Journal of Neurology最新文献

Background: Studies on patients with spinal cavernous malformations (SCM) who were managed conservatively are scarce. We aimed to assess clinical, functional, and patient-reported outcomes in these patients.

Methods: This single-center cohort study included consecutive adult patients with SCM, diagnosed in 1995-2024, who underwent conservative management as the primary treatment strategy and had ≥ 6 months of follow-up. We retrospectively analyzed events of symptomatic hemorrhage (SH) and/or focal neurological deficits (FND) and conducted cross-sectional telephone and questionnaire follow-up. We evaluated functional outcome on the modified Rankin Scale (mRS) and quality of life using EuroQol 5-dimensions 5-levels (EQ-5D-5L) and Patient-Reported Outcome Measurement Information System 29 (PROMIS-29).

Results: We identified 30 patients with SCM, of whom 28 were included (median age 47 years [IQR 36-61], 32% women). Nine (32%) initially presented with SH, 10 (36%) with FND, and 9 (32%) incidentally. During a median follow-up of 6.4 years (IQR 4.0-10.6), 10 (36%) patients experienced SH/FND and 5 (18%) underwent surgical intervention. The annual rate of SH/FND was 5.1% (95% CI 2.5-9.4%). At final follow-up, 26 (93%) patients completed the questionnaire and 16 (57%) were functionally independent (mRS ≤ 2). Patients had lower utility-weighted EQ index scores than the general population (0.63 versus 0.87, p < 0.001) and reported more PROMIS-29 anxiety/fear (56.8 versus 50.3, p = 0.002), depression/sadness (55.9 versus 50.3, p = 0.023), and fatigue (55.2 versus 49.4, p = 0.029).

Conclusions: Among 28 conservatively managed patients with SCM, 23 (82%) did not require surgical treatment during follow-up and the majority remained functionally independent. However, patients do report worse health than the general population, particularly mental health.

Background: Health-related quality of life (HRQoL) is a key outcome in the management of vestibular schwannoma (VS). Although wait-and-scan (W&S), stereotactic radiosurgery (SRS), and microsurgery (MS) are established management strategies, their comparative effects on HRQoL remain unclear. This systematic review and meta-analysis aimed to synthesize HRQoL outcomes using the Penn Acoustic Neuroma Quality of Life (PANQOL) questionnaire and to pool PANQOL scores for W&S, SRS, and MS.

Methods: A systematic search of PubMed and Embase was conducted up to February 2025. Eligible studies included patients with unilateral sporadic VS managed with W&S, SRS, or MS, with HRQoL assessed by PANQOL at least one year after diagnosis or intervention. Pooled mean PANQOL scores were calculated using single-arm meta-analyses. Minimal clinically important differences (MCIDs) were applied to assess relevance.

Results: 16 studies including 3745 patients were analyzed. The pooled PANQOL total score was 69.1 (95% CI 66.0-72.2) for W&S (n = 1,430), 66.9 (95% CI 62.7-71.2) for SRS (n = 864), and 61.3 (95% CI 57.2-65.4) for MS (n = 1451). Across domains, scores were the lowest for hearing and energy and the highest for facial function and anxiety. None of the between-strategy differences in total or domain scores exceeded established MCID thresholds. Substantial heterogeneity was present across all analyses (I² > 75%).

Conclusion: Patients with unilateral VS report broadly comparable HRQoL following W&S, SRS, or MS. Although numerical differences in PANQOL scores exist, they are not clinically meaningful. The observed heterogeneity highlights the need for standardized, prospective studies and international collaboration to better inform patient-centered decision-making.

Background: Digital monitoring shows promise for detecting disease activity in people with relapsing-remitting multiple sclerosis (PwRRMS). Here, we study associations between digital biomarkers for cognition and walking ability and radiological disease activity.

Methods: In a prospective, 1-year cohort study, PwRRMS performed the smartphone-based symbol digit modalities test (sSDMT) and 2-min walk test (s2MWT) on weekly basis. MRIs and the clinical SDMT (cSDMT), expanded disability status scale (EDSS), timed 25-foot walk (T25FW) and nine-hole peg test (NHPT) were collected at baseline and every 3 months. Associations were determined using logistic generalized estimating equations. For the digital measures, associations were also analyzed using a hybrid model and were repeated with values from 6 weeks before and after MRI.

Results: We included 57 PwRRMS. The sSDMT was negatively associated with contrast-enhancing lesions (CELs) (OR_overall 1.80, 95% CI 1.12-2.91), predominantly caused by variation within individuals (OR_{within-subjects} 4.37, 2.05-9.33), with a similar relation using sSDMT values 6 weeks prior to MRI (OR_overall: 1.92, 0.947-3.90, OR_{within-subjects}: 13.7, 1.74-107). The negative association between s2MWT and CELs (OR_overall 1.20, 1.04-1.38) was caused equally by variation within and between individuals. All clinical measures were negatively associated with CELs: T25FW (OR_overall 2.23, 1.50-3.32), EDSS (OR_overall 1.49, 0.932-2.39), cSDMT (OR_overall 1.20, 1.02-1.42) and NHPT (OR_overall 1.15, 1.04-1.27).

