Stroke remains a leading cause of long-term disability worldwide, with persistent upper limb (UL) impairment affecting approximately half of survivors. Robotic rehabilitation has shown efficacy comparable to conventional therapy, but most available devices are bulky, non-wearable, and limited to institutional settings. Wearable robotic solutions combined with artificial intelligence (AI) may overcome these barriers. The present protocol study will investigate the wearability and acceptance of a new soft, exosuit robotic device, the effect on the rehabilitation of paretic UL in stroke subjects and the role of AI for movement classification and actuation.

The study will be conducted in a single neurorehabilitation center and divided into 2 phases: phase A including 10 adult healthy subjects and 10 stroke survivors who will wear the experimental robot device. The usability and acceptance of device will be ascertained by System Usability Scale (SUS); User Experience Questionnaire (UEQ); Technology Assisted Rehabilitation Patient Perception Questionnaire (TARPP-Q) measures and will be considered successfully completed whether SUS and UEQ exceed 68 and 0.8 score, respectively. Phase B is a randomized controlled trial comparing wearable robotic rehabilitation with conventional therapy in stroke survivors. Neurological evaluation will be executed by the National Institutes of Health Stroke Scale (NIHSS). Functional evaluation will be quantified according to International Classification of Functioning, Disability and Health (ICF) domains by Fugl Meyer Assessment