Frontiers in Neurology最新文献

Background: Abdominal migraine (AM) is an episodic syndrome characterized by recurrent, self-limiting episodes of abdominal pain with autonomic features, now recognized to affect both children and adults according to ICHD-3 criteria. Its diagnosis is clinical and requires the exclusion of organic gastrointestinal or renal diseases, yet no standardized treatment exists, leading to therapeutic approaches often adapted from migraine management. Challenges in diagnosis, due to difficulties in symptom description by children and cognitive biases in adults, frequently result in underdiagnosis, repeated consultations, and diminished quality of life. This study aims to analyze the clinical characteristics, diagnostic and therapeutic approaches, and outcomes of AM in pediatric and adult patients based on a large case series.

Methods: A systematic literature review was conducted per PRISMA guidelines. Major databases were searched from inception to June 2025 for case reports and clinical studies on AM. Data on demographics, clinical presentation, treatment, and outcomes were extracted and analyzed.

Results: We included 662 patients (629 children, 33 adults) from 63 studies. The female-to-male ratio was 1.6:1. The median age at onset was 4.2 years in children and 31.0 years in adults, with diagnostic delays of 3.1 and 4.0 years, respectively. Among cases with specific data, periumbilical pain was reported in 43.3% (of 223), while nausea (66.1%), vomiting (53.6%), and headache (47.1%) were common in a cohort of 448 cases. Photophobia, pallor, and anorexia were also frequently observed. Triptans showed the highest acute efficacy (98.04%, 50/51), versus 62.5% (5/8) for NSAIDs. Prophylactics were highly effective: anticonvulsants (95.0%, 19/20), beta-blockers (100%, 12/12), and antihistamines (92.8%, 64/69). These exceptional rates likely reflect reporting bias and require prospective validation.

Conclusion: AM presents with significant clinical heterogeneity but shares core features with migraine disorders. Early diagnosis and management, potentially incorporating agents used in migraine (such as triptans and prophylactics) based on preliminary evidence, may improve outcomes, though this requires confirmation in controlled studies. Increased awareness of non-gastrointestinal symptoms and migraine history is essential for accurate diagnosis.

Background: This study aimed to develop and validate a deep learning model based on preoperative MRI to non-invasively predict Telomerase Reverse Transcriptase (TERT) promoter mutation status in glioma patients.

Methods: A retrospective cohort of 100 patients with histologically confirmed high-grade glioma was included. Regions of interest (VOIs) were manually annotated on contrast-enhanced T1-weighted MRI sequences by senior radiologists. Five deep learning models (RegNet, GhostNet, MobileNet, ResNeXt50, ShuffleNet) were trained and evaluated using accuracy, precision, recall, and F1-score. The dataset was split into training (80%) and internal validation (20%) sets.

Results: RegNet achieved the highest performance with an accuracy of 0.7742, recall of 0.8704, precision of 0.7163, and F1-score of 0.7023. It demonstrated superior ability to capture imaging features associated with TERT mutations compared to other models. The area under the ROC curve (AUC) for RegNet was 0.7182, indicating moderate discriminative power.

Conclusion: The RegNet model effectively predicts TERT promoter mutation status from routine MRI, offering a non-invasive tool for preoperative molecular subtyping of glioma. This approach may facilitate personalized treatment planning and address limitations of invasive tissue-based diagnostics. Further validation with multi-center data is warranted to enhance clinical applicability.

Introduction: This study aims to rigorously evaluate the consistency and reliability of a pluripotent stem cell (PSC) differentiation system and explore how the KCNB1 mutation disrupts the temporal regulation of gene expression during neuronal differentiation and modulates neuron function-related pathways.

Methods: Induced pluripotent stem cells (iPSCs) derived from a patient carrying a KCNB1 variant (c.990G > T, p.Glu330Asp) and from a healthy donor were differentiated into neurons. Differentiation and RNA expression were assessed at multiple time points. Immunofluorescence, RNA sequencing, fuzzy c-means clustering, and pathway analyses were performed.

Results: The differentiation system was successfully established, with cells exhibiting stage-appropriate morphology and maturing into neurons. RNA sequencing revealed consistent gene expression patterns at the neural progenitor cell (NPC) stage but significant differences at the neuron stage between the KCNB1 mutant patient and the healthy donor. Notably, KCNB1 expression was lower in the patient's neurons. Genes specifically clustered in healthy neurons were enriched in synapse-related pathways, while genes clustered in patient neurons were associated primarily with basic cellular metabolism pathways and abolished neuron-specific pathways.

