Frontiers in Molecular Neuroscience

Background: Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease characterized by death of upper and lower motor neurons, usually presented with clinical heterogeneity. Fluid biomarker development remains dominated by neurofilament light chain (NEFL), a marker of neuroaxonal injury. NEFL is however unspecific to ALS and its phenotypes and there is currently a lack of biomarkers that capture ALS heterogeneity such as onset site and ALS-frontotemporal spectrum disorder (ALS-FTSD). Therefore, we investigated whether plasma proteomics could reveal pathway-level signatures that stratify and explain ALS heterogeneity. Methods: We profiled ~5,400 plasma proteins (Olink Explore HT) in 299 patients with ALS and 50 age- and sex comparable healthy controls. We used two complementary analytic frameworks: (i) differential protein abundance analysis to identify altered proteins in ALS and across clinical subgroups, and (ii) weighted gene correlation network analysis (WGCNA) to identify coordinated protein modules and relate them to ALS diagnosis and to ALS-specific clinical traits (site of onset, ALS-FTSD, ALS functional rating scale-revised (ALSFRS-R) score, and plasma NEFL). Results: Differential abundance analysis identified 56 proteins altered in ALS versus controls, of which 40 were increased. WGCNA identified 11 co-expression modules, with ALS samples having the strongest correlation to a protein module (n=51) highly enriched for muscle-related proteins. Out of the 40 proteins that had increased expression levels, 29 overlapped with the muscle-enriched protein module, indicating that muscle related proteins are the dominant circulating proteomic signature in ALS. This signal extended to clinical stratification: spinal-onset patients showed a strong positive association with the muscle-module. Further, differential abundance analysis of spinal- versus bulbar-onset ALS identified changes that mapped predominantly to the same module, supporting a molecular signature of onset phenotype. In contrast, cognitive status (ALS-FTSD) mapped to distinct modules enriched for extracellular matrix/cell-adhesion pathways, consistent with a separable biological axis of disease heterogeneity. Although multiple modules correlated with NEFL, trait-specific signatures were not fully explained by neuroaxonal injury. Notably, the muscle-enriched module increased with higher NEFL and lower ALSFRS-R, supporting its interpretation as a severity-linked, muscle-involvement proxy. Conclusions: Large-scale plasma proteomics reveals that heterogeneity in ALS reflects underlying biological structures. We identified a dominant muscle-associated protein network that distinguished ALS patients from controls and correlated with disease onset phenotype and severity, alongside distinct protein networks linked to ALS-FTSD. By integrating differential protein abundance with network-based analysis, we defined pathway-level biomarker signatures that extend beyond NEFL, enabling biologically informed patient stratification and improved therapeutic monitoring.

Motor speech disorders (MSDs) are early markers of neurological disease, but expert perceptual analysis is rarely available outside specialized centers. Automated speech analysis offers a scalable alternative, yet prior studies have not systematically compared modeling approaches or assessed clinically relevant metrics in independent datasets. This study compared static acoustic features, articulatory informed Phonet features, and self-supervised pretrained models for binary and multi label MSD classification. We trained and evaluated models on 583 speech samples using speaker level splits. Baseline models included logistic regression and Gated Recurrent Units (GRUs) trained on eGeMAPS and MFCCs. We extracted three types of Phonet derived features and evaluated pretrained HuBERT and SSAST models in frozen, partially fine-tuned, and fully fine-tuned configurations. Binary classification distinguished MSDs from controls, while multi label classification identified six MSD subtypes. Models were assessed using validation AUC, and cut points were tested on two independent datasets. Pretrained and Phonet based models substantially outperformed static acoustic features. In binary classification, HuBERT achieved the highest AUC (0.95), while compact Phonet derived GRUs achieved comparable performance (up to 0.94). These models generalized well to independent datasets, maintaining high sensitivity (0.94) and specificity (0.97). In multi label classification, Phonet models achieved the highest macro average AUC (0.86), but threshold-based subtype performance declined on unseen data. Automated MSD detection is feasible and clinically promising. Binary classification generalized well, whereas multi label classification showed limited threshold stability across datasets.

