BMC Neurology最新文献

Background: Reversible cerebral vasoconstriction syndrome (RCVS) is characterized by severe headaches, often thunderclap headaches, and a multifocal constriction of the cerebral arteries. Although RCVS can occur spontaneously, some cases occur after exposure to drugs. We describe the first case of RCVS in which methylphenidate, a drug with vasoconstrictive properties, is the only suspected drug. Still an unexpected adverse drug reaction of methylphenidate, and so far observed with the concomitant use of vasoactive drugs and methylphenidate, RCVS can be observed when methylphenidate is used alone.

Case presentation: A 44-year-old French female presented with sudden onset of severe thunderclap headache during exercise. She had been treated for about 2 years with 54 mg extended-release MPH twice a week for attention deficit / hyperactivity disorder. After clinical, biological and imaging examinations, clinicians concluded to a highly probable RCVS diagnosis, probably linked to methylphenidate use. Major causes of RCVS were ruled out and the methylphenidate treatment was discontinued. The outcome was favourable with nimodipine treatment. We also describe two other cases of methylphenidate induced RCVS recorded in French Pharmacovigilance Database. Moreover, RCVS is an adverse reaction reported more frequently than expected with methylphenidate in the International Pharmacovigilance Database (VigiBase®), suggesting a pharmacovigilance signal. Given its pharmacodynamics, i.e. pre-synaptic dopamine and norepinephrine reuptake inhibition, methylphenidate is theoretically likely to contribute to this vascular event.

Conclusions: The role of methylphenidate needs to be considered in case of RCVS diagnosis observed in a treated patient. Although the frequency of this potential adverse drug reaction is expected to be rare, clinicians should be aware of its possible occurrence, given the ever-increasing use of methylphenidate.

Objective: The study aims to identify characteristics that impact the postoperative prognosis and recurrence of intracranial dissecting aneurysms (IDA) patients treated using multi-stent overlapping techniques.

Methods: Clinical data from 69 IDA patients treated with multistate-assisted spring coil embolization at the hospital between January 2017 and October 2023 were retrospectively reviewed, including clinical and imaging data gathered at admission and discharge. The prognosis was determined based on mRS grade at discharge, and the patients were divided into excellent prognosis (mRS 0-2 points) and poor prognosis (mRS 3-6 points). They were split into two groups: recurrence and no-recurrence, based on whether the patients had recurrence during surgical follow-up. The patient's clinical information and aneurysm data were compared between the two groups to better understand the efficacy of multi-stenting for IDA and to investigate the factors that influence the good or negative prognosis of multi-stenting for IDA and recurrence.

Results: The prognosis was poor in 10 patients, 7 of whom died, while 59 had an excellent prognosis. Hunt-Hess classification (χ2 = 25.503a, P = < 0.01), hospitalization days (t=-3.873, P < 0.01), operation time (t=-1.970, P = 0.049), and aneurysm height (t=-1.969, P = 0.049) were all significant. 62 patients were discharged with 4 postoperative recurrences and 58 without recurrences in patients treated with multiple stents, with significant differences in the largest diameter (t=-2.235, P = 0.025), basal length (t=-2.149, P = 0.032), and position(located in pica base or not ) (χ2 = 10.955a, P = 0.001). The postoperative recurrence rate was 5.8%, but 85.8% reported satisfactory neurologic function (mRS ≤ 2). The case fatality rate was 10.1%.

Conclusion: Hunt-Hess grading on admission, aneurysm high, and operation time affect the prognosis of IDA, Hunt-Hess grade was an independent risk factor for prognosis. Aneurysm size, longest diameter, basal length, and location at the base of the pica affect recurrence. Located in pica base by the dissecting aneurysm is an independent risk factor for recurrence.

Objective: We aimed to determine the predictive value of renal function status [estimating glomerular filtration rate (eGFR)] in conjunction with inflammatory biomarkers [white blood cell(WBC) and C-reactive protein (CRP)] for in-hospital outcomes in acute ischemic stroke (AIS) patients treated with intravenous thrombolysis (IVT).