Conclusion: Low expression of KCNB1 disrupts the temporal pattern of gene expression and related neuron-specific pathways during neuronal differentiation and impairs neuronal differentiation and maturity.

Background: Patient-reported outcome measures (PROMs) are increasingly used for symptom monitoring and care delivery, yet their prognostic value for identifying patients at higher risk for mortality in neurological populations is unclear. This systematic review evaluated whether PROMs predict mortality and/or survival in adults with neurological conditions.

Methods: We systematically searched MEDLINE, Embase, and the Cochrane Central Register of Controlled Trials (January 2002-November 2024) for studies incorporating PROMs into mortality or survival prediction models across 10 neurological conditions: motor neuron disease, diabetic neuropathy, nervous system cancers, Alzheimer's and other dementias, Guillain-Barré syndrome, epilepsy, headache, multiple sclerosis, Parkinson's disease, and stroke. Screening, data extraction, and risk-of-bias assessment followed the CHARMS and PRISMA guidelines. Findings were descriptively summarized.

Results: Of 6,218 abstracts reviewed, 49 studies met the inclusion criteria. Most evaluated stroke (n = 16), nervous system cancers (n = 14), or motor neuron disease (n = 9). None evaluated headache, diabetic neuropathy, Guillain-Barré syndrome, or epilepsy. Of the included studies, 26 used generic PROMs, 19 used condition-specific PROMs, and 4 included both. Across conditions, PROMs independently predicted mortality in three-quarters of studies, with the strongest evidence observed in nervous system cancers and motor neuron disease. By instruments, EORTC QLQ in brain cancers and SF-36 in stroke showed the most consistent prognostic utility. Among studies with mixed findings by domain, physical health components were more likely to predict mortality than emotional components.

Conclusion: PROMs independently predict mortality in several neurological conditions, though prognostic value varied by condition and instrument type. Future studies should evaluate their additive value and feasibility for integration into prognostic models in routine care.

Objective: To investigate the correlation between the neutrophil-to-apolipoprotein A1 ratio (NAR) and disease severity, long-term prognosis, and risk of relapse in patients with anti-N-methyl-D-aspartate receptor (anti-NMDAR) encephalitis.

Methods: This study included 125 patients with anti-NMDAR encephalitis as a retrospective cohort. Baseline clinical, laboratory, and imaging data was collected. Spearman's correlation analysis was used to evaluate correlations between NAR, disease severity, and C-reactive protein (CRP) levels. Logistic regression and Cox proportional hazards models were used to analyze independent associations between NAR and poor prognosis and recurrence, respectively. The predictive performance of NAR was evaluated using receiver operating characteristic (ROC) curves. Mediation analysis was used to explore potential pathways of action. Sensitivity and subgroup analyses were performed to verify the reliability of the results.

Results: The final modified Rankin's score (mRS) score and recurrence rate were significantly higher in the high-NAR group than in the low-NAR group (both p < 0.05). NAR significantly and positively correlated with the initial mRS score (r = 0.308, p < 0.001) and CRP level (r = 0.486, p < 0.001). Multivariate analysis showed that NAR was an independent risk factor for poor prognosis (OR = 1.19, 95% confidence interval (CI): 1.02-1.38, p = 0.026) and recurrence (Hazard ratio (HR) = 1.13, 95% CI: 1.02-1.24, p = 0.017). ROC curve analysis showed that the area under the curve (AUC) for predicting poor prognosis with NAR was 0.724, the optimal cutoff value was 10.34, and the specificity was 92.2%. Mediation analysis showed that disease severity partially mediated the relationship between NAR and prognosis (effect rate, 41.7%).

Conclusion: NAR is an independent predictor of poor disease prognosis and risk of recurrence in patients with anti-NMDAR encephalitis. Its high specificity helps identify high-risk patients early and accurately, giving this biomarker long-term prognostic value.

Purpose: This study aimed to investigate the diagnostic value of somatosensory evoked potentials (SEPs) in patients with paroxysmal sympathetic hyperactivity (PSH) and to identify independent predictors of the condition.

