The latest medical research on Neurology
The research magnet gathers the latest research from around the web, based on your specialty area. Below you will find a sample of some of the most recent articles from reputable medical journals about neurology gathered by our medical AI research bot.
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Request AccessSkull Density Ratio as Arm-Allocation Parameter for a Controlled Focused Ultrasound Trial in Parkinson's Disease.
"Movement Disorders Clinical PracticeMR-guided focused ultrasound (FUS) thermoablation is an established therapy for movement disorders. FUS candidates must meet a predefined threshold of skull density ratio (SDR), a parameter that accounts for the efficiency in reaching ablative temperatures. Randomized sham-controlled trials to provide definitive therapeutic evidence employ pure randomization of subjects into active treatment or control arms. The latter design has several general limitations.
To demonstrate that SDR values are not associated with clinically and demographically relevant variables in patients with Parkinson's disease (PD). This in turn would allow using SDR as an arm-allocation parameter, separating patients who will receive active FUS treatment and best medical management treatment (BMT).
We studied a cohort of 215 PD patients who were candidates for FUS subthalamotomy to determine if the SDR was correlated with demographic or clinical variables that could introduce bias for group allocation in a controlled trial.
SDR was unassociated with age, gender, and clinical motor features nor with levodopa daily dose in our cohort of PD patients. A negative association with age was found for the female subgroup.
Our results show that in a PD population considered for FUS subthalamotomy treatment, the SDR may be a valid group-allocation parameter. This could be considered as the basis for a controlled study comparing FUS subthalamotomy vs BMT.
Neurological manifestations of nontuberculous mycobacteria in adults: case series and review of the literature.
Frontiers NeurologyNontuberculous mycobacteria (NTM) mediated infections are important to consider in cases with neuroinflammatory presentations. We aimed to characterize cases of NTM with neurological manifestations at the National Institutes of Health (NIH) Clinical Center and review the relevant literature.
Between January 1995 and December 2020, six cases were identified. Records were reviewed for demographic, clinical, and radiological characteristics. A MEDLINE search found previously reported cases. Data were extracted, followed by statistical analysis to compare two groups [cases with slow-growing mycobacteria (SGM) vs. those with rapidly growing mycobacteria (RGM)] and evaluate for predictors of survival. NIH cases were evaluated for clinical and radiological characteristics. Cases from the literature were reviewed to determine the differences between SGM and RGM cases and to identify predictors of survival.
Six cases from NIH were identified (age 41 ± 13, 83% male). Five cases were caused by SGM [Mycobacterium avium complex (MAC) n = 4; Mycobacterium haemophilum n = 1] and one due to RGM (Mycobacterium abscessus). Underlying immune disorders were identified only in the SGM cases [genetic (n = 2), HIV (n = 1), sarcoidosis (n = 1), and anti-interferon-gamma antibodies (n = 1)]. All cases were diagnosed using tissue analysis. A literature review found 81 reports on 125 cases (SGM n = 85, RGM n = 38, non-identified n = 2). No immune disorder was reported in 26 cases (21%). Within SGM cases, the most common underlying disease was HIV infection (n = 55, 65%), and seizures and focal lesions were more common. In RGM cases, the most common underlying condition was neurosurgical intervention or implants (55%), and headaches and meningeal signs were common. Tissue-based diagnosis was used more for SGM than RGM (39% vs. 13%, p = 0.04). Survival rates were similar in both groups (48% SGM and 55% in RGM). Factors associated with better survival were a solitary CNS lesion (OR 5.9, p = 0.01) and a diagnosis made by CSF sampling only (OR 9.9, p = 0.04).
NTM infections cause diverse neurological manifestations, with some distinctions between SGM and RGM infections. Tissue sampling may be necessary to establish the diagnosis, and an effort should be made to identify an underlying immune disorder.
Rate of atrial fibrillation by Holter-Stroke Risk Analysis in undetermined TIA/rapidly improving stroke symptoms patients.
Frontiers NeurologyHolter-SRA (Stroke Risk Analysis) is an automated analysis of ECG monitoring for Atrial Fibrillation (AF) detection. The aim of this study was to evaluate the rate of AF in undetermined TIA/Rapidly improving stroke symptoms (RISS) patients.
Prospective study of undetermined TIA/RISS patients who presented to the emergency department. Early vascular studies (angio CT, transthoracic echocardiography and ECG) were performed in emergency department. The Holter-SRA device was placed for 2 h and the patients were classified into: confirmed AF, high risk of AF or low risk of AF. Prolonged ambulatory monitoring (7 days) was carried out every month for patients with a high-risk pattern. The results were evaluated until definitive detection of AF or low-risk pattern. The endpoints were rate of AF and vascular recurrence at 90 days.