Methods: We retrospectively screened a total of 409 AIS patients treated with IVT. The study participants were classified into two groups according to post-stroke pneumonia or functional outcome. They were divided into four groups according to the cut-offs of inflammatory biomarkers and eGFR by receiver operating characteristics(ROC) curves for two outcomes of post-stroke pneumonia and functional status: WBC↓/eGFR↑, WBC↓/eGFR↓, WBC↑/eGFR↑, and WBC↑/eGFR↓for post-stroke pneumonia; and CRP↓/eGFR↑, CRP↓/eGFR↓, CRP↑/eGFR↑, and CRP↑/eGFR↓for functional outcome. Logistic regression models were used to calculate the odds ratios (ORs) and 95% confidence intervals (CIs) of post-stroke pneumonia or at-discharge functional outcome, using the WBC↓/eGFR↑group or CRP↓/eGFR↑group as the reference. The Net Reclassification Index (NRI) and the Integrated Discrimination Improvement (IDI) were calculated to analyze the combined predictive value.

Results: Compared with patients in WBC↓/eGFR↑group, those in WBC↑/eGFR↑group had increased risk of post-stroke pneumonia (OR 5.15, 95% CI 1.67-15.87) and poor functional outcome (OR 5.95, 95% CI 2.25-15.74). Furthermore, patients in WBC↑/ eGFR↓group had the highest risk of clinical outcomes (all P value for trend < 0.001), the multivariable-adjusted ORs (95% CIs) were 7.04 (2.42-20.46) for post-stroke pneumonia and 8.64 (3.30-22.65) for poor functional outcome. The addition of WBC and eGFR to the basic model significantly improved risk prediction for post-stroke pneumonia (category-free NRI 69.0%, 95% CI 47.3%-90.7%; IDI 5.4%, 95% CI 2.6%-8.3%) and functional outcome (category-free NRI 59.4%, 95% CI 39.2%-79.9%; IDI 5.3%, 95% CI 2.9%-7.8%). Similarly, when we added CRP and eGFR to the basic model with conventional risk factors, the risk discrimination and prediction for post-stroke pneumonia and functional outcome was also significantly improved.

Conclusion: Combining renal function status and inflammatory biomarkers within 4.5 h after onset could better predict in-hospital outcomes of AIS patients with IVT.

Parkinson's disease (PD) is a neurodegenerative disease affecting millions of people around the world. Conventional PD detection algorithms are generally based on first and second-generation artificial neural network (ANN) models which consume high energy and have complex architecture. Considering these limitations, a time-varying synaptic efficacy function based leaky-integrate and fire neuron model, called SEFRON is used for the detection of PD. SEFRON explores the advantages of Spiking Neural Network (SNN) which is suitable for neuromorphic devices. To evaluate the performance of SEFRON, 2 publicly available standard datasets, namely (1) UCI: Oxford Parkinson's Disease Detection Dataset and (2) UCI: Parkinson Dataset with replicated acoustic features are used. The performance is compared with other well-known neural network models: Multilayer Perceptron Neural Network (MLP-NN), Radial Basis Function Neural Network (RBF-NN), Recurrent Neural Network (RNN) and Long short-term memory (LSTM). The experimental results demonstrate that the SEFRON classifier achieves a maximum accuracy of 100% and an average accuracy of 99.49% on dataset 1. For dataset 2, it attains a peak accuracy of 94% and an average accuracy of 91.94%, outperforming the other classifiers in both cases. From the performance, it is proved that the presented model can help to develop a robust automated PD detection device that can assist the physicians to diagnose the disease at its early stage.

Background: Stroke is the main cause of death and disability. Post-stroke cognitive impairment (PSCI) is one of the most severe complications of stroke, which lacks effective biomarkers for its early detection.

Objective: This study evaluated the significance of lncRNA SIX3OS1 in acute stroke and PSCI aiming to identify a novel biomarker.

Patients and methods: The study enrolled 138 patients with acute stroke and 80 healthy individuals. By comparing the serum SIX3OS1 in acute stroke and healthy individuals, the significance of SIX3OS1 in diagnosing acute stroke, assessing disease severity, and predicting the risk of PSCI was revealed.

