Journal of Neurology最新文献

Background: Only a few longitudinal studies, with follow-up duration up to 3.6 years, have assessed the substrates of relapses and disability in aquaporin-4 (AQP4) IgG-positive neuromyelitis optica spectrum disorders (NMOSD), primarily focusing on clinical and conventional MRI variables.

Objective: We evaluated the association of clinical and MRI measures, including a comprehensive multimodal advanced MRI protocol, with key long-term clinical outcomes in AQP4 IgG-positive NMOSD patients over a median follow-up of 8.5 years (interquartile range [IQR] = 3.5; 13.3).

Methods: Forty-six NMOSD patients and 77 healthy controls underwent 3T brain MRI. In patients, neurological evaluations were collected at baseline and every six months. Time to first relapse and 6-month confirmed disability worsening (6m-CDW) were recorded. Lesion volume and topography, global and regional brain volumes, normal-appearing white matter and gray matter fractional anisotropy and mean diffusivity, choroid plexus volume, enlarged perivascular spaces number and glymphatic system function were assessed.

Results: During the follow-up, 30% patients experienced at least one clinical relapse, while 22% had 6m-CDW. Higher number of previous attacks (hazard ratio [HR] = 1.17, 95%-confidence interval [CI] = 1.04; 1.32) and presence of anterior optic pathway lesions (HR = 4.92, 95%-CI = 1.12; 21.852) were risk factors independently associated with a shorter time to a first clinical relapse; lower thalamic volume was marginally associated (HR = 0.93, 95%-CI = 0.87; 1.00). Presence of cervical cord lesions (HR = 3.93, 95%-CI = 1.16; 13.31) and lower normalized cortical volume (HR = 0.94, 95%-CI = 0.89;0.99) were risk factors independently associated with a shorter time to 6m-CDW; higher number of previous attacks contributed marginally (HR = 1.19, 95% = 0.99; 1.43). High efficacy treatments (HETs) delayed time to first relapse and 6m-CDW.

Conclusions: Previous attacks, optic nerve/spinal cord involvement, cortical/thalamic atrophy and the use of HETs associate with long-term outcomes in NMOSD.

Background and objectives: Age at onset is a key determinant of disease course in the general Parkinson's disease (PD) population, but its influence among GBA-PD remains undetermined. This study investigates whether age at onset affects cognitive decline in GBA-PD patients and compares symptoms between GBA-PD and nonGBA-PD groups, stratified by age of onset.

Methods: In this multicentric cross-sectional study, PD patients were stratified into early onset (< 50 years), intermediate onset (50-60 years), and late onset (> 60 years). Demographic-clinical data and scores of the Movement Disorder Society-Unified Parkinson's Disease Rating Scale (MDS-UPDRS), Montreal Cognitive Assessment (MoCA), Scales for Outcomes in Parkinson's Disease-Autonomic Dysfunction (SCOPA-AUT), and Beck Depression Inventory (BDI-II) were compared using ANCOVA. The effects of age of onset, GBA1 status, and their interaction were investigated. External validation on cognition was performed using data from the PPMI cohort.

Results: We analyzed 80 GBA-PD and 236 nonGBA-PD patients. Among GBA-PD, late-onset patients exhibited worse axial scores (p = 0.037), while early-onset had more severe motor complications (p = 0.007) and dysautonomia (p = 0.012). Age of onset and GBA1 status did not influence MoCA scores. Conversely, GBA1 status independently affected MDS-UPDRS parts I and II (p < 0.001 and p = 0.019, respectively) and BDI-II scores (p = 0.002). Analysis on the external dataset (PPMI) showed late-onset PD had lower MoCA scores (p < 0.001) and confirmed GBA1 status did not influence cognition.

Discussion: In the first decade of PD, cognitive decline is mainly age and duration dependent, irrespective of GBA1 genotype. Early onset does not increase cognitive risk in GBA-PD, supporting its relevance for counseling and treatment planning.

Objective: This study aimed to investigate the influence of different obesity-metabolic syndrome (MetS) statuses on mild cognitive impairment (MCI) and to explore the modifying roles of related factors.

Methods: Data were obtained from the China Health and Retirement Longitudinal Study (CHARLS, 2011-2015) and a real-world cohort (RWC). Binary logistic regression and restricted cubic spline models were used to examine the associations between obesity, MetS, and MCI, adjusting for covariates. In the RWC, the effects of obesity-metabolic phenotypes on cognitive function were further explored using structural magnetic resonance imaging (MRI) to evaluate brain atrophy.