Over a period of 24 months, 83 undetermined TIA/RISS patients were enrolled. The mean age was 70 ± 10 years and 61% were men. The median ABCD2 score was 4 points (1-7). After 2 h of monitoring in the emergency department, AF was detected in one patient (1.2%), 51 patients with a low-risk pattern and 31 patients (37.3%) showed a high-risk pattern of AF. During the ambulatory monitoring, of the 31 patients high risk pattern patients, AF was diagnosed to 17 cases and of the 51 patients with a low-risk pattern, one case experienced a recurrent vascular due to undetected AF (1.9% false negative). Three patients (3.6%) suffered a vascular recurrence within the first 90 days, before AF diagnosis.
In our study, AF was detected in 22.9% of the 83 patients with indeterminate TIA/RISS. Holter-SRA has allowed us to increase the detection of AF, especially those patients with a high-risk pattern in the first 3 months.
Hemispheric asymmetries in hippocampal volume related to memory in left and right temporal variants of frontotemporal degeneration.
Frontiers NeurologyIn addition to Alzheimer's disease (AD), the hippocampus is now known to be affected in variants of frontotemporal degeneration (FTD). In semantic ...
An exploration on the machine-learning-based stroke prediction model.
Frontiers NeurologyWith the rapid development of artificial intelligence technology, machine learning algorithms have been widely applied at various stages of stroke diagnosis, treatment, and prognosis, demonstrating significant potential. A correlation between stroke and cytokine levels in the human body has recently been reported. Our study aimed to establish machine-learning models based on cytokine features to enhance the decision-making capabilities of clinical physicians.
This study recruited 2346 stroke patients and 2128 healthy control subjects from Chongqing University Central Hospital. A predictive model was established through clinical experiments and collection of clinical laboratory tests and demographic variables at admission. Three classification algorithms, namely Random Forest, Gradient Boosting, and Support Vector Machine, were employed. The models were evaluated using methods such as ROC curves, AUC values, and calibration curves.
Through univariate feature selection, we selected 14 features and constructed three machine-learning models: Support Vector Machine (SVM), Random Forest (RF), and Gradient Boosting Machine (GBM). Our results indicated that in the training set, the RF model outperformed the GBM and SVM models in terms of both the AUC value and sensitivity. We ranked the features using the RF algorithm, and the results showed that IL-6, IL-5, IL-10, and IL-2 had high importance scores and ranked at the top. In the test set, the stroke model demonstrated a good generalization ability, as evidenced by the ROC curve, confusion matrix, and calibration curve, confirming its reliability as a predictive model for stroke.
We focused on utilizing cytokines as features to establish stroke prediction models. Analyses of the ROC curve, confusion matrix, and calibration curve of the test set demonstrated that our models exhibited a strong generalization ability, which could be applied in stroke prediction.
Safety considerations in the treatment with anti-CGRP(R) monoclonal antibodies in patients with migraine.
Frontiers NeurologyAnti-CGRP-(receptor-)monoclonal antibodies (anti-CGRP(R)-mAbs) represent a novel class of drugs for migraine treatment, but their long-term cerebrovascular and cardiovascular (CV) safety warrants further examination.
In this observational cohort study we assessed the CV safety for erenumab and fremanezumab in a real-world setting during a follow-up period of at least 1 year. Patients with hypertension or CV history were excluded. We conducted ECGs and collected clinical data at treatment initiation and thereafter every 3 months, including liver and kidney function, lipid-, electrolyte-and glucose levels.
Among patients receiving erenumab (n = 101) or fremanezumab (n = 92), 3.1% (6/193) developed abnormal ECGs or CV adverse events. Of these, three (1.6%) experienced moderate to severe CV adverse events (cerebellar stroke, spontaneous coronary artery dissection, and pericarditis) and discontinued treatment. The remaining three (1.6%) developed non-threatening ECG abnormalities without physical complaints. No significant changes were observed in liver and kidney function, lipid-, electrolyte-, or glucose levels.
We observed CV events in 1.6% of patients with 1.5-year follow-up of anti-CGRP(R)-mAbs treatment. We advise awareness regarding CV events in patients with migraine undergoing CGRP-targeted treatment, not as a confirmation of increased risk but as a proactive measure to address potential multifactorial influences.
