Stroke: Vascular and Interventional Neurology

Background: Three-dimensional visualization and quantitative analysis of cerebral arteries on 3DRA are central to endovascular treatment planning, device selection, and cerebrovascular research. Manual segmentation is time-consuming and operator-dependent, yet no open-source deep learning model has been prospectively validated for this task on 3DRA. Methods: A nnUNet v2 model was trained for binary cerebral artery segmentation on 400 consecutive 3DRA acquisitions from three angiographic systems, comparing four configurations across architectures and loss functions. The best-performing configurations were prospectively validated on 40 patients using a dual approach: quantitative metrics (DSC, clDice, HD95, ASD, Precision, Recall), and blinded expert qualitative evaluation by two interventional neuroradiologists assessing 12 arterial segments, a global quality score, and clinical usability across 40 test cases. Results: The ensemble model achieved median DSC 0.917, clDice 0.932, and HD95 1.494 mm. Global quality scores were significantly lower for nnUNet v2 than for expert segmentations (median 4 vs 5, p<0.001), but nnUNet v2 segmentations were rated clinically usable in 88-90% of cases versus 95-98% for expert segmentations, without significant difference on the binary usability criterion. A consistent proximal-to-distal quality gradient was identified, with comparable scores at proximal arteries and the largest differences at distal arterial segments. Conclusion: nnUNet v2 with topology-aware training provides clinically usable cerebral artery segmentations on 3DRA, prospectively validated through both quantitative metrics and structured expert qualitative assessment, and represents a reproducible open-source foundation for endovascular and research applications.

Background and Purpose: Futile interhospital transfers, where patients transferred for endovascular thrombectomy (EVT) do not ultimately receive the procedure, represent a critical systemic burden on stroke transfer network. Whether pre-transfer computed tomography angiography (CTA) at the primary stroke center (PSC) reduces futile transfers, and at what workflow cost, remains incompletely characterized. Methods: This retrospective study enrolled 314 acute ischemic stroke patients transferred for potential EVT within the Tainan-Chiayi Stroke Network (October 2021-September 2025). Patients were stratified by CTA timing: pre-transfer (n=66) versus post-transfer (n=248). Workflow time metrics and 90-day functional outcomes were compared. Futile transfers were classified into three categories: preventable over-triage, physiological futility, and gray zone cases. Results: The futile transfer rate was substantially lower in the pre-transfer CTA group (27.3% vs. 66.1%; P<0.001), with post-transfer CTA as the strongest independent predictor of futility (aOR 5.21; 95% CI 2.83-9.60). In the post-transfer CTA group, 40.2% of futile transfers involved conditions identifiable by pre-transfer CTA. Regardless of CTA timing, gray zone cases predominated in both groups (83.3% vs. 47.6%), driven by intracranial atherosclerotic stenosis/ chronic total occlusion, large infarct cores, and medium vessel occlusions. Pre-transfer CTA significantly prolonged PSC door-in-door-out time (140 vs. 88 min; P<0.001) and showed numerical trends toward longer onset-to-EVT time and lower rates of favorable functional outcome. Conclusions: Adopting CTA during the pre-transfer period reduces preventable futile transfers but prolongs PSC processing time. Nevertheless, the persistent gray zone requires strategies beyond imaging alone, and the trade-off between triage precision and transfer efficiency warrants ongoing evaluation across different stroke networks settings.-

Background and Purpose: Hemorrhagic transformation (HT) is a serious complication of endovascular thrombectomy (EVT), yet dedicated prediction models for young adults are lacking. We aimed to develop and externally validate a simplified risk score for HT in young adults with acute ischemic stroke undergoing EVT. Methods: This multicenter retrospective study included patients aged 18 to 49 years with acute anterior circulation large vessel occlusion who underwent EVT. The primary outcome was any HT within 24 hours after EVT. Multivariable logistic regression was used to identify independent predictors of HT, from which the NO?PAIN Score was derived. External validation was performed in an independent cohort of 138 patients. Results: Among 598 patients in the derivation cohort, HT occurred in 176 (29.4%). Five independent predictors were identified: admission NIHSS, number of thrombectomy passes, atrial fibrillation, alcohol consumption, and mTICI grade. The mTICI grade demonstrated a non-linear, inverted U-shaped relationship with HT risk, peaking at partial recanalization. The NO-PAIN Score showed acceptable discrimination in both the derivation (C-index, 0.737; optimism-corrected C-index, 0.748) and external validation cohorts (C-index, 0.726), with satisfactory calibration. Conclusions: The NO-PAIN Score is a simple risk prediction tool for HT after EVT in young adults with acute anterior circulation large vessel occlusion. It may assist in individualized risk stratification in this population.