Discussion: Digital biomarkers show to be capable of measuring changes in individuals when inflammation is detectable on MRI, with the sSDMT additionally capturing changes 6 weeks prior to the MRI, suggesting that early identification of inflammation using these biomarkers may be possible.

Background: Parkinson's disease (PD) and multiple system atrophy with parkinsonian type (MSA-P) share various motor and nonmotor symptoms, complicating early differential diagnosis, although prognosis and levodopa response differ.

Objectives: To develop a machine learning model using balance analysis to differentiate early-stage PD and MSA-P.

Methods: We enrolled 22 healthy controls (HC), 20 PD, and 17 MSA-P patients within three years of onset. Participants stood for 60 s on dual force-plates under eyes open (EO) and eyes closed (EC). Seven center of pressure (COP) parameters per condition and EC-EO differences were analyzed. Group differences were assessed with ANOVA. Feature selection was performed using LightGBM (LGBM), followed by model training with fourfold cross-validation.

Results: Mean ages were 63.8 (HC), 64.2 (PD), and 68.8 years (MSA-P). Disease durations were 2.4 years in PD and 1.8 years in MSA-P. Except for mean distance in the anteroposterior direction with EO and 95% confidence ellipse area with EC, all parameters showed significant group differences. Post-hoc analysis revealed significant differences between HC and PD/MSA-P in EO, whereas in EC, differences were more pronounced between MSA-P and PD/HC. The LGBM model achieved 81.4% accuracy in distinguishing PD from MSA-P, 94.9% in distinguishing healthy controls from patient groups, and 84.9% for three-group classification.

Conclusion: Balance biomarker, which analyzes the balance parameters with machine learning model could differentiate early-stage PD and MSA-P with high accuracy.

Blood-based biomarkers for Alzheimer's disease (AD) have demonstrated high performance in identifying amyloid-β (Aβ) pathology. However, the diagnostic accuracy of commercial plasma biomarker assays in predicting PET-defined AD stages-particularly late-stage tau accumulation-requires further evaluation. We included 229 participants from the Alzheimer's Disease Neuroimaging Initiative, all of whom underwent amyloid and tau PET imaging and testing with plasma assays. Among the plasma biomarkers, p-tau217 showed the strongest linear and non-linear associations with amyloid and tau PET. When distinguishing A + from A - T - participants, p-tau217 assays achieved the highest accuracy (AUC range: 0.85-0.91), outperforming other plasma biomarkers (AUC range: 0.66-0.81). However, the accuracy of plasma biomarkers, including p-tau217 assays, significantly decreased when differentiating A + T + from A + T - stages (AUC for p-tau217 assays: 0.69-0.77; AUC for other plasma biomarkers: 0.53-0.67; P < 0.05). These findings were replicated in an independent cohort (n = 334). Our study found that among currently available commercial plasma assays, including p-tau217 assays, they demonstrate high accuracy in classifying Aβ status but are less accurate in assessing tau pathology severity in Aβ positive individuals.

Introduction: In multiple sclerosis (MS), depression and anxiety are common, yet their relation to disease progression is unclear. We investigated whether Hospital Anxiety and Depression Scale (HADS) symptoms predict neurological disability progression.

Methods: In our prospective cohort of people with primary progressive MS (PPMS), depressive and anxiety symptoms were assessed using HADS. Disability progression at 1 and 2 years was assessed using three predefined endpoints: (1) Expanded Disability Status Scale (EDSS), (2) a three-variable composite endpoint (EDSS, Timed 25-Foot Walk (T25FW), or Arm Function in Multiple Sclerosis Questionnaire (AMSQ)), and (3) a five-variable composite endpoint (EDSS, T25FW, AMSQ, Symbol Digit Modalities Test (SDMT), or Patient-Determined Disease Steps (PDDS)). Logistic regression modelled whether HADS scores predicted disability progression. Boruta feature selection identified the most informative HADS items.

Results: One hundred eleven adults with PPMS completed the HADS (all ≥ 1-year follow-up; 62 ≥ 2 years). Progression occurred predominantly on individual domains. At 1 year, higher total HADS scores predicted progression on the five-variable composite endpoint (OR 3.10, [95% CI 0.99-9.75], p = 0.05; AUC 0.59, [95% CI 0.47-0.70]). At 2 years, the depression sub-score consistently predicted progression on EDSS (OR 8.88, [95% CI 1.12-70.66], p = 0.04), and the five-variable composite endpoint (OR 9.46, [95% CI 1.50-59.52], p = 0.02). Boruta feature selection identified HADS depression-associated items 6 and 8 as best predictors; together achieving similar predictive accuracy compared to the full HADS questionnaire.