Results: A total of 6079 participants from CHARLS and 522 from the RWC were included. Each additional MetS component increased the risk of MCI in females aged < 60 and 60-70 years. Low high-density lipoprotein (HDL) levels in older males negatively affected cognition, and elevated fasting glucose was significantly associated with poorer cognitive performance. Metabolically unhealthy non-obesity (MUNO) and metabolically unhealthy obesity (MUO) were associated with higher MCI risk both in males and females, while metabolically healthy obesity (MHO) in males aged 60-70 years was also linked to increased risk. RWC further revealed that MHO, MUNO, and MUO groups exhibited varying degrees of brain atrophy compared with healthy controls.

Conclusion: Findings from both cohorts suggest that obesity and metabolic health jointly influence cognitive impairment risk. Structural MRI results highlight that metabolic dysregulation may exacerbate obesity-related neurodegeneration.

Background: Immune effector cell-associated neurotoxicity syndrome (ICANS) is a frequent and potentially severe complication of anti-CD19 CAR T-cell therapy. Nevertheless, its neuroradiological characterization remains insufficiently defined, as most available evidence stems from retrospective cohorts, heterogeneous imaging protocols, or studies limited to pediatric populations.

Methods: We conducted a prospective, monocentric study including adult patients with B-cell lymphoproliferative disorders undergoing anti-CD19 CAR T-cell therapy. All patients underwent a standardized neurological and neuroradiological protocol, with brain MRI performed at screening (15-20 days before CAR T-cell infusion), 60 days, and 12 months after infusion, as well as urgently in the event of ICANS. Brain MRI records were reviewed by a panel of expert neuroradiologists.

Results: Of 154 treated patients, 112 were included. ICANS occurred in 34 patients (30.4%); 27 underwent urgent MRI, which showed abnormalities in 11 cases (40.7%). Two distinct radiological patterns emerged. The central variant pattern-characterized by symmetric involvement of thalami, hippocampi, brainstem, and variably the geniculate bodies or corpus callosum-was associated with severe ICANS and acute clinical deterioration, including two cases with diffuse centrum semiovale edema and intracranial hypertension. This pattern resolved in most cases on follow-up imaging. The stroke-like pattern consisted of focal cortico-subcortical white matter lesions, often DWI-restricted, appearing in both ICANS and asymptomatic patients, typically in subacute phases. These lesions persisted as non-enhancing FLAIR abnormalities at follow-up.

Conclusions: Serial brain MRI enabled identification of two specific ICANS-related imaging signatures with distinct temporal and radiological characteristics. While overall MRI sensitivity for ICANS remains low, pattern recognition improves diagnostic specificity, supports clinicians in the differential diagnosis, and provides insights into underling pathophysiology.

Background and objectives: Radiologically isolated syndrome (RIS) is the incidental finding of lesions typical for multiple sclerosis (MS) on magnetic resonance imaging in asymptomatic individuals. We investigated which environmental factors are associated with a first clinical event in RIS patients.

Methods: Subjects presenting as RIS (cases) or as clinically isolated syndrome (CIS)/relapsing-remitting multiple sclerosis (RRMS) at onset (controls) were included. Patients were administered an environmental questionnaire. The distribution of clinical and demographic characteristics and environmental factors was analysed. RIS subjects were divided according to time of conversion to MS and clinical and demographic characteristics and environmental factors were investigated as risk factors for conversion.

Results: Fifty-two RIS and 216 controls were included. Controls were younger at diagnosis (33.4 vs 39.0 years old), while RIS patients had more frequent onset with supratentorial symptoms (26.9% vs 8.3%). Spending more time outdoor during childhood was associated with a higher risk of a CIS/RRMS onset (odds ratio (OR) 0.24, 95% confidential interval (CI): 0.09-0.65, p = 0.0049). RIS that converted within 5 years were more likely to be underweight during adolescence (hazard ratio (HR) 11.57, 95% CI: 2.45-54.61, p = 0.0020), to have had pregnancy losses (HR 4.48, 95% CI: 1.35-14.88, p = 0.0145) and to have used assisted reproduction technology (ART) before RIS diagnosis (HR 20.42, 95% CI: 2.82-147.82, p = 0.0028).