Causal effects of immune cells in glioblastoma: a Bayesian Mendelian Randomization study.
Frontiers NeurologyGlioblastoma (GBM) is a highly malignant brain tumor, and immune cells play a crucial role in its initiation and progression. The immune system's cellular components, including various types of lymphocytes, macrophages, and dendritic cells, among others, engage in intricate interactions with GBM. However, the precise nature of these interactions remains to be conclusively determined.
In this study, a comprehensive two-sample Mendelian Randomization (MR) analysis was conducted to elucidate the causal relationship between immune cell features and the incidence of GBM. Utilizing publicly available genetic data, we investigated the causal associations between 731 immune cell signatures and the risk of GBM. Subsequently, we conducted a reverse Mendelian randomization analysis to rule out reverse causation. Finally, it was concluded that there is a unidirectional causal relationship between three subtypes of immune cells and GBM. Comprehensive sensitivity analyses were employed to validate the results robustness, heterogeneity, and presence of horizontal pleiotropy. To enhance the accuracy of our results, we concurrently subjected them to Bayesian analysis.
After conducting MR analyses, we identified 10 immune phenotypes that counteract glioblastoma, with the most protective being FSC-A on Natural Killer T cells (OR = 0.688, CI = 0.515-0.918, P = 0.011). Additionally, we found 11 immune cell subtypes that promote GBM incidence, including CD62L- HLA DR++ monocyte % monocyte (OR = 1.522, CI = 1.004-2.307, P = 0.048), CD4+CD8+ T cell % leukocyte (OR = 1.387, CI = 1.031-1.866, P = 0.031). Following the implementation of reverse MR analysis, where glioblastoma served as the exposure variable and the outcomes included 21 target immune cell subtypes, we discerned that only three cell subtypes (CD45 on CD33+ HLA DR+ CD14dim, CD33+ HLA DR+ Absolute Count, and IgD+ CD24+ B cell Absolute Count) exhibited a unidirectional causal association with glioblastoma.
Our study has genetically demonstrated the close relationship between immune cells and GBM, guiding future clinical research.
The incidence of brain metastases in breast cancer according to molecular subtype and stage: a 10-year single institution analysis.
Journal of Neuro-OncologyBreast cancer (BC) is the second most common etiology of brain metastases (BrM). We aimed to examine the incidence of BrM among all BC patients presenting to a large tertiary cancer centre over one decade.
We included all BC patients presenting consecutively between 2009 and 2019 and cross referenced that cohort to a radiotherapy database, identifying patients treated for BrM at any time following their initial presentation. Cumulative incidences (CI) of BrM diagnoses were calculated using death as a competing risk and compared using the Fine-Gray method. Overall survival was estimated using the Kaplan Meier method.
We identified 12,995 unique patients. The CI of BrM in patients who initially presented with Stage 0-4 disease was 2.1%, 3.7%, 9.4%, 10.6%, and 28.7%, respectively at 10 years. For 8,951 patients with available molecular subtype data, 6,470 (72%), 961 (11%), 1,023 (11%), and 497 (6%) had hormone-receptor (HR)-positive/ERBB2-, HR-negative/ERBB2-, HR-positive/ERBB2 + , and HR-negative/ERBB2 + disease, respectively; the CI of BrM in each was 7.6%, 25.3%, 24.1%, and 26.6%, at 10 years following BC diagnosis, respectively. Median overall survival (OS) following BC diagnosis and BrM diagnosis was 28 years 95% CI [25, 32] and 10 months 95% CI [9, 12], respectively.
From a large, registry-based study, we observed that patients with ERBB2 + and triple negative BC have the highest incidence of BrM. Our data supports prospective surveillance brain MRI studies. Given advancements in BrM treatment, clinicians should have a low threshold for brain imaging in BC patients with high risk subtypes.
PaCO2 Association with Outcomes of Patients with Traumatic Brain Injury at High Altitude: A Prospective Single-Center Cohort Study.
Neurocritical CarePartial pressure of carbon dioxide (PaCO2) is generally known to influence outcome in patients with traumatic brain injury (TBI) at normal altitudes. Less is known about specific relationships of PaCO2 levels and clinical outcomes at high altitudes.
This is a prospective single-center cohort of consecutive patients with TBI admitted to a trauma center located at 2600 m above sea level. An unfavorable outcome was defined as a Glasgow Outcome Scale-Extended (GOSE) score < 4 at the 6-month follow-up.