Methods: A retrospective cohort study was conducted on 123 patients with prolonged disorders of consciousness (PDOC) admitted to the Critical Care Rehabilitation Department of Nanjing Jiangning Hospital between August 2022 and August 2024. Patients were classified into PSH-positive (PSH+) and PSH-negative (PSH-) groups according to the Paroxysmal Sympathetic Hyperactivity Assessment Measure (PSH-AM). Demographic, clinical, and SEPs parameters were collected. Univariate and multivariate logistic regression analyses were employed to examine the association between these variables and PSH. The predictive performance was evaluated using receiver operating characteristic (ROC) curve analysis.

Results: A total of 123 patients with prolonged disorders of consciousness were enrolled in the study. Among these, 34 patients (27.64%) were classified into the PSH + group and 89 patients (72.36%) into the PSH - group. Multivariate logistic regression analysis identified younger age (OR = 0.96, 95% CI: 0.92-0.99, p = 0.02), male patient (OR = 0.28, 95% CI: 0.09-0.75, p = 0.02), and reduced N20-P25 amplitude (OR = 0.34, 95% CI: 0.13-0.70, p = 0.01) as independent predictors of PSH. Using a cut-off value of 1.19 μV for the N20-P25 amplitude, the area under the curve (AUC) for discriminating PSH was 0.811 (95% CI: 0.71-0.912), yielding a sensitivity of 79.7% and a specificity of 75%. The combination of these three predictors improved the AUC to 0.846 (95% CI: 0.75-0.942). After adjusting for potential confounders, partial correlation analysis demonstrated a significant negative correlation between N20-P25 amplitude and PSH-AM score (adj. r = -0.30, p = 0.003).

Conclusion: A reduced N20-P25 amplitude may serve as an independent and objective electrophysiological biomarker for the early prediction of PSH. In combination with younger age and male patient, it contributes to the identification of high-risk populations and offers valuable guidance for clinical management.

Background: Accurate prediction of functional recovery after thoracolumbar fracture with incomplete spinal cord injury (SCI) remains challenging. We aimed to identify independent predictors and develop a validated model for 12-month functional outcome.

Methods: In this single-center, retrospective cohort study (January 2018-December 2024), consecutive adults (≥18 years) with acute T11-L2 fractures and admission American Spinal Injury Association Impairment Scale (AIS) grade B, C, or D were enrolled. Functional recovery was defined as ≥1 AIS grade improvement plus ≥10-point Spinal Cord Independence Measure version III (SCIM-III) gain at 12 months. Candidate predictors (n = 23) were selected a priori based on literature review and expert consensus. Missing data (<8% per variable) were multiply imputed (m = 20). Multivariable logistic regression with Firth's correction and backward elimination guided by Akaike Information Criterion was used. Model discrimination [optimism-corrected area under the curve (AUC) 0.87] and calibration (Hosmer-Lemeshow test) were assessed by 1,000 bootstrap resamples. Pre-specified subgroup analyses examined age, AIS grade, surgical timing and lesion length.

Results: Among 1,032 eligible patients, 206 (20.0%) achieved functional recovery. Eight predictors were independently associated: admission AIS grade (OR 4.5 per grade, 95% CI 3.5-5.8), motor score (OR 1.05 per point, 1.03-1.07), intact posterior ligamentous complex (OR 2.3, 1.6-3.2), decompression ≤ 24 h (OR 1.9, 1.4-2.7), non-smoking (OR 1.7, 1.2-2.4), Charlson Comorbidity Index = 0 (OR 1.5, 1.1-2.1), shorter intramedullary T2 lesion length (OR 0.96 per mm, 0.95-0.97) and rehabilitation intensity ≥3 h/day (OR 1.4, 1.0-1.9). The final model demonstrated an optimism-corrected AUC of 0.87 (95% CI: 0.85-0.89) and calibration characteristics with a calibration slope of 1.02, an intercept of 0.01, and a Hosmer-Lemeshow p-value of 0.18 during internal validation. Predictive effects were stronger in younger, AIS B/C patients and when surgery was performed early.

Conclusion: A parsimonious eight-factor model showed robust discrimination and satisfactory calibration in internal validation for 12-month functional recovery after thoracolumbar incomplete SCI, enabling individualized prognostication. External validation in independent multicenter cohorts is required before clinical implementation and treatment decision-making.