Results: Significant upregulation of SIX3OS1 in acute stroke was observed, which discriminated patients with acute stroke from healthy individuals and indicated severe disease conditions of patients. There were 72 acute stroke patients who had PSCI accounting for 52.17% that showed a higher serum SIX3OS1 level than post-stroke cognitive normal patients. The increasing serum SIX3OS1 level was also identified as a risk factor for PSCI and could distinguish PSCI patients. Additionally, SIX3OS1 showed a negative correlation with the MoCA score of PSCI patients.

Conclusion: Serum SIX3OS1 level can be considered a biomarker for screening acute stroke and a predictor for PSCI.

Objective: To evaluate the efficacy of repetitive transcranial magnetic stimulation (rTMS) on cognitive function, depression, and walking ability in patients with Parkinson's disease.

Methods: A comprehensive search was conducted in PubMed, Web of Science, Embase, Cochrane Library, China National Knowledge Infrastructure (CNKI), Chinese Biomedical Literature Database (CBM), VIP Database, and Wanfang Database. Randomized controlled trials (RCTs) on rTMS treatment in Parkinson's disease patients were retrieved, covering the period from the inception of each database to July 2024. The quality of the included studies was assessed using the Cochrane risk of bias tool. Two researchers independently screened the literature, extracted data, and assessed the risk of bias in the studies. Data synthesis and analysis were performed using RevMan 5.4 and Stata 17.0 software.

Results: A total of 15 studies were included. The meta-analysis revealed that rTMS significantly improved the MOCA score (MD = 2.98, 95% CI 2.08, 3.88, P = 0.000), TUGT score (SMD=-0.72, 95% CI -1.43, 0.00, P = 0.048), FOG-Q score (SMD=-0.54, 95% CI -0.97, -0.11, P = 0.01), and UPDRS-III score (SMD=-0.66, 95% CI -0.84, -0.47, P = 0.000) in Parkinson's disease patients, and also alleviated depressive symptoms as measured by the HAMD (SMD=-0.43, 95% CI -0.72, -0.13, P = 0.004).

Conclusions: rTMS can improve cognitive function, depressive symptoms, and walking ability in patients with Parkinson's disease.

Background: Fatal familial insomnia (FFI) is a rare autosomal dominant inherited disease and a type of prion diseases. We report a case of fatal familial insomnia (FFI) in a 52-year-old man who was initially misdiagnosed as Alzheimer's disease.

Case presentation: The patient presented with persistent insomnia as the initial symptom, accompanied by cognitive impairment, autonomic dysfunction, and disorders of voluntary movement. Cerebrospinal fluid analysis revealed a decrease in Aβ_1-40 levels and an increase in total tau protein. Cranial imaging demonstrated bilateral hippocampal atrophy, while long-term video electroencephalography indicated focal abnormalities. The patient's prion protein gene was D178N/129MM type, confirmed the diagnosis of FFI.

Conclusions: The key characteristics of FFI include insomnia and rapidly progressive dementia, its differential diagnosis with AD has been extensively discussed in clinical practice. This is the first report of FFI concerning Aβ and tau protein, raises the awareness that the ratio of p-tau/t-tau in cerebrospinal fluid can provide valuable diagnostic clues for FFI.

Neuronal intranuclear inclusion disease (NIID) is a rare progressive neurodegenerative disease with a characteristic pathological feature of eosinophilic hyaluronan inclusions in the nervous system and internal organs. The identification of GGC-repeat expansions in the Notch 2 N-terminal like C (NOTCH2NLC) gene facilitates the accurate diagnosis of NIID. Due to its rareness and high clinical heterogeneity, the diagnosis of NIID is often delayed or missed. Here, we report a case of NIID mimicking autoimmune encephalitis. A 55-year-old Chinese man presented with fever, headache, recurrent seizures, and weakness in the upper and lower left limbs. Brain MRI revealed diffuse T2/ FLAIR-hyperintense lesions in the bilateral basal ganglia, corpus callosum, and periventricular white matter, with swelling of the right temporal, frontal, and parietal cortices accompanied by meningeal enhancement. Abnormally high signal lesions were observed in the corticomedullary junction in diffusion-weighted imaging (DWI). The infectious or autoimmune disease screening of central nervous system using CSF was normal. The test of GGC-repeat expansion in the NOTCH2NLC gene by capillary electrophoresis indicated GGC repeats (48 and 110 GGC repeats), which supported the diagnosis of NIID. After treatment with glucocorticoid, the clinical symptoms of this patient improved significantly. In the literature, 12 cases of NIID presenting with encephalitis-like attacks were identified, most of which were recurrent, accompanied by progressive symptoms such as dementia, Parkinsonism symptoms, migraine, or dysuria. In this case, there was a single encephalitis-like episode without other progressive symptoms. In patients with encephalitis-like symptoms, NIID should be considered, especially when no other evidence of infection is found, as demonstrated in this case. In addition, long-term monitoring of disease progression is also very important.