Dementia is a progressive condition that impairs cognitive processes such as memory, decision making, and the ability to manage daily activities. Recent estimates suggest that more than half of all dementia cases could be preventable by addressing their risk factors, including disease comorbidities such as diabetes and vision loss. Yet, we lack a comprehensive molecular map of dementia comorbidities. In this work, we analyzed Austrian nationwide hospital claims data, comprising 13 million hospital stays from 2015 to 2019, to systematically assess dementia-related risk across disease comorbidity patterns, covering both their molecular relationships and their epidemiological overrepresentation. We identified disease trajectories occurring before and at the time of dementia diagnosis, revealing both sex-specific and shared comorbidity patterns. Overall, we identified 51 potential risk factors, with a prominent contribution from endocrine and metabolic disorders. While Parkinson's disease emerged as a strong molecularly related driver of dementia, we also identified emerging and previously under chracterized risk factors, including vitamin D deficiency. This integrative framework provides a comprehensive view of dementia associated disease networks and identifies novel, potentially modifiable risk factors. These results offer new opportunities for targeted prevention strategies and advance our understanding of the complex interplay between comorbidities and dementia development.

Importance: Neuroinflammation is a key component of the response to injury after concussion, but direct links between diffusion MRI metrics and specific plasma inflammatory pathways in human concussion have not been established. Objective: To examine associations between diffusion MRI metrics and pathway-level inflammatory proteomic signatures in adolescents during the subacute period after concussion. Design, Setting, and Participants: Cross-sectional analysis of data from the CARE4Kids Consortium, a six-site prospective study. Participants were English-speaking adolescents ages 11-17.99 with concussion and symptoms at 7-35 days post-injury. Data were collected between 2022-2024. Of 370 enrolled participants, 122 had both diffusion MRI and plasma proteomics available for analysis. Exposure: Advanced diffusion MRI metrics were converted to z-scores and participants were grouped by the spatial extent of outlier values (potholes and peaks) across 15 white matter regions of interest. Nine non-redundant groupings were selected for primary analysis. Main Outcomes and Measures: Pathway-level inflammatory profiles derived from gene set enrichment analysis (GSEA) of ~5,400 plasma proteins measured by Olink proximity extension assay, targeting nine hallmark inflammatory pathways spanning initiation through resolution. Persistent symptoms were assessed 64-115 days post-injury. Results: Diffusion metrics reflecting tissue disorganization were associated with upregulation of the coagulation pathway, consistent with hemostatic-inflammatory signaling. Metrics reflecting reduced tissue complexity and neurite density were associated with upregulation of interferon- and interferon-{gamma} response pathways, consistent with microstructural remodeling driven by cellular immune activation. Elevated free water content was associated with downregulation of most inflammatory pathways and trend-level transforming growth factor - {beta} upregulation, reflecting inflammatory resolution. Time since injury did not differ between groups based on free water (Kolmogorov-Smirnov p = 0.97), suggesting these differences reflect individual variability in recovery pace. Exploratory analyses showed a trend toward lower odds of persistent symptoms in the group with elevated free water content (odds ratio = 0.51, p = 0.18). Conclusions and Relevance: Multiple diffusion MRI metrics are differentially sensitive to distinct neuroinflammatory states in the subacute period after adolescent concussion. These findings suggest that diffusion imaging could serve as a non-invasive tool for inflammatory phenotyping, with potential implications for identifying patients who may benefit from targeted immunomodulatory intervention.

This study examined the extent to which goodness of pronunciation (GoP) scores and phonological posterior probabilities capture perceptual ratings of speech severity in individuals with motor speech disorders (MSD). Speech recordings of the word catastrophe were obtained from 489 participants, including 333 neurologically typical controls and 156 individuals with MSD. GoP scores were derived using traditional acoustic features and self-supervised speech representations, including WavLM and XLS-R, across multiple modeling approaches, while phonological posterior probabilities were extracted using Phonet. Model performance was evaluated using Kendall's rank correlations, regression, and receiver operating characteristic analyses against speech-language pathologists' perceptual ratings of sound distortion and intelligibility. Both GoP and phonological posterior probabilities were significantly associated with perceptual ratings. Self-supervised speech representations substantially outperformed traditional acoustic features, with WavLM-based GoP using k-nearest neighbors achieving the strongest performance. Across correlation, regression, and classification analyses, GoP consistently outperformed phonological posterior probabilities for both sound distortion and intelligibility. Age and gender had minimal influence on model-derived measures or their relationships with perceptual ratings. These findings demonstrate the value of self-supervised GoP as an objective measure of speech impairment while highlighting the complementary role of phonological posterior probabilities in characterizing articulatory aspects of motor speech disorders.