Background: Circulating endothelial progenitor cells (cEPCs) contribute to vascular repair following an ischemic stroke. The aim of the study was to evaluate the association between cEPCs and functional outcomes in patients with acute ischemic stroke (AIS) due to large vessel occlusion (LVO) who received endovascular therapy (EVT). Methods: Prospective study of patients with LVO-AIS who received EVT. Blood samples were obtained within 24 +- 12 hours and on day 7+-1 from stroke onset. cEPCs were detected using flow cytometry (CD34+/VEGFR2+/CD133+). The primary endpoint was a favourable functional outcome (modified Rankin Scale 0-2) at three months of follow-up. Secondary endpoints include baseline to 24 hours/day 7 changes in the National Institutes of Health Stroke Scale (NIHSS) score and collateral circulation (CC) status. Bivariate and multivariable logistic regression analyses were performed. Results: Included were 90 patients (73.2+-12.7 years, 41.1% women) in 42 of whom (46.7%) cEPCs were detected at 24 hours. On day 7, cEPCs were detected in 27 (43.6%) of 62 patients for which this information was available. Atrial fibrillation, prior anticoagulant treatment and stroke onset-to-door time <6 hours were associated with lower cEPC counts, and intravenous fibrinolysis therapy was associated with a higher cEPC count on day 7. No association was found between cEPCs and functional outcomes at three months. Patients with the highest cEPC count (Q4) at 24 hours had a lower probability of good CC (46.2% vs 77.3%; p=0.031). Conclusion: cEPC count in patients with LVO-AIS who received EVT was not associated with functional outcomes.

Background and Purpose Prognostication after acute ischemic stroke often relies on limited variables and simple risk scores, despite richer information being available at admission. We developed a multimodal AI model using admission data to predict modified Rankin Scale (mRS) outcomes and compared it to established tools. Methods In a retrospective study of ischemic stroke/TIA patients, we trained three modality-specific models on admission non-contrast head CT, history and physical notes, and structured clinical variables, and combined them in a weighted-average ensemble. We predicted binary (mRS 0-2 versus 3-6) and ordinal mRS (0-6) outcomes at discharge and 90 days. Performance on an external test cohort was compared with THRIVE and SPAN-100 scores using AUROC, AUPRC, Brier score, mean absolute error (MAE), and quadratic weighted kappa (QWK). Results A total of 6,915 patients were split into training, validation and testing cohorts in a 3:1:1 ratio. For discharge binary mRS (n=1596), the multimodal ensemble achieved significantly better discrimination (AUROC 0.859, AUPRC 0.858) with 25-61% lower Brier scores than THRIVE or SPAN?100 (all p<0.001). For 90?day binary mRS (n=207), the model also outperformed both THRIVE and SPAN-100 (AUROC 0.838, AUPRC 0.805, with 3-38% lower Brier scores). Ordinal mRS prediction showed similarly strong performance with significantly better QWK at discharge and numerically lower MAE. The multimodal ensemble model reassigned about one?third of patients to different risk categories versus THRIVE and was closer to the true discharge outcome in ~74% of discordant cases. Conclusions We developed a well-calibrated multimodal AI model for prediction of discharge and 90-day post-stroke functional outcomes using only data present at the time of admission. This model outperforms existing prognostic tools and can support early clinical decision-making.

Stroke is a leading cause of disability and mortality worldwide, with ischaemic stroke the most prevalent type. Statins, used for cholesterol management, have demonstrated benefits in reducing stroke risk and improving outcomes in preclinical studies. However, the impact of pre-stroke statin use on stroke outcomes remain inconsistent. In this study, we aim to evaluate whether pre-stroke statin use is associated with greater volume of salvaged tissue and improved cerebral collateral perfusion. A retrospective analysis was conducted using data from 281 patients presenting with acute ischemic stroke to the John Hunter Hospital between May 2015 and May 2020. Patients were grouped based on pre-stroke statin use, and clinical variables, including infarct volume and collateral perfusion, were assessed. The primary outcome was salvage volume derived from baseline perfusion lesion volume minus infarct volume at follow-up. Collateral perfusion was measured by the hypoperfusion volume defined by delay time (DT)>6 seconds divided by the hypoperfusion volume defined by DT >2 seconds. Patients on statins at admission were significantly older and had more comorbidities. No significant association was found between pre-stroke statin use and salvage volume or collateral perfusion after adjusting for covariates. Larger initial infarct core was a significant predictor of salvage volume due to larger salvageable tissue volume at baseline. These findings indicate that pre-morbid statin use is not associated with larger salvage volume or improved cerebral collateral perfusion.

