Journal of Neurology最新文献

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.

Background: Globoid cell leukodystrophy (GLD) is a progressive neurodegenerative disease caused by galactocerebrosidase deficiency. Juvenile phenotypes-onset between ages 3 and 16-account for up to 25% of cases. Hematopoietic stem cell transplantation (HSCT) is the only available treatment, yet only eight juvenile-onset cases treated with HSCT have been reported, with heterogeneously collected data. We aim to comprehensively evaluate long-term neurological outcomes post-HSCT in juvenile GLD.

Methods: We conducted a retrospective study of all juvenile GLD patients treated with HSCT and followed at our Institution. We assessed survival, neurological status, disability (modified Rankin Scale), cognitive outcomes, GALC activity, serial MRIs (Loes score), evoked potentials (internal scoring system), and nerve conduction studies at pre-HSCT, first post-HSCT visit, and last follow-up.

Results: Six biochemically and genetically confirmed juvenile GLD cases were included. Four were symptomatic at diagnosis; two were pre-symptomatic. All survived to last follow-up (range 9 years, 2 months-19 years, and 8 months). Four achieved near-normal cognitive, motor, and functional status. Two symptomatic patients-with extensive pre-HSCT white matter disease and specific pre-HSCT clinical features (epilepsy and cognitive impairment)-had suboptimal outcomes. Loes scores stabilized/improved in four patients; GALC enzyme activity normalized in all. Electrophysiological measures mostly remained stable.

Conclusions: HSCT significantly impacts the natural history of juvenile GLD, resulting in largely optimal long-term outcomes, preserved quality of life, and minimal disability. Standardized pre-transplant assessments are critical. High pre-HSCT Loes scores, epilepsy, and cognitive impairment could be prognostic indicators, highlighting the importance of early intervention based on comprehensive instrumental evaluations.

Background: Orthostatic tremor (OT) is a rare, heterogenous disorder, recently sub-classified into primary OT (isolated 13-18 Hz tremor), OT-plus (OT with additional neurological features) and pseudo-OT (OT with frequencies < 13 Hz). However, to our knowledge no study to date has compared clinical characteristics between all three subgroups.

Objectives: We aim to further define and compare the clinical characteristics of the three different OT subgroups, utilising one of the largest described single centre cohorts to date.

Methods: A retrospective analysis was undertaken of clinical records from 74 OT patients at Charing Cross Hospital between 1999 and 2023, enabling categorisation into subgroups. Clinical characteristics, including treatment efficacy and overall disability, were subsequently described and compared between subgroups.

Results: 61 primary OT, 5 OT-plus and 8 pseudo-OT patients were identified. Baseline demographics were comparable between subgroups. Logistic regression suggested age of onset (OR = 1.02, p = 0.229), symptom duration (OR = 1.05, p = 0.083), tremor frequency (OR = 1.02, p = 0.826) and subgroup (OT-plus (OR = 1.86, p = 0.565) and pseudo-OT (OR = 1.41, p = 0.683)) were not significant predictors of disability. Treatment response varied between subgroup, with primary OT and pseudo-OT patients more frequently reporting symptomatic improvement with clonazepam, gabapentin and/or alprazolam than OT-plus patients.

Conclusions: We provide further insight into the clinical phenotypes of the OT subgroups and encourage future studies to validate these findings with larger sample sizes and establish reliable tools to measure OT severity to better assess disease progression and treatment response.

Background: Although many patients with Parkinson's disease (PD) report experiencing episodes of freezing of gait (FOG) at home under ON medication ("On-meds") conditions, objective and accurate diagnosis of different types of FOG events remains an extremely challenging task.

Methods: We conducted an observational, case-control study enrolling 75 consecutive PD patients, who were classified into "freezer" (n = 50) and "non-freezer" (n = 25) group, based on responses to the FOG Questionnaire and clinical confirmation. A modified timed up and go (TUG) protocol comprised one single‑task TUG (sTUG) and two dual‑task TUGs (cognitive, manual). Synchronized video and a single wearable sensor (Ambulosono) provided parallel capture for real‑time detection and subtyping of FOG.

Results: In the "freezers" group, 337 FOG episodes occurred during TUG testing, whereas none were recorded in the "non‑freezers" group (p < 0.01). The mean frequency was 2.25 FOG episodes per person per test. Compared with the sTUG test (74 FOG episodes), dual-task trials identified 263 FOG episodes, representing a 255% increase (p < 0.01). Trembling, shuffling and akinetic subtypes were identifiable on the device display (GMGI), with sensitivity 87.2% and specificity 89.5% versus video. Wearable data also localized subtypes by gait phase (initiation, turning, midway and ending).

Conclusions: "On-meds" FOGs can be objectively diagnosed among self-reported freezers using a dual task protocol during gait tests. Parallel video and wearable sensor recordings facilitate the real-time detection and subtyping of "On-meds" FOGs, which can substantially improve the current clinical practice.