Discussion: Being underweight during adolescence, the use of ART and a history of pregnancy losses led to a higher risk of conversion from RIS to MS. Outdoor activity during childhood was more frequent in patients with CIS/RRMS.

The Short-Term Memory Conjunctive Binding (STMCB) test assesses the ability to maintain integrated shape-colour associations in memory. It has been applied to detect Alzheimer's disease (AD) across the continuum, from preclinical stages and subjective cognitive decline (SCD) to dementia. The objective of the present study was to examine whether the STMCB test can differentiate individuals at very early stages of AD from controls. The sample included 67 participants with normal performance on standard neuropsychological tests. Participants were classified as controls or as having SCD based on self-reported memory complaints. Twenty-three controls and 44 individuals with SCD completed the STMCB test. All individuals also underwent a comprehensive neuropsychological evaluation, amyloid ([¹¹C]PIB) and FDG-PET scans. No significant group differences were observed in STMCB test performance between the groups. Furthermore, the STMCB test did not distinguish between amyloid-negative controls and SCD participants with amyloid pathology. These findings suggest that binding deficits may emerge later in the AD continuum, particularly when tau deposition or neurodegeneration is present.

Background: Interictal epileptiform discharges (IEDs) are transient spikes or waves that occur in electroencephalography (EEG) records and can help support the diagnosis and classification of epilepsy. High-throughput machine learning models aim to automate the detection of IEDs. Previous evaluations of machine learning models have reported non-inferiority compared to human experts, but these studies predominantly use small datasets of pre-selected, 'IED rich' records, which are not representative of clinical practice. Therefore, this study aims to analyse the accuracy of machine learning models in a large, routine, clinically representative cohort.

Methods: All routine EEGs performed in a large regional hospital in England were identified between June 2024 and February 2025. EEG records were run through the commercial machine learning model P15 and automated IED reports generated. The sensitivity, specificity, positive and negative predictive value of P15-detected IEDs were evaluated using the final clinical report as a reference standard.

Results: Of 484 EEG records, 53 were reported to contain at least one IED in the final clinical report. At P15's default sensitivity setting, sensitivity for IED detection was 81.1% (95% CI:77.6-84.6), specificity 59.9% (95% CI: 55.5-64.2), positive predictive value 19.9% (95% CI:16.3-23.5) and negative predictive value 96.3% (95% CI:94.6-98.0).

Discussion: This large-scale study of a machine learning model for identification of IEDs in a representative clinical population found a high negative predictive value suggesting that this may be a useful tool to rule out IEDs. However, the low positive predictive value demonstrates the potential for over-calling IEDs in routine EEGs. Future research should evaluate machine learning models alongside clinical feedback before this approach can have sufficient utility in direct clinical care.

Diabetic neuropathy (DN) is one of the most common and debilitating chronic complications of diabetes mellitus. It typically presents as a distal symmetric polyneuropathy (DSP), which is characterized by symmetric involvement of the distal extremities, manifesting as numbness, pain, paresthesia, and sensory loss. In addition to peripheral sensory involvement, patients may also experience autonomic neuropathy and focal nerve injuries. Persistent hyperglycemia can impair the structure and function of the nervous system through multiple interrelated mechanisms. Prolonged elevation of blood glucose levels induces non-enzymatic glycation reactions, leading to the excessive accumulation of advanced glycation end products (AGEs). These AGEs bind to their receptor RAGE, triggering a cascade of downstream signaling pathways, including ROS/NF-κB, JAK/STAT, and PKC, that promote oxidative stress and chronic inflammation. In addition, hyperglycemia exacerbates neural injury and impedes repair by disrupting microvascular integrity, altering immune cell function, disturbing ionic homeostasis within nerves, and inducing Schwann cells (SCs) apoptosis along with impaired production of neurotrophic factors. Currently, a variety of pharmacological agents are available for the treatment of DN, including gabapentin, pregabalin, methylcobalamin, α-lipoic acid, and aldose reductase inhibitors, either as monotherapy or in combination. These treatments can partially alleviate neurological dysfunction and neuropathic pain. This review summarizes the key mechanisms by which hyperglycemia induces nerve injury and highlights recent advances in pharmacological interventions. The aim is to provide a theoretical framework and therapeutic perspective to support both mechanistic research and clinical management of DN.