Background: A substantial proportion of coronary events originate from angiographically moderate lesions, indicating that stenosis severity alone does not reflect lesion biomechanical risk. Objectives: To test whether adding lesion-adjacent pericoronary adipose tissue (PCAT) and CTCA-derived anatomy-flow descriptors to quantitative plaque assessment improves identification of future culprit lesions, with a prespecified focus on moderate stenosis. Methods: We performed a within-patient, lesion-level case-control analysis in the GeoCAD cohort, including patients undergoing coronary revascularisation during follow-up. Culprit lesions were identified from longitudinal CTCA. Stenosis severity, quantitative plaque composition, and PCAT volume were quantified (MEDIS), and vessel centreline geometry and lesion haemodynamics derived using computational modelling. Incremental prognostic value was assessed using Cox models with drop-one and stepwise workflow analyses, including a prespecified subgroup analysis of moderate stenosis lesions (25 - 49% diameter stenosis). Results: Among 46 patients (212 lesions; 55 culprit), percent area stenosis (%AS) dominated culprit lesion discrimination (HR: 2.01; 95% CI: 1.54 - 2.62; p < 0.001). In 82 moderate-stenosis lesions (30 culprit), %AS provided minimal discrimination ({Delta}C-index: 0.01; p=0.895). Culprit lesions were characterised by greater PCAT volume (HR: 1.75; 95% CI: 1.29 - 2.37; p < 0.001), higher helical flow intensity (HR: 1.35; 95% CI: 1.16 - 1.57; p < 0.001), and lower torsion (HR: 0.50; 95% CI: 0.29 - 0.84; p=0.009). Adding anatomy-flow descriptors improved risk stratification for moderate lesions beyond CTCA stenosis and plaque/PCAT features (p=0.007). Conclusions: In moderate stenosis, lesion-adjacent PCAT and anatomy-flow descriptors provided incremental prognostic information beyond luminal narrowing and plaque composition, supporting integrated CTCA phenotyping to identify high-risk nonobstructive coronary lesions.

Objective: Outcome after surgical hematoma evacuation for intracerebral hemorrhage (ICH) depends on hematoma location. As corticospinal tract (CST) integrity affects motor recovery after stroke, we hypothesized that CST integrity drives heterogeneity in surgical outcomes and investigated this in a secondary analysis of MISTIE-III participants. Methods: Risk of CST injury was categorized into four levels, based on the interaction between the CST, the hematoma, and perihematomal edema (PHE) on automatically segmented stability CT: no risk, PHE infiltration, hematoma infiltration, and complete interruption of the CST. Associations with outcome were tested using multivariable linear regression for motor National Institutes of Health Stroke Scale (NIHSS) at day 180 and ordinal regression for modified Rankin Scale (mRS) at day 365, introducing an interaction term between CST risk and treatment group. Results: Day 180 motor NIHSS was significantly lower for 'no risk' ({beta}:-3.77, [95% confidence interval [CI]: -5.8 to -1.70], p=0.0003) and 'PHE infiltration' ({beta}:-2.3, [95%CI: -3.5 to -1.1]; p=0.0002) vs. 'complete interruption'. Surgery was associated with lower Day 180 motor NIHSS in participants with hematoma infiltration ({beta}:-2.07, [95%CI: -3.8 to -0.4], p=0.016). Compared to complete interruption, 'no risk' (adjusted odds ratio [aOR]:0.27, [95%CI: 0.10 to 0.74], p=0.01) and 'PHE infiltration' (aOR:0.41, [95%CI: 0.23 to 0.74]; p=0.003) were associated with lower odds of unfavorable day 365 mRS. Surgery was associated with lower mRS in participants with no risk (aOR:0.23, [95%CI: 0.05 to 0.97, p=0.045). Interpretation: Increasing CST risk is associated with worse motor recovery (day 180) and disability (day 365). CST risk modifies the effect of the MISTIE-III procedure on motor recovery and disability.