Objective: To compare first-line emergency department (ED) treatment classes for acute headache on short-term all-cause ED return and index admission across two independent health systems. Background: ED trials of acute headache treatment are judged on in-ED pain relief, a documented endpoint that is recorded incompletely and shifts with the scoring rule, and is a weak surrogate for what happens after discharge. All-cause ED return after an index headache visit (any subsequent ED encounter within the window) has not been used to compare first-line treatments at scale, and society guidance favors dopamine-receptor antagonists while recommending against routine opioids. Methods: Retrospective two-center cohort of adults treated for headache in the ED, using MIMIC-IV-ED (Beth Israel Deaconess Medical Center, 2011-2019) and MC-MED (Stanford, 2020-2022). The first-line class was the earliest qualifying acute agent. The primary contrast was opioids versus dopamine-receptor antagonists (the guideline-preferred class). Outcomes were 72-hour and 7-day all-cause ED return (among discharged patients; any subsequent ED encounter within the window) and index hospital admission. Confounding by indication was addressed with propensity overlap weighting; associations are reported as adjusted risk ratios (RRs) with bootstrap 95% CIs and E-values. Estimates were pooled with a site term and examined per site. Results: Among 13,285 treated adults (10,799 MIMIC-IV-ED; 2,486 MC-MED), opioid recipients were older and higher-acuity than dopamine-antagonist recipients (index admission 38.1% vs 16.4%). In the MIMIC-IV-ED discharged primary-contrast population, overlap weighting reduced the maximum standardized mean difference from 0.35 to 0.002; pooled and site-specific balance diagnostics are provided in the Supplement. First-line opioids remained associated with a higher 72-hour all-cause ED return (6.8% vs 3.8%; adjusted RR 1.79; 95% CI 1.31 to 2.33), 7-day return (10.7% vs 6.6%; RR 1.62; 95% CI 1.28 to 1.98), and index admission (RR 2.32; 95% CI 2.11 to 2.58, consistent with strong residual severity differences in patients selected for opioids). The direction of association was concordant across both health systems, although MC-MED return estimates were imprecise given the smaller opioid-treated discharged sample. In MIMIC-IV-ED, the cumulative all-cause return incidence by treatment class separated by day 3 and persisted through 30 days. The direction was consistent, though attenuated and no longer statistically significant, when the outcome was restricted to a headache-specific return (72-hour RR 1.31; 95% CI 0.91 to 1.88); the direction persisted for the composite of admission or 72-hour return, which does not condition on discharge but is influenced by the more confounded admission component (RR 2.16; 95% CI 1.98 to 2.39). Conclusion: Across two health systems, first-line opioid treatment for ED headache was associated with higher all-cause short-term ED return among discharged patients and higher index admission than dopamine antagonists. These observational associations reflect downstream all-cause ED utilization after an index headache visit rather than confirmed headache recurrence or treatment failure; they are consistent with guideline-concordant, opioid-sparing first-line treatment and warrant prospective confirmation. Plain Language Summary: Emergency departments treat headaches with several different medicines, but the usual way of judging which works, the pain score recorded during the visit, is often missing or inconsistent. Using two large hospital systems and a clearer outcome, whether patients came back to the emergency department for any reason, we found that patients first treated with opioids returned within 72 hours about 1.8 times as often as those given the guideline-preferred dopamine-blocking medicines and were admitted more than twice as often. These patterns pointed the same direction in both hospital systems after adjustment for the measured differences available in both databases. Because this was an observational comparison and returns were counted for any reason, the findings are consistent with using guideline-preferred non-opioid medicines first, rather than proof that opioids worsen headache.

Background: Post-stroke dysphagia (PSD) contributes to aspiration, pneumonia, malnutrition, prolonged hospitalization and mortality. We evaluated the discrimination, validity and readiness of machine learning and data-driven prediction models for PSD-related outcomes. Methods: Following a prospectively registered protocol (PROSPERO CRD420261419259), we searched PubMed/MEDLINE, Embase, Web of Science Core Collection, CINAHL and CENTRAL from inception through June 7, 2026. Eligible studies developed or validated multivariable prediction models for PSD-related outcomes in adults with stroke. We used PROBAST and PROBAST+AI to assess risk of bias and applicability and TRIPOD+AI to evaluate reporting. Area under the curve (AUC) estimates were pooled on the logit scale with random-effects models. Results: Twenty-four studies were included and ten contributed to meta-analysis. Four studies predicting early or incident PSD yielded a pooled AUC of 0.94 (95% CI 0.60-0.99; I2 = 95.6%). Pooled AUCs were 0.84 (95% CI 0.71-0.92) for aspiration or penetration-aspiration and 0.89 (95% CI 0.24-1.00) for severe dysphagia. The exploratory analysis of all ten risk-prediction models produced an AUC of 0.90 (95% CI 0.80-0.95), but heterogeneity was substantial (I2 = 90.3%) and the prediction interval was 0.51-0.99. Every study had high risk of bias because of analysis-domain concerns; calibration and external validation were uncommon. Conclusions: Reported discrimination was often high, but the evidence does not establish reliable performance in care. Independent validation, calibration, complete model reporting and clinical-impact studies are needed before these models guide post-stroke swallowing care. Keywords: Post-stroke dysphagia; Stroke; Deglutition disorders; Machine learning; Clinical prediction model; Area under the curve; Meta-analysis