Background: Neuroimaging plays a vital role in the diagnosis of intracerebral hemorrhage (ICH) and in identifying the underlying etiology for appropriate therapeutic approach. This study aims to determine the significance and potential advantages of using early magnetic resonance imaging (MRI) as a diagnostic tool for ICH.

Methods: This retrospective study included 359 patients with ICH treated at the Department of Neurology, Mannheim University Hospital between January 2017 and December 2021. Patient characteristics, stroke severity and imaging procedures were descriptively analyzed. Factors associated with the choice of imaging modalities were evaluated. The etiology of hemorrhage was retrospectively analyzed using the existing data. We recorded the reassignment of ICH etiology by comparing the assessment after first sole review of CT scan and then subsequent MRI review. The overall rate of reassignments and the reassignments per CT-based initial etiology were analyzed.

Results: In the sample of 359 patients with ICH (mean age 73.1 years, 55.4% male), patients receiving an additional MRI were significantly younger (p < .001) and were less severely affected by stroke (median NIHSS score 5 vs. 15, p < .001). MRI was performed significantly less frequently in patients who died during hospitalization (11.7% vs. 63.9%, p < .001). MRI led to a reassignment of ICH etiology in 48.2% of cases (80/166), uncovering unknown underlying causes in 69% of cases (49/71). Reassignment occurred most frequently in patients with a CT-based diagnosis of hypertensive ICH (18/50). The most frequent reassigned etiologies after MR imaging were cerebral amyloid angiopathy (CAA; 36 patients) and secondary hemorrhage of an ischemic stroke (30 patients).

Conclusions: Early MR imaging in patients with ICH improves the determination of underlying etiology and the conception of an appropriate treatment approach, potentially contributing to better patient outcomes.

Background: ICU-acquired weakness (ICU-AW) is a common complication among ICU patients. We used machine learning techniques to construct an ICU-AW inflammatory factor prediction model to predict the risk of disease development and reduce the incidence of ICU-AW.

Methods: The least absolute shrinkage and selection operator (LASSO) technique was used to screen key variables related to ICU-AW. Eleven indicators, such as the presence of sepsis, glucocorticoids (GC), neuromuscular blocking agents (NBAs), length of ICU stay, Acute Physiology and Chronic Health Evaluation (APACHE II) II score, and the levels of albumin (ALB), lactate (LAC), glucose (GLU), interleukin-1β (IL-1β), interleukin-6 (IL-6), and interleukin-10 (IL-10), were used as variables to establish the prediction model. We divided the data into a dataset that included inflammatory factors and a dataset that excluded inflammatory factors. Specifically, 70% of the participants in both datasets were used as the training set, and 30% of the participants were used as the test set. Three machine learning methods, logistic regression (LR), random forest (RF), and extreme gradient boosting (XGB), were used in the 70% participant training set to construct six different models, which were validated and evaluated in the remaining 30% of the participants as the test set. The optimal model was visualized for prediction using nomograms.

Results: The logistic regression model including the inflammatory factors demonstrated excellent performance on the test set, with an area under the curve (AUC) of 82.1% and the best calibration curve fit, outperforming the other five models. The optimal model is represented visually in the nomograms.

Conclusion: This study used easily accessible clinical characteristics and laboratory data that can aid in early clinical recognition of ICU-AW. The inflammatory factors IL-1β, IL-6, and IL-10 have high value for predicting ICU-AW.

Trial registration: The trial was registered at the Chinese Clinical Trial Registry with the registration number ChiCTR2300077968.