Purpose: Accurate assessment of the pressure gradient ({Delta}P) across aortic coarctation (CoA) is critical for determining disease severity and the need for intervention. Current non-invasive methods are unreliable, while invasive catheterization remains the clinical gold standard. This study evaluates a novel MRI acquisition strategy, 4D-FlowP, that simultaneously encodes blood velocity and acceleration to enable reliable non-invasive pressure gradient mapping in CoA. Methods: Patient-specific compliant aortic phantoms were created from clinical MRI data of two patients with CoA. Additional geometries were synthetically generated by increasing stenosis severity. Phantoms were studied in an MRI compatible flow loop under physiologically realistic flow and pressure conditions. Pressure gradients were estimated using conventional 4D-Flow MRI, 4D-FlowP, and fluid-structure interaction (FSI) simulations. Results were compared against ground-truth catheter-based measurements across multiple flow rates and stenosis severities. Results: Conventional 4D-Flow consistently underestimated {Delta}P (slope = 0.63, R2=0.75) relative to catheter measurements. In contrast, 4D-FlowP demonstrated substantially improved agreement (slope = 0.95, R2=0.75). FSI simulations showed the highest overall agreement with catheter-derived {Delta}P (slope = 1.14, R2=0.82). Scan times for 4D-FlowP were comparable to 4D-Flow (26 vs. 24 minutes). Conclusion: 4D-FlowP enables a more accurate MRI-based pressure gradient mapping in CoA than conventional 4D-Flow, when compared to ground truth catheter measurements. These findings support further in vivo evaluation of 4D-FlowP as a non-invasive alternative for functional assessment of CoA severity

Background: The Functional Outcome in Patients with Primary Intracerebral Hemorrhage (FUNC) score was initially validated for prediction of functional independence on the Glasgow Outcome Scale (GOS) 90 days after intracerebral hemorrhage (ICH), but recovery often extends beyond three months. Aims: Our objective was to extend the FUNC score for prediction of 12-month functional independence to strengthen its utility for family counseling and research methodology. Methods: We conducted a single-center prospective cohort study enrolling adult patients with primary ICH between February 2009 and January 2018. We calculated FUNC scores at admission and assessed GOS 12 months after ICH. The primary outcome was 12-month functional independence, defined as a GOS score [&ge;]4. We calculated the area under the receiver operating characteristic curve (AUC) of the FUNC score using logistic regression, handling missing GOS with multiple imputation by chained equations. We evaluated score calibration using a calibration curve and the Brier score, and we assessed clinical utility using decision curve analysis. We explored the statistical efficiency gains of using FUNC-based sliding dichotomy thresholds for favorable outcome definitions by running simulations of a clinical trial with 1:1 randomization. We ran 5000 simulations for each sample size (100 to 1000, in increments of 10) and treatment effect (odds ratio of 1.5, 2.0 and 2.5) combination and calculated efficiency gains for each respective treatment effect as the percentage reduction in sample size required to have 80% power using sliding versus fixed dichotomy thresholds. Results: A total of 535 patients were included (median [IQR] age 68 [54-79], 237 [44%] female, median [IQR] NIHSS 16 [6-25], median [IQR] FUNC 8 [6-9]). Overall, 99 of 445 (22%) patients with known 12-month GOS achieved functional independence. The FUNC score had an AUC of 0.79 (95%-CI: 0.75-0.84) for 12-month functional independence. The calibration plot was reasonable, with modest evidence of overestimation at low predicted probabilities, and the Brier score was 0.15. A net benefit was observed across 5-50% threshold probabilities. Sliding dichotomy had an efficiency gain of 27% for a treatment effect of OR=2.0, and a gain of 22% for a treatment effect of OR=2.5. The efficiency gain for a treatment effect of OR=1.5 could not be calculated because the fixed dichotomy did not reach 80% power despite a sample size of 1000 patients. Conclusions: The FUNC score's predictive performance for 12-month functional independence was comparable to its originally validated 3-month discrimination. Following external validation across centers, the FUNC score may be leveraged to counsel families on global measures of long-term functional independence and to implement sliding dichotomy methodology in ICH research.