ABSTRACT Objective Delayed cerebral infarction (DCIn) is a severe complication following aneurysmal subarachnoid hemorrhage (aSAH). Previous studies suggest that glycemic variability is associated with DCIn. However, whether diabetes status modifies the relationship between glycemic traits and DCIn remains unknown. Methods Clinical data were collected from aSAH patients admitted to the First Affiliated Hospital of Shantou University Medical College between January 2015 and April 2025. The collected data included demographic characteristics, clinical variables, and glycemic traits. Glycemic traits included mean blood glucose (GLU-M), standard deviation of blood glucose (GLU-SD), coefficient of variation of blood glucose (GLU-CV), variance of blood glucose (GLU-Var), range of blood glucose (GLU-R), average real variability of blood glucose (GLU-ARV), and variability independent of the mean (GLU-VIM). After 1:2 case-control matching, conditional logistic regression models were used to evaluate the associations between glycemic traits and DCIn risk, with stratified analyses performed according to diabetes status. Multiplicative interaction terms were additionally included to assess the potential modifying effect of diabetes status. Results A total of 306 patients with aSAH were included. Among them, 102 developed DCIn cases. For each of these 102 cases, two controls were matched by age ({+/-}5 years), sex and year of admission ({+/-}5 years). In the overall population, higher GLU-M and GLU-ARV were associated with increased DCIn risk, with odds ratios (ORs) per 1-SD increase of 1.62 (95% CI, 1.25-2.11) and 1.63 (95% CI, 1.25-2.11), respectively. Among patients without diabetes (n=266), the associations with DCIn per 1-SD were observed for GLU-M (OR, 2.23; 95% CI, 1.56-3.19), GLU-SD (OR, 1.53; 95% CI, 1.13-2.06), GLU-Var (OR, 1.48; 95% CI, 1.04-2.10), and GLU-ARV (OR, 1.88; 95% CI, 1.38-2.55). No significant associations were observed among patients with diabetes. Significant interactions were observed between diabetes status and GLU-SD and GLU-Var, with P for interaction values of 0.033 and 0.032, respectively. Conclusion Higher mean blood glucose and greater glycemic variability are associated with an increased risk of DCIn in aSAH patients, especially in those without diabetes.

Background Functional neurological disorder (FND), one of the most common neurological conditions, affects women almost twice as frequently as men. The reasons for this are unknown, and there has been minimal research into how physiological and pathological features of women's health interact with symptoms of FND. Methods We conducted an online survey assessing the effect of several aspects of women's health with the severity of symptoms of FND. Results 484 people completed the survey. Among the 223 who had regular or fairly regular menstrual cycles, a strong difference across the menstrual cycle was seen, with symptoms at their best in the follicular phase, worsening in the luteal phase, and worst in the pre-menstrual period and the menses. This effect was not moderated by a proxy measure of pre-menstrual dysphoric disorder (PMDD). Participants who were taking the combined oral contraceptive (COC, n=43) and progesterone-based contraception (n=80) were more likely to report symptom improvement from starting the medication than worsening. When compared to menstruating participants who were not taking the COC, participants taking the COC reported less worsening in their symptoms of FND in the luteal, pre-menstrual, and menstrual phases. Of the 99 women who had passed menopause since developing FND, 76% reported worsening of their FND symptoms after menopause. Discussion This study demonstrates interactions between several aspects of women's health and symptoms of FND. The observed pattern of symptom fluctuation across hormonal states suggests a potential modulatory role of oestrogen, warranting further targeted investigation.