Conclusion: Higher HADS scores, particularly depressive symptoms, predicted disability progression. These findings indicate prognostic value of patient-reported outcomes in predicting disease worsening and their potential use in guiding personalised treatment in progressive MS.

Background: Myasthenia gravis (MG) is an autoimmune disease with an onset age distribution in women, which peaks within the reproductive age range, leading to a potential interference with pregnancy. In this systematic review, we aim to assess the impact of pregnancy on the course of MG during pregnancy and postpartum period and to identify potential risk factors influencing the postpartum course.

Methods: A systematic literature search was conducted in the two databases PubMed and Epistemonikos on the topic "Myasthenia gravis and pregnancy" in October 2025. We included cohort studies and case series with at least 5 cases, reporting the clinical course of MG in women during pregnancy or postpartum period. Quality assessment was performed using the Critical Appraisal Skills Programme (CASP) tool for cohort studies.

Results: In total, 34 studies were included, covering 3720 pregnancies in women with MG. Of 842 pregnancies worsening myasthenic symptoms was reported in 30% of pregnancies most frequently in the first trimester. Postpartum exacerbations were observed in 27% of the cases. However, incidence of worsening and scoring systems differed vastly. Preterm birth was reported at a rate of 9%. Vaginal delivery and cesarean section were performed in 68% and 32% respectively. Of 1530 infants, 9% developed neonatal myasthenia gravis.

Conclusion: This review confirms that symptom worsening is most common in the first trimester or postpartum. Women with MG were more likely to require cesarean section or operative vaginal delivery compared to general population data. However, the studies' quality varied widely. Prospective studies are needed to better identify risk factors for complicative course during pregnancy and postpartum period.

Background: Episodic ataxia type 2 (EA2) results from pathogenic variants in CACNA1A that encodes the CaV2.1 P/Q-type calcium channel. The molecular basis of cognitive impairments requires further elucidation in EA2.

Objective: To correlate AI-predicted structural alterations of the CaV2.1 channel with intellectual function observed in patients with EA2.

Methods: Using AlphaFold3, we modeled the wild-type and variant CACNA1A proteins. Structural similarity between the wild-type and variant proteins was quantified using the Template Modeling (TM) score. To assess degree of truncation, the relative amino acid length ratio (AA%) was also calculated. These protein-level metrics were then compared with the standardized intellectual indices in 13 patients with EA2.

Results: The TM scores ranged from 0.624 to 0.838, and showed a strong correlation with most intellectual indices, including the full-scale IQ (FSIQ, r = 0.722, p = 0.005), verbal comprehension index (VCI, r = 0.834, p < 0.001), perceptual reasoning index (PRI, r = 0.624, p = 0.023), and working memory index (WMI, r = 0.700, p = 0.008). The AA% ranged from 50.6% to 100%, and also showed a correlation with VCI (r = 0.566, p = 0.044) and WMI (r = 0.649, p = 0.016), but less consistently when compared to the TM score.

Conclusions: Structural preservation of CaV2.1 correlates more strongly with intellectual function in patients with EA2 than protein length, which suggests that structural disruption of the CaV2.1 channel may contribute to cognitive impairments in EA2. AI-based protein modeling is a valuable tool for linking genotype to phenotype, particularly in channelopathies with diverse clinical presentation.

Background: Freezing of gait (FOG) is a key contributor to gait impairment in people with Parkinson's disease (PD). Previously, we found freezing-specific increased effective connectivity from the dorsolateral prefrontal cortex (DLPFC) to the mesencephalic locomotor region (MLR), but it is yet unknown whether effective connectivity changes with FOG progression.

Objective: The primary objective of this study was to evaluate effective connectivity changes in freezers over time and their association with gray matter structural alterations.

Methods: In this longitudinal study, spanning 2 years, we analyzed 51 patients (27 freezers and 24 non-freezers) for the main effective connectivity, and 88 patients (44 freezers and 44 non-freezers) and 37 age-matched healthy controls for structural volume analysis. Spectral dynamic causal modeling (DCM) with hierarchical empirical Bayes approaches was performed.

Results: Freezers reported a significant worsening of FOG over time. Longitudinally, abnormally increased functional connectivity was observed between the bilateral cerebellar lobule VIIb and the MLR. Spectral DCM revealed that the previously identified increase in DLPFC-to-MLR effective connectivity was lost at follow-up. In contrast, an increased inhibitory effective connectivity from the left cerebellar lobule VIIb to the right MLR emerged (posterior probability > 0.99). This was associated with slower FOG progression, but not with structural volume changes.

Conclusions: We found that the pattern of FOG-related effective connectivity changed over time, characterized by increasing inhibitory connectivity from the cerebellum to MLR, while frontal compensatory influences were no longer apparent. Future study needs to focus on how compensatory cortical mechanisms could be optimized to counteract FOG progression.

Clinical trial registration: This study was registered in the University Hospital Medical Information Network Clinical Trial Registry (UMIN-CTR 000036570) on 22 April 2019.