Introduction: Precise anatomical navigation is fundamental to safe endoscopic pituitary surgery, a high-stakes procedure characterised by a challenging learning curve. While traditional navigation systems often rely on workflow-disrupting probes or static preoperative imaging, advancements in computer vision AI (CVAI) now enable dynamic, real-time anatomical segmentation directly from live surgical video1-3. Our group has previously conducted a series of preclinical human-computer interaction studies to refine the system's design, alongside digital and high-fidelity physical simulations demonstrating the benefit of AI assistance in improving overall performance, training, and safety4-8. Building on this foundation, the current study represents a first-in-human application of real-time CVAI assistance in the neurosurgical operating room, serving to assess feasibility and safety, and to iteratively improve the system. Method: Guided by DECIDE-AI and IDEAL frameworks, this single-centre evaluation comprises an initial proof-of-concept phase (n=6) for endoscopic transsphenoidal pituitary surgeries. The AI model utilised a DINOv3-derived vision transformer architecture, deployed via a high-performance edge computing unit to achieve low-latency, real-time inference without reliance on cloud infrastructure2. Given the high-risk nature of the procedure and the early stage of clinical AI integration, the system was initially deployed as an educational adjunct on a secondary monitor, ensuring the primary surgical feed remains uncompromised. Functionality and safety were assessed via structured questionnaire, prospective observation, and blinded retrospective review of the recordings of the endoscopic surgical video feed and wider operating room environment. Continuous multi-stakeholder feedback through validated human factors surveys drove iterative technical refinements between cases. Results: Six patients with pituitary adenomas were enrolled. The CVAI system was successfully deployed in four cases, demonstrating acceptable real-time sella segmentation accuracy. Deployment failed pre-operatively in two cases owing to a single recurring system reboot bug. Iterative refinement between cases were driven by our experience and surgical team feedback. This resulted in the integration of additional anatomical structure segmentations (e.g., carotid arteries), enhanced model accuracy via training dataset expansion, and hardware firmware upgrades. Multi-stakeholder surveys demonstrated satisfactory system feasibility, usability, and acceptability among the surgical team. Both prospective observation and retrospective video review confirmed the absence of adverse events, including no significant distraction to the primary surgeon, and there were no AI-related clinical complications. Conclusion: This first-in-human early clinical evaluation demonstrates the feasibility, safety and iterative development of real-time, CVAI-based anatomical navigation during high-stakes neurosurgery. Future work will include a larger single-centre case series (IDEAL Stage 2a) with more surgical teams to further iterate the system and explore its impact on training and workflow. As the underpinning technology improves, deployment will transition to direct intra-operative decision support and integration with other intra-operative navigational technologies.

High-density electrophysiological recording using Neuropixels probes enables single-unit resolution of human neural activity. However, integrating these systems into clinical environments remains challenging. Reported human recordings have been limited to a few centres in the United States utilising variable regulatory, sterilisation and operative techniques. Here, we present human Neuropixels recordings under a nationally managed ethical and regulatory framework in the United Kingdom. We provide a reproducible roadmap to overcome regulatory and equipment constraints. Guided by the IDEAL Stage 2a (Development) framework, we established a frameless intraoperative workflow utilising manufacturer-sterilised probes and a commercially available, clinical-grade setup for Neuropixels insertion including micromanipulator and endoscope holder. We prospectively evaluated this workflow across six participants (mean age 62.5 years) undergoing elective ventriculoperitoneal shunt surgery. Iterative failure-mitigation cycles successfully resolved key technical barriers, including neuronavigation interference and hardware instability. Assessed across three predefined endpoints (clinical safety, procedural timing, and neural data yield), the workflow achieved zero research-related adverse events and maintained a strict 30-minute procedural extension. Progressive technical refinements increased single-unit yield from 25 units during early development to 146 manually curated units. This approach provides a scalable, clinically integrated workflow to safely perform high-density electrophysiology in routine neurosurgical environments.

Background: With growing impetus to integrate artificial intelligence (AI) tools into radiology, clinical practices must navigate workflow redesign. This carries implications for medical malpractice liability. Methods: We conducted an online vignette experiment with United States adults who acted as hypothetical jurors in a malpractice case involving a missed intracranial hemorrhage. Participants (n=2,347) were randomized to one of 22 conditions: a no-AI control and 21 conditions involving a hypothetical AI system. These twenty-one conditions varied by whether (1) a single-read or double-read workflow was used, (2) the radiologist's initial interpretation was documented, (3) the radiologist changed their interpretation after viewing AI output, (4) the AI detected the abnormality, and (5) the AI error rate--False Discovery Rate (FDR) or False Omission Rate (FOR--was provided to participants only, both participants and radiologist, or neither. The primary outcome was perceived liability, assessed by whether the radiologist met their duty of care. Findings: Perceived liability differed across conditions (p<0.0001). Double-read workflows (p<0.0001), documenting initial interpretations (p=0.0125), and providing participants with AI error rates, including the FDR (p=0.0038) or FOR (p=0.0035), reduced perceived liability. Liability was also lower when AI was incorrect (p<0.0001). Radiologists' awareness of AI error rates did not significantly impact liability. Notably, we observed an erroneous change penalty: the greatest liability occurred when radiologists initially identified an abnormality but later changed their interpretation to normal after seeing that AI identified the case as normal; conversely, perceived liability was lowest with documented, double-read workflows. Interpretation: Double-read workflows with documented initial interpretations and disclosure of AI error rates reduce perceived liability, though changing a correct initial interpretation increases it. Strategic workflow design is critical for successful AI implementation that can mitigate malpractice risk.