Background: aneurysmal subarachnoid hemorrhage (aSAH) is neurological emergency associated with substantial mortality and disability. Current grading systems such as the modified Fisher Scale (mFS) and World Federation of Neurological Societies (WFNS) score, rely on semiquantitative and examination based assessments. Hence, they demonstrate limited predictive precision. The enhanced subarachnoid hemorrhage (eSAH) score is a simplified quantitative model integrating age, Glasgow Coma Scale (GCS), and cisternal subarachnoid hemorrhage volume (SAHV) to predict clinical outcomes after aSAH. Methods: We performed a retrospective multicenter cohort study that included 1088 patients across three tertiary-care centers the United States. Predictive performance for unfavorable functional outcome, in-hospital mortality and delayed cerebral ischemia (DCI) was evaluated using receiver operating characteristic (ROC) analysis and area under the curve (AUC). Comparative analyses were performed and compared to the WFNS and mFS grading systems. Results: the eSAH score demonstrated excellent discrimination for unfavorable functional outcome at discharge ( AUC 0.89 ) and in-hospital mortality (AUC 0.87). The DCI subscore demonstrated good discriminatory performance for predicting DCI (AUC 0.77). Compared with conventional grading systems, this was superior to both the WFNS (AUC 0.75) and the mFS ( AUC 0.70). increasing eSAH scores were additionally associated with progressively higher rates of mortality and unfavorable functional outcomes. Conclusion: the eSAH score demonstrates strong external validity, reproducibility and superior predictive performance compared with conventional grading systems in a large multicenter cohort. These findings support the clinical utility of quantitative hemorrhage burden integration for early risk stratification in patients with aSAH.

Objective: Shunt-dependent hydrocephalus is a common and costly complication of aneurysmal subarachnoid hemorrhage (aSAH), affecting up to 28% of survivors. Existing prediction tools, including the Chronic Hydrocephalus Ensuing from SAH Score (CHESS), have limited discriminative accuracy. We developed the CHECKMATE score, a clinically practical tool to improve prediction of ventriculoperitoneal shunt dependency after aSAH. Methods: In this multicenter retrospective cohort of 486 patients with aSAH from Mayo Clinic (January 1, 2006-December 31, 2021), we used multivariable logistic regression and machine learning to identify independent predictors of ventriculoperitoneal shunt placement. The CHECKMATE score was derived from 5 weighted variables: symptomatic hydrocephalus (10 points), intraventricular hemorrhage (5 points), SAH volume greater than 10 mL (3 points), neutrophil-to-lymphocyte ratio greater than 12 (2 points), and 10-year incremental age thresholds starting at older than 60 years (1 point each). Results: Of 486 patients (mean age, 56.3 years; 64.6% female), 137 (28.2%) required ventriculoperitoneal shunt placement. The CHECKMATE score achieved an area under the curve of 0.808 (compared to 0.737 for CHESS), with a sensitivity of 0.85, specificity of 0.67, and negative predictive value of 0.92 at the optimal cutoff of 14 points. Conclusions: The CHECKMATE score outperforms CHESS for predicting ventriculoperitoneal shunt dependency after aSAH and is easily used at the bedside. Its high negative predictive value helps identify low-risk patients who may benefit from earlier external ventricular drain weaning and shorter hospital stays.

The aim of this work is to validate patient-specific EEG baseline establishment using the e-norms method as a screening and retrospective-review tool for seizure detection in pediatric epilepsy. The method was applied to 247 seizure-free EEG recordings (263.92 hours) from 10 patients in the CHB-MIT Scalp EEG Database (ages 3-18). A composite stability metric combining first-derivative dynamics, spectral entropy, variance, and line length was computed per 2-second epoch across 23 channels. Patient-specific detection thresholds were derived from each patient's seizure-free baseline using a weighted statistical procedure. Performance was validated against 72 expert-annotated seizures (2,705 epochs) across 62 seizure files, with durations spanning 6 to 264 seconds (44-fold range). The results show that detection achieved 94.4% event-level sensitivity (68 of 72 seizures; 95% CI 86.6-97.8%) and 81.5% epoch-level sensitivity (2,204 of 2,705 epochs; 95% CI 80.0-82.9%). Eight of ten patients achieved 100% event-level sensitivity with epoch-level sensitivity ranging from 58.7% to 100.0%. Two patients showed partial event-level failures (CHB-15: 17 of 20; CHB-18: 5 of 6), with the four missed events attributable to two characterizable failure modes. Patient-specific thresholds ranged from 4.06 to 4.81 (mean 4.51 +/- 0.25); threshold variation did not correlate reliably with age or sex, confirming that no universal threshold could achieve comparable performance. Detection margins ranged from 0.88 to 1.24 times. Patient-specific e-norms achieves 94.4% event-level sensitivity for pediatric EEG seizure detection without requiring labeled seizure training data, exceeding published human expert inter-rater agreement (50-76%) and recent automated approaches in adult cohorts using behind-the-ear EEG and wearable ECG. Two characterizable failure modes account for the four missed events and inform appropriate clinical use. As a high-sensitivity screening tool complementary to real-time alarm systems, the method is ready for adult validation, prospective deployment, and head-to-head benchmarking.