We had a total of 81 patients with complete data, 80% (65/81) were men, and the median (interquartile range) age was 36 (25-50) years. Median Glasgow Coma Scale (GCS) score on admission was 9 (6-14); 49% (40/81) of patients had severe TBI (GCS 3-8), 32% (26/81) had moderate TBI (GCS 12-9), and 18% (15/81) had mild TBI (GCS 13-15). The median (interquartile range) Abbreviated Injury Score of the head (AISh) was 3 (2-4). The frequency of an unfavorable outcome (GOSE < 4) was 30% (25/81), the median GOSE was 4 (2-5), and the median 6-month mortality rate was 24% (20/81). Comparison between patients with favorable and unfavorable outcomes revealed that those with unfavorable outcome were older, (median age 49 [30-72] vs. 29 [22-41] years, P < 0.01), had lower admission GCS scores (6 [4-8] vs. 13 [8-15], P < 0.01), had higher AISh scores (4 [4-4] vs. 3 [2-4], P < 0.01), had higher Acute Physiology and Chronic Health disease Classification System II scores (17 [15-23] vs. 10 [6-14], P < 0.01), had higher Charlson scores (0 [0-2] vs. 0 [0-0], P < 0.01), and had higher PaCO2 levels (mean 35 ± 8 vs. 32 ± 6 mm Hg, P < 0.01). In a multivariate analysis, age (odds ratio [OR] 1.14, 95% confidence interval [CI] 1.1-1.30, P < 0.01), AISh (OR 4.7, 95% CI 1.55-21.0, P < 0.05), and PaCO2 levels (OR 1.23, 95% CI 1.10-1.53, P < 0.05) were significantly associated with the unfavorable outcomes. When applying the same analysis to the subgroup on mechanical ventilation, AISh (OR 5.4, 95% CI 1.61-28.5, P = 0.017) and PaCO2 levels (OR 1.36, 95% CI 1.13-1.78, P = 0.015) remained significantly associated with the unfavorable outcome.
Higher PaCO2 levels are associated with an unfavorable outcome in ventilated patients with TBI. These results underscore the importance of PaCO2 levels in patients with TBI and whether it should be adjusted for populations living at higher altitudes.
Mitigation of TDP-43 toxic phenotype by an RGNEF fragment in amyotrophic lateral sclerosis models.
BrainAggregation of the RNA-binding protein TAR DNA binding protein (TDP-43) is a hallmark of TDP-proteinopathies including amyotrophic lateral sclerosi...
Low-intensity ultrasound ameliorates brain organoid integration and rescues microcephaly deficits.
BrainHuman brain organoids represent a remarkable platform for modeling neurological disorders and a promising brain repair approach. However, the effec...
Familial aggregation of seizure outcomes in four familial epilepsy cohorts.
EpilepsiaTo assess the possible effects of genetics on seizure outcome by estimating the familial aggregation of three outcome measures: seizure remission, history of ≥4 tonic-clonic seizures, and seizure control for individuals taking antiseizure medication.
We analyzed families containing multiple persons with epilepsy in four previously collected retrospective cohorts. Seizure remission was defined as being 5 and 10 years seizure-free at last observation. Total number of tonic-clonic seizures was dichotomized at <4 and ≥4 seizures. Seizure control in patients taking antiseizure medication was defined as no seizures for 1, 2, and 3 years. We used Bayesian generalized linear mixed-effects model (GLMM) to estimate the intraclass correlation coefficient (ICC) of the family-specific random effect, controlling for epilepsy type, age at epilepsy onset, and age at last data collection as fixed effects. We analyzed each cohort separately and performed meta-analysis using GLMMs.
The combined cohorts included 3644 individuals with epilepsy from 1463 families. A history of ≥4 tonic-clonic seizures showed strong familial aggregation in three separate cohorts and meta-analysis (ICC .28, 95% confidence interval [CI] .21-.35, Bayes factor 8 × 1016). Meta-analyses did not reveal significant familial aggregation of seizure remission (ICC .08, 95% CI .01-.17, Bayes factor 1.46) or seizure control for individuals taking antiseizure medication (ICC .13, 95% CI 0-.35, Bayes factor 0.94), with heterogeneity among cohorts.
A history of ≥4 tonic-clonic seizures aggregated strongly in families, suggesting a genetic influence, whereas seizure remission and seizure control for individuals taking antiseizure medications did not aggregate consistently in families. Different seizure outcomes may have different underlying biology and risk factors. These findings should inform the future molecular genetic studies of seizure outcomes.
