medical directive (n = 13), ethical/legal frameworks (n = 13), geographical differences (n = 9) and religious beliefs (n = 5) all played pivotal roles in WLST decisions. Older age consistently emerged as a determinant for WLST, as well as poor prognosis and white race.

Conclusion: WLST decisions are most often made for older adults, with age consistently identified as a key predictor, independent of the clinical severity of ABI. Additional factors such as race, socioeconomic status, advance directives, and variations in healthcare provider attitudes and institutional policies further contribute to disparities in WLST practices. Understanding these intersecting influences is essential to recognizing potential biases and promoting more equitable, patient-centered end-of-life decision-making.

Background: We performed a secondary data analysis of a previously published study to investigate the effects of different electrical stimulation modalities on specific impaired sensory and motor functions.

Methods: A total of 51 patients with chemotherapy-induced peripheral neuropathy (CIPN) ≥ grade 1 after receiving platinum- and/or taxane-based chemotherapy were randomized to 8 weeks of high-tone external muscle stimulation (HTEMS) or transcutaneous electrical nerve stimulation (TENS). A control group (n = 17) receiving no intervention was recruited retrospectively. Patients received 8 weeks of home-based electrotherapy for at least 5 days a week, for 30 min per day, using either a TENS or HTEMS device. In the original study, changes in the EORTC-QLQ-CIPN20 questionnaire were measured before and after the intervention. For this secondary data analysis, we performed sub-analyses to examine the specific effects of TENS and HTEMS on the individual sensory and motor scale outcomes of the EORTC-QLQ-CIPN20 questionnaire.

Results: For sensory function categories, HTEMS significantly improved tingling in the fingers or hands (p = 0.009) and the numbness in the toes or feet (p = 0.018). TENS tended to reduce shooting or burning pain in the toes or feet (p = 0.051). TENS also demonstrated a trend to improve problems in standing or walking due to difficulties in feeling the ground (p = 0.051), while improvements after HTEMS reached significance (p = 0.045). For motor function categories, TENS improved difficulties opening a bottle due to weakness (p = 0.036), and HTEMS reduced difficulties in walking due to downward dropping of the feet (p = 0.015). There were no changes for any category in the control group.

Conclusion: Electrotherapy is a useful tool for treating CIPN. A symptom-oriented selection of the stimulation modality may be promising.

Clinical trial registration: https://clinicaltrials.gov/ct2/show/NCT03978585.

Understanding the neural mechanisms underlying upper limb motor recovery after stroke remains a significant challenge in rehabilitation research. It has been proposed that individuals who show no motor-evoked potential (MEP) response to transcranial magnetic stimulation (TMS) and are thus classified as MEP negative (MEP-) have limited potential for recovery in part due to damage of the corticospinal pathway. In this study, we investigate how individuals categorized as MEP- with TMS respond to stimulation of the corticospinal pathway at a subcortical level. We describe the methodology for eliciting MEPs by using cervicomedullary electrical stimulation (CMEP) in post-stroke individuals with severe upper limb hemiparesis. MEP status (+/-) of the more affected arm was assessed using TMS and cervicomedullary electrical stimulation in stroke survivors with severe upper extremity hemiparesis. While most of the participants were classified as MEP-, all individuals were categorized as CMEP+ in the biceps brachii, extensor carpi radialis, and first dorsal interosseous muscles. Importantly, we report the first testing of CMEPs in a small cohort of individuals with stroke. This technique is feasible in this population and has potential for application in clinical translation settings. Our findings provide a foundation for future studies to replicate and expand upon this approach, enabling the exploration of new hypotheses related to post-stroke rehabilitation and recovery.

Background: The cognitive difficulties experienced by individuals with narcolepsy type 1 (NT1), a rare and chronic neurological disorder, are understudied, with limited knowledge of their consequences in daily life. Here, we investigated the nature of cognitive difficulties and their consequences for daily life from the perspective of adults with NT1.