Aphasia diagnosis in Indonesia remains challenging due to limited culturally and linguistically appropriate instruments. Widely used tools such as the Boston Diagnostic Aphasia Examination (BDAE) and Western Aphasia Battery (WAB) are not adapted to the Indonesian context, while Tes Afasia untuk Diagnosis, Informasi, dan Rehabilitasi (TADIR) provides screening but lacks diagnostic accuracy. To address this gap, we developed the Instrumen Diagnosis dan Evaluasi Afasia (IDEA) for native Indonesian speakers and evaluated its validity, reliability, and normative cutoff values in cognitively healthy Indonesian adults. Eighty-three cognitively normal adults (screened using MoCA-Ina) with no history of neurological disease were assessed using IDEA, which evaluates six language domains. Items were adapted from existing tools and reviewed by experts. Content validity, internal consistency (Cronbachs alpha), and construct validity (Exploratory Factor Analysis) were analyzed using SPSS v25. A total of 83 participants were included (median age = 55.81 years, 54% secondary education). IDEA demonstrated good feasibility, with an average completion time of 45-60 minutes depending on participant engagement. Content validity was established by unanimous expert consensus. Construct validity showed meritorious sampling adequacy (KMO = .872) and significant sphericity (Bartletts test {chi}^2 (15) = 278.523, p<.001), supporting factor analysis. Internal consistency showed good reliability across six domains (Cronbachs = 0.896). IDEA is a valid and reliable tool for assessing aphasia in Indonesian natives. It is a culturally appropriate assessment tool which offers structured, domain-based evaluation and supports differential diagnosis of both classical and progressive aphasia syndromes. Keywords: Aphasia, Language Assessment, Indonesian, IDEA, Validity

Background. Early diagnosis and intervention are crucial in multiple sclerosis (MS), yet diagnostic delays are common. Large language models (LLMs) such as generative pre-trained transformers (GPTs) may help streamline diagnostic workflows by extracting MS diagnostic signals from clinical notes. Objective. To derive MS diagnosis status from the first neurology note using a computable algorithm based on the 2017 McDonald criteria and applying GPT-4 for node-level reasoning within a structured decision framework. Methods. We analyzed first neurology notes from 125 randomly selected patients (including those with MS, related disorders, and controls) enrolled in a clinic cohort between 2017 and 2023. We included the clinical history and diagnostic testing sections but redacted the assessment and plan. We converted the 2017 McDonald criteria into a decision tree and provided expert-curated clinical knowledge to guide GPT-4 reasoning at each decision node. GPT-4 generated binary decisions at each node to traverse the tree and classified MS diagnoses at terminal nodes. We evaluated performance against neurologist-assessed diagnoses and characterized hallucinations (non-factual, incongruent, irrelevant, over-reliant, and logical reasoning errors). Results. In this study cohort (mean age 40{+/-}13 years; 81% women) representative of the clinic population, GPT-4 performed well in predicting MS diagnosis (84% accuracy, 79% precision, 74% recall, 91% specificity) using first neurology notes. Hallucinations occurred in 32 cases (26%), most commonly incoherence (75%) and overreliance (47%). Conclusion. A structured, LLM-guided decision framework can flag MS diagnoses from early clinical documentation. Large-scale studies are needed to mitigate hallucinations, validate this approach, and test implementation in clinical settings.

Introduction: Intracerebral hemorrhage (ICH) carries higher morbidity and mortality than ischemic stroke. Recent studies have demonstrated improved patient outcomes by applying ultra-early bundled interventions including blood pressure management, coagulopathy reversal, and osmotic therapy. Effective strategies to deliver these ultra-early treatment options are currently being explored. On December 19th, 2022, the Mayo Clinic Comprehensive Stroke Center (CSC) launched the "ICH Phases'' communication system to accelerate ICH patient care. Objective: To evaluate adherence to the AHA/ASA guidelines in acute ICH care following the implementation of our novel-tiered paging system. Methods: We retrospectively reviewed patients admitted with spontaneous ICH during 2024 and 2025. We excluded traumatic cases. We extracted clinical data such as time to imaging, documentation of ICH score, blood pressure control, reversal of anticoagulation, venous thrombo-embolism (VTE) prophylaxis and discharge disposition. Results: Among 67 patients, 68.7% underwent CT imaging within 25 minutes. We documented the ICH score within 6 hours in 82.9% of patients. Nearly 94.7% of patients with SBP>140 mm Hg received antihypertensive therapy, yet only 18% reached target BP within 60 minutes. We completed the reversal of anticoagulation within 120 minutes in 75% of patients. VTE prophylaxis was initiated within 24 hours in 91% of patients. Discussion: Our novel system demonstrated adherence to the AHA/ASA guidelines, and time sensitive benchmarks in neuroimaging, reversal of anticoagulation, and VTE prophylaxis. Early BP control remains a challenge, that highlights the discrepancy between guidelines and real-ground implementation. Conclusion: A novel tiered paging system is effective for enhancing early ICH care. Such a holistic system remains critical for sustained improvement in quality of care.

Background: Mechanical thrombectomy (MT) is a time-sensitive reperfusion treatment for acute ischemic stroke caused by large-vessel occlusion. Workflow time metrics for MT remain poorly characterized in Indonesia, where stroke burden is substantial. This study describes pre-hospital and in-hospital time-interval metrics for MT across two major tertiary hospitals in Jakarta and evaluates institutional trends over a nine-year period. Methods: We conducted a retrospective descriptive study of consecutive patients undergoing MT at dr. Cipto Mangunkusumo National General Hospital (RSCM) and Prof. Dr. dr. Mahar Mardjono National Brain Center Hospital (RSPON) from 2017 to 2025. Pre-hospital and in-hospital time-interval metrics were reported as median (interquartile range [IQR]) and stratified by institution. Results: Among 330 registered patients, 71 were excluded due to incomplete data, leaving 259 in the final cohort (RSCM n=38; RSPON n=221). The pooled cohort had a mean age of 58.12 {+/-} 11.09 years; 63.71% were male. Hypertension was the most prevalent vascular risk factor (53.67%). Median door-to-CT time was 9 minutes (IQR 18), door-to-decision 101 minutes (IQR 100), and door-to-groin puncture 272 minutes (IQR 152). Total ischemic time (onset-to-groin puncture) was 468 minutes (IQR 294). MT volume increased substantially over the study period, particularly after 2022 at RSPON, which also demonstrated progressive improvement in in-hospital workflow times. RSCM showed increasing delays in later years, consistent with institutional congestion at a general multispecialty center. Conclusions: Early brain imaging was achievable at both centers; however, post-imaging delays particularly in CT-to-groin intervals, represent the dominant in-hospital bottleneck. Future quality-improvement efforts should prioritize decision-making, team mobilization, and pre-hospital coordination to reduce total ischemic time and improve access to reperfusion therapy.

Background: Cerebral vasospasm is a frequent complication after aneurysmal subarachnoid hemorrhage (aSAH) and is associated with delayed cerebral ischemia (DCI) and unfavorable outcome. While CTA-based vasospasm grading is frequently used, its relationship with actual cerebral perfusion remains incompletely understood. This study investigates the association between vasospasm severity and distribution and territorial perfusion deficits. Methods: In this retrospective single-center study, 513 CT examinations (CTA and CT perfusion) from 194 patients with aSAH were analyzed. Vasospasm was graded per vessel segment using the CTA Vasospasm Score, and perfusion deficits were assigned to corresponding vascular territories (left/right anterior circulation, posterior circulation). Vasospasm distribution was further classified by severity and multifocality. Associations between vasospasm score and perfusion deficits were assessed using a generalized linear mixed model with binomial distribution, adjusting for Hunt & Hess grade, modified Fisher score, and days since hemorrhage. Results: Vasospasm was detected in 79.3% of examinations, and a perfusion deficit in at least one territory was present in 62.6%. The proportion of perfusion deficits increased progressively with both vasospasm severity and multifocality, ranging from 21.7-25.0% in the absence of vasospasm to 81.2-82.2% in severe multifocal vasospasm. The CTA Vasospasm Score was significantly associated with perfusion deficits in all territories (OR 1.36-1.50), with stronger associations in the anterior than posterior circulation. Conclusion: Vasospasm severity and distribution are strongly associated with perfusion deficits, supporting a continuum model of ischemic risk. However, the substantial proportion of perfusion deficits occurring independent of vasospasm suggests additional microcirculatory mechanisms not captured by CTA. CT perfusion should be considered complementary to CTA, particularly in clinically deteriorating or non-assessable patients.

We used the September 2013 age-based rollout of the live-attenuated shingles vaccine in England as a natural experiment to estimate the effect of vaccine eligibility on shingles and dementia diagnoses in linked hospital records. Individuals born just before and after the eligibility cutoff were compared using regression discontinuity methods, with follow-up for up to eight years after programme introduction. Eligibility was associated with a clear reduction in hospital-coded shingles diagnoses (RD estimate -0.12 percentage points, 95% CI -0.153 to -0.079; p = 5.9 x 10-10), but there was no evidence of a corresponding reduction in hospital-coded dementia diagnoses (RD estimate -0.06 percentage points, 95% CI -0.40 to 0.27; p = 0.72). Results were robust across denominator definitions, diagnostic-code specifications, estimator choice, placebo cutoffs, and negative-control analyses. The dementia estimate was also close to null in an independently conducted analysis using a separately held HES extract. Comparator analyses in Welsh data with linked primary care and death data did not suggest these results were driven by our reliance on hospital data. These findings do not support a detectable intention-to-treat effect of live-attenuated shingles vaccine eligibility on hospital-coded dementia in England.

Prenatal alcohol exposure (PAE) is a major cause of neurodevelopmental disorders, yet most children are diagnosed late or misdiagnosed. Neuroplacentology suggest that placental factors released into maternal and/or umbilical cord blood contribute to fetal brain development. Consistently, a preclinical inter-organ transcriptomic database revealed that PAE disrupts the expression ratio of angiogenic and inflammatory factors suggesting an angio-inflammatory response. This study aimed i) to assay, by multiplex immunoassay, angiogenic and inflammatory factors in maternal and umbilical cord blood from alcohol-consuming women and ii) to perform a maternofetal analysis according to neonatal sex. Afterwards, dysregulated factors from mothers who gave birth to females or males were submitted to STRING and ShinyGO analyses. Results showed that PAE differently altered the distribution profiles of dysregulated angiogenic and inflammatory factors in maternal and umbilical cord blood. Moreover, sex-specific differences were observed, with 36% of dysregulated proteins specific to males, 48% to females, and 16% common to both. STRING analysis revealed robust functional protein-protein interactions linking together inflammatory and angiogenic clusters while the ShinyGO analysis identified enriched pathways related to vascular shear stress. These findings provide the first maternofetal analysis of combined angiogenic and inflammatory factors from alcohol-consuming mothers.

People differ widely in their sensitivity to pain, and this variability is clinically relevant, yet the underlying structural brain mechanisms remain poorly understood. White matter hyperintensities (WMH), a common imaging marker of cerebral small vessel disease, are associated with microstructural abnormalities in white matter tracts and have also been linked to pain related outcomes; however, the mechanisms linking WMH to altered pain perception remain unclear. We investigated whether WMH are linked to pain sensitivity through tract specific microstructural alterations and cortical structural differences. We analysed data from 1,448 participants (mean age 73 years; 53% women) in the population based Rotterdam Study and independently replicated the findings in 1,522 participants (mean age 63 years; 52% women) from the population based Tromso Study. Pain sensitivity was quantified using the cold pressor test. Multimodal magnetic resonance imaging, including T1 weighted, fluid attenuated inversion recovery and diffusion tensor imaging, was used to map WMH to predefined white matter tracts, derive tract specific fractional anisotropy (FA), and estimate cortical measurements. Cox proportional hazards models assessed associations with pain sensitivity, and tract specific mediation analyses evaluated whether white matter microstructure or tract connected cortical regions mediated the relationship between white matter hyperintensities and pain sensitivity. WMH were present in 20 of 27 predefined tracts and were associated with reduced FA in 18 tracts. Higher WMH burden was associated with greater pain sensitivity, particularly in the left anterior thalamic radiation and left superior thalamic radiation, while lower FA in the anterior thalamic radiation, medial lemniscus, superior thalamic radiation and inferior fronto occipital fasciculus was associated with greater pain sensitivity. Mediation analyses showed that white matter microstructural disruption was the principal pathway linking WMH to pain sensitivity, with the strongest indirect effects observed through the inferior fronto occipital fasciculus (44.6% mediated) and anterior thalamic radiation (32.6% mediated). Cortical atrophy in the precentral and postcentral gyri provided a smaller secondary pathway, mediating approximately from 3 to 6% of the association between corticospinal or superior thalamic radiation WMH and pain sensitivity. Replication analyses supported these cortical mediation pathways, and meta analysis strengthened the tract specific associations. Together, the results suggest that vascular white matter injury is associated with pain perception through specific structural pathways, with DTI based markers appearing particularly sensitive to these relationships.