Background: Before transcatheter aortic valve replacement (TAVR), patients with severe aortic valve stenosis are at an increased risk of developing fluid volume overload and heart failure, which is associated with subsequent adverse outcomes after TAVR. Purpose: To quantify fluid volume status as whole-body fast-exchange extracellular volume (FE-ECV) in patients undergoing TAVR compared to healthy reference values using photon-counting CT (PCCT). Methods: Consecutive patients referred for TAVR and healthy living kidney donor candidates, respectively, underwent PCCT including the pelvis. FE-ECV (mL) was quantified using venous hematocrit, injected iodinated contrast concentration and volume, and blood iodine concentration and urinary bladder excreted iodine mass quantified in iodine map regions of interest from the inferior vena cava and covering the urinary bladder, acquired at one time point 6-10 minutes after intravenous iodinated contrast administration. Results: The study included 156 subjects (healthy: n=51, age 47{+/-}9 years, 55% female; TAVR: n=105, age 78{+/-}6 years, 39% female). In healthy subjects, FE-ECV was 160{+/-}22 mL/kg lean body mass (LBM), 95% limits 116-204 mL/kg LBM, and was independent of age, sex, contrast agent type, and scan delay time after contrast injection (p>0.66 for all). Compared to healthy subjects, FE-ECV in patients referred for TAVR was higher (174{+/-}34 mL/kg LBM, p=0.01), with 19 patients (18%) exceeding the normal range. Conclusion: One in five patients referred for TAVR demonstrated increased FE-ECV, revealing a substantial prevalence of fluid overload detectable by single-time point late-phase PCCT iodine mapping.

Background:Stroke continues to be one of the major causes of death and long-term disability worldwide, with a greater impact in low-and middle-income countries. In India, there is limited evidence examining stroke burden and its changes over time and across regions. Therefore, we aimed to assess the burden of stroke in India from 1990 to 2023 using the latest data from the Global Burden of Disease (GBD) Study, along with projections up to 2035. Methods:We used estimates from the GBD 2023 study to examine stroke incidence, prevalence, mortality, and disability-adjusted life years (DALYs) in India from 1990 to 2023. Age-standardized rates were analyzed to understand how these measures have changed over time. We also conducted state-level analyses to explore regional differences in stroke burden. The contributions of all major modifiable risk factors were assessed using population-attributable fractions. In addition, we projected future trends in stroke burden up to 2035. Results:From 1990-2023, the percentage change in overall stroke burden in India showed minimal variation across key indicators. Incidence remained largely stable (0.00%[-0.04 to 0.05]), while prevalence showed a slight increase(0.06%[0.03 to 0.10]). Mortality (-0.11%[-0.36 to 0.20]) and DALYs (-0.17%[-0.38 to 0.12]) demonstrated modest declines over the study period. Notable regional disparities were evident, with states such as Chhattisgarh, Assam, and Jharkhand bearing the highest burden. High systolic blood pressure remained the leading risk factor in 2023, contributing the largest share of stroke-related deaths, followed by dietary risks, air pollution, tobacco use, and high body mass index. Future projections indicate that by 2035, stroke prevalence is likely to increase, while incidence, mortality, and DALYs are expected to show only modest changes. Conclusions: Stroke remains a major and growing public health challenge in India with a continuing increase in burden despite slight improvements in age-standardized rates over time. Addressing this challenge will require stronger prevention efforts, better control of key risk factors, and focused strategies to reduce regional disparities in stroke burden nationwide.

Background: Immune-mediated mechanisms are increasingly implicated in childhood arterial ischemic stroke (AIS), but the associated inflammatory pathways and how they differ by stroke subtype and outcome remain poorly understood. Understanding immune responses to AIS may identify subtype-specific mechanisms and inform targeted strategies to reduce ischemic injury. Methods: We conducted a prospective cohort study with cross-sectional transcriptomic analysis through the Vascular Effects of Infection in Pediatric Stroke Study Part II (VIPS II) at 22 academic centers in the United States, Canada, and Australia between December 2016 and January 2022. Children aged 28 days to 18 years with centrally confirmed AIS were enrolled within 72 hours of stroke onset, in addition to enrollment of stroke-free well children. Peripheral blood RNA sequencing was performed on samples collected within 72 hours of stroke or at enrollment for controls. Differential gene expression (DGE) and pathway analyses were performed comparing all AIS cases to stroke-free well children. Additional cross-sectional analyses stratified by stroke subtype and neurological outcomes were performed. Results: Transcriptomes were available in 190/205 AIS cases (median age 11.7 years) and 91/100 stroke-free children (11.8 years). Stroke subtypes included 67 definite arteriopathic, 74 probable arteriopathic, 23 cardioembolic, and 26 idiopathic, with similar demographics but smaller infarct size for idiopathic cases. 47 genes (false discovery rate (FDR) <0.05 and log2 fold-change (log2FC)>1) were differentially expressed in AIS versus stroke-free well children, with upregulated pathways reflecting innate immune responses. Stratification by subtype revealed these inflammatory responses occurred after arteriopathic and cardioembolic AIS, but not idiopathic AIS; in sensitivity analyses, these findings were not explained by infarct size. Four immune-related genes were differentially expressed in children with good versus poor neurological outcomes at hospital discharge or 12 months; upregulation of one (Joining Chain; JCHAIN) correlated with poor outcomes at both timepoints. Conclusions: Compared with stroke-free children, children with AIS, particularly arteriopathic and cardioembolic subtypes, have upregulated innate immune pathways, including neutrophil activation and interleukin-1 signaling. Differential expression of immune-related genes also correlated with neurological outcomes. These findings support immune dysregulation as a key feature of early pediatric AIS while highlighting differences across subtypes and clinical outcomes, with implications for targeted immunomodulatory therapies and future biomarker development.

Background: High school students may be able to communicate health topics to peers and adults. Yet, few studies have evaluated the role of high school students in community health initiatives, making them an underutilized group for disseminating health information. We pilot tested stroke education across five high schools using varied delivery approaches as a preliminary step toward evaluating youth stroke education to improve community health. Methods: In April-May 2025, five high schools in Connecticut and New York participated in stroke education. The format was designed to fit the needs of each school and included an 8-session classroom curriculum (Derby, CT), after-school club meetings (New Haven, CT; Long Island, NY), and one large assembly (Bridgeport, CT). Developed by teachers and neurology providers, the curriculum covered stroke risk factors, symptoms, and emergency response. Students completed a 15-point assessment adapted from the validated Stroke Action Test before, immediately after, and 4-6 weeks post-intervention; data were collected between April and July 2025. Results: Of 112 students completing the pre-test, 99 (88%) completed the immediate post-test and 51 (46%) the delayed follow-up. Average scores rose from 47% pre-intervention to 75% post and 70% at 4-6 weeks. All schools scored <50% on pre-tests suggesting poor baseline stroke knowledge. Conclusion: This pilot suggests that stroke education can be delivered to high school students across varied settings and may support knowledge gains up to 6 weeks. Limitations included small sample sizes and missing follow-up data. If validated in larger studies, this adaptable, teacher-supported approach could offer a scalable public health strategy for improving community stroke preparedness.

Background: The specific 3D morphological substrates distinguishing the newly defined massive and torrential functional tricuspid regurgitation (FTR) phenotypes from standard severe disease remain under-characterized. Objectives: This study investigates the 3D geometric changes of the tricuspid valve (TV) apparatus across the spectrum of FTR, specifically focusing on the structural definition of massive and torrential grades. Methods: Three-dimensional (3D) transesophageal echocardiography (TEE) was performed in 322 patients with FTR secondary to left-sided heart disease. Patients were stratified into mild-moderate (n=166), severe (n=82), and massive-torrential (n=74) groups. TV geometry, including annular dimensions, leaflet tethering, and subvalvular apparatus, was quantified using 3D modeling software. Results: Patients with massive-torrential TR were characterized by advanced age, female predominance, and atrial fibrillation (75%). 3D analysis demonstrated that massive-torrential TR represents a distinct phenotype defined by extreme annular circularization (ellipticity index 1.0) and planar flattening (P < 0.001). Furthermore, these patients exhibited a critical leaflet-annulus uncoupling, where compensatory leaflet growth (relative length < 80%) failed to match the massive annular dilation. Consequently, the regurgitant orifice in massive-torrential grades appeared highly complex, frequently manifesting as multiple irregular orifices. Conclusions: Massive and torrential FTR are characterized by a unique geometric profile involving extreme annular circularization, severe leaflet tethering, and leaflet-annulus uncoupling. These morphological insights suggest that conventional repair strategies may be insufficient for these advanced phenotypes, highlighting the necessity for pre-procedural 3D TEE to guide device selection.

Background: Patients in socioeconomically disadvantaged neighborhoods face barriers to care. Missing BP documentation may signal gaps in risk-factor management, a crucial component of primary and secondary prevention of intracerebral hemorrhage (ICH). We tested whether neighborhood deprivation was associated with absent electronic health record (EHR) blood pressure (BP) documentation surrounding ICH and whether absent documentation predicted subsequent uncontrolled BP. Methods: We conducted a case-only study within the NIH All of Us Research Program. We included ICH survivors (ICD-10 I61.x, surviving >=1 year) with available ZIP3-based Deprivation Index. Deprivation was categorized as Privileged, Intermediate, or Deprived using cohort-based tertiles. We excluded BP measurements collected by All of Us. Outcomes were (1) absent EHR-derived BP documentation and (2) uncontrolled BP (mean systolic BP >=140 mmHg) during three windows: 1-365 days before ICH; 30-365 days and 1-5 years after ICH. Multivariable logistic regression tested associations adjusting for age, sex, and race/ethnicity. Results: 1,474 ICH survivors were included (mean age 60.1, 50.4% female). Compared to privileged neighborhoods, those living in deprived neighborhoods had higher odds of absent EHR BP documentation in the year prior to ICH (OR 2.10, 95% CI 1.60-2.76; p<0.001), 30-365 days post-ICH (OR 2.82, 95% CI 2.14-3.73; p<0.001) and 1-5 years post-ICH (OR 2.81, 95% CI 2.13-3.71; p<0.001). Absence of EHR BP documentation in the year before ICH predicted uncontrolled BP 30-365 days (OR 1.97, 95% CI 1.36-2.85; p<0.001; N=888) and 1-5 years (OR 1.83, 95% CI 1.24-2.69; p=0.002; N=814) after ICH. Absence of BP documentation 30-365 days post-ICH also predicted uncontrolled BP 1-5 years post-ICH (OR 1.66, 95% CI 1.10-2.50; p=0.017; N=814). Conclusions: Neighborhood deprivation is associated with persistent gaps in EHR BP documentation surrounding ICH, and absent documentation before or soon after ICH predicts subsequent uncontrolled BP. These findings highlight the need for community-level strategies that ensure equitable BP monitoring for socioeconomically disadvantaged populations.

Background: Stroke is a time-sensitive neurological emergency in which early EMS activation and presentation to definitive care are cornerstones of effective therapy. Large language models (LLMs) are increasingly consulted by the public for medical advice, but the veracity of the guidance provided by commercially available models responding to potential stroke symptoms is not well understood. Methods: We performed a cross-model benchmarking study comparing the triage choices of three frontier LLMs (Claude Sonnet 4.6, GPT-4o, and Llama 3.3-70b-versatile) on first-person vignettes describing a unilateral arm symptom on waking, across 10 symptom descriptors, and two clinical phases (before and after a partially reassuring self-examination), with or without a clinical distractor (n=50 per condition). Results: Claude sought emergency care most often, Llama least, and GPT-4o in between, diverging most sharply in the post-examination phase where Claude called 911 in 100% of runs, Llama called for non-emergency help in 100%, and GPT-4o was symptom-dependent. A distractor shifted behavior away from emergency care in almost all conditions: calling 911 fell from 37.9% to 14.6% and waiting rose from 0% to 45.9% in the post-examination vignette. Responses were also sensitive to symptom word: weak, limp, heavy, and clumsy generated higher alarm, whereas numb, tingly, odd, strange, and weird generated less urgent responses. Conclusions: The increasing use of LLMs for medical advice has significant public health implications. Commercially available LLMs show significant model-to-model variability and framing sensitivity when confronted with potential stroke symptoms, including under-recognition of canonical CDC warning descriptors, underscoring the need for systematic benchmarking as these tools become de facto first points of contact for patients experiencing neurological emergencies.