Methods: In-depth, qualitative interviews were conducted with adults diagnosed with NT1 residing in the United States. Participants were recruited through (1) a patient advocacy organization (via social media and website); (2) a professional market research firm; and (3) participant referrals. Individual interviews were conducted by telephone, following a semi-structured guide, and lasted approximately 90 min. Qualitative analysis used an adapted grounded theory approach to identify key conceptual themes related to cognitive difficulties and their impacts on daily life.

Results: Of 46 participants, most reported experiencing some cognitive difficulties, with the most common being trouble remembering and difficulty with focus or sustained attention. Most participants characterized their difficulties with cognition as moderate or severe and reported these occurring daily. The qualitative findings informed the development of a conceptual model depicting cognitive difficulties and their broad impact on functioning and well-being in adults with NT1.

Conclusion: Cognitive difficulties in adults with NT1 are frequent, severe, and described as interfering with daily life activities and well-being. These data highlight a clear need to assess cognitive function in people with NT1 and identify treatments that address NT1-associated cognitive symptoms.

Introduction: Insomnia and hypertension frequently co-occur and may exacerbate cardiovascular risk. While acupuncture and related therapies (ARTs) are widely used for sleep symptoms, their comparative effectiveness across modalities remains unclear. This protocol outlines a Bayesian network meta-analysis (NMA) to compare the effectiveness of ARTs for insomnia in adults with hypertension and inform clinical decision-making.

Methods and analysis: This protocol follows preferred reporting items for systematic review and meta-analysis protocols (PRISMA-P) and is registered in PROSPERO. We will search PubMed, Embase, Cochrane Library (CENTRAL), Web of Science, and four Chinese databases (CNKI, Wanfang, VIP, and SinoMed) from inception to January 2026, and we will also screen WHO ICTRP, ClinicalTrials.gov, and ChiCTR without language restrictions. Eligible studies are randomized controlled trials enrolling adults with hypertension and insomnia, comparing an ART with sham, usual care, sleep hygiene, pharmacotherapy, or another ART. The primary outcome is change in global insomnia severity at post-treatment or at the first follow-up; secondary outcomes include sleep parameters, blood pressure, quality of life, mood, and adverse events. Pairwise meta-analyses will be performed using RevMan. A Bayesian random-effects NMA will be implemented in R (v4.4.1), with network plots and league tables generated in Stata (v15.1). The assumptions of transitivity and coherence will be assessed using design-by-treatment and node-splitting approaches; model fit will be evaluated using the deviance information criterion (DIC). Risk of bias will be assessed using RoB 2, and the certainty of evidence will be rated using GRADE adapted for NMA, with prespecified subgroup and sensitivity analyses.

Registration number: PROSPERO; identifier CRD420251173289.

Objective: This study employs bibliometric analysis to systematically examine global research trends and map the intellectual landscape of α-synuclein (α-syn) in Parkinson's disease (PD) from 2015 to 2024.

Methods: On January 14, 2025, bibliographic data were extracted from the web of science core collection (WOSCC) and PubMed. Using CiteSpace (version 6.2.R4), VOSviewer (version 1.6.20), the Bibliometrix R package (4.4.2), and Microsoft Excel 2024, we analyzed publication trends, geographic and institutional contributions, journal distributions, author distributions, co-cited references, and keyword co-occurrences.

Results: A total of 10,390 publications were included, with a steady annual growth (R² = 0.8741). The United States, China, and Germany were the top contributing countries. Leading institutions included the University of Cambridge and the University of Pennsylvania. Core journals such as Movement Disorders and International Journal of Molecular Sciences exhibited significant influence. Keyword clustering highlighted research hotspots, including neurodegeneration, aggregation, oxidative stress, Lewy bodies, and emerging diagnostic technologies like RT-QuIC. Important trends were identified in immune mechanisms, exosome-mediated propagation, gut-brain axis involvement, and cross-disease mechanisms.

Conclusion: The significance of α-syn in Parkinson's disease research is growing. Future efforts should emphasize mechanistic studies, biomarker validation, and targeted therapies to advance personalized medicine in PD.

Background: We aimed to explore the risk factors for early neurological deterioration after thrombolysis in patients with mild stroke. Machine learning model and logistic regression model were established. We compared them to facilitate early identification of patients with mild stroke who still experience early neurological deterioration after thrombolysis. It can alert the physician and clinical remedial measures can be prepared in advance.

Methods: We conducted a study on patients with mild stroke who underwent thrombolysis from April 1, 2017 to April 1, 2024 at emergency department. Four common machine learning methods-Extreme Gradient Boosting (XGBoost), K-Nearest Neighbors (KNN), Random Forest (RF), and Support Vector Machine (SVM)-were used to create predictive models based on the information of eligible participants. The unbalanced data was preprocessed using four different methods. Each machine learning model was paired with four preprocessing schemes, resulting in 16 workflows. Then, we selected the optimal machine learning model from them. Additionally, five methods were used to establish logistic regression models. The optimal logistic regression model was then selected from them.

Results: A total of 625 patients with mild stroke were included in the study, among whom 80 experienced early neurological deterioration after thrombolysis. Through 10-fold stratified cross-validation and simulated annealing algorithm, the optimal model among the four machine learning methods was selected as the SVM model that balanced the data through upsampling in 16 workflows. The area under the curve (AUC) of the SVM model was 0.889 (95% CI: 0.853, 0.926) in the training set and 0.859 in the test set processed by upsampling. Among the five methods used to establish logistic regression models, model m4 was the optimal one, with an AUC of 0.848 in the test set.

Conclusion: We explored the risk factors influencing the occurrence of early neurologic deterioration after thrombolysis in patients with mild stroke. We also found that logistic regression model and machine learning model demonstrated comparable performance in this single-center retrospective dataset.

Objective: To describe brain computed tomography (CT) features in Alzheimer's disease (AD) with comorbid cardiovascular diseases (CVDs) and examine associations with behavioral and psychological symptoms (BPSD).

Methods: This single-center, hospital-based observational case-control study (August 2019-May 2021) used consecutive sampling. We enrolled 165 older adults with AD and CVDs (CVD group), 165 older adults with AD without CVDs (AD-only group), and 165 cognitively healthy older adults (healthy controls). All participants underwent non-contrast brain CT at baseline. Qualitative CT findings [cortical atrophy, widened sulci, and medial hippocampal cerebrospinal fluid (CSF) pool widening] and quantitative parameters (lateral split brain width, frontal sulcus width, lateral ventricle width, third ventricle width, forehead index, and caudate nucleus index) were compared across groups. Diagnostic performance for AD (AD groups vs. healthy controls) was evaluated using receiver operating characteristic (ROC) curves and the area under the curve (AUC). BPSD were assessed with the Neuropsychiatric Inventory Questionnaire (NPI-Q), and correlations between NPI-Q scores and CT parameters were analyzed in the CVD group.

Results: Qualitative CT abnormalities were more frequent in both AD groups than in healthy controls (p < 0.05) but did not differ between the CVD and AD-only groups (p > 0.05). Quantitative CT parameters showed a similar pattern: both AD groups differed from healthy controls (p < 0.05), while comparisons between the two AD groups were not significant (p > 0.05). The combined diagnostic AUC for AD was 0.881. In the CVD group, higher NPI-Q total scores were associated with decreased lateral split brain width and increased frontal sulcus width, lateral ventricle width, third ventricle width, forehead index, and caudate nucleus index (all p < 0.05).

Conclusion: AD participants, with or without CVD comorbidity, showed significant CT abnormalities compared with healthy controls. In AD with CVDs, quantitative CT parameters were associated with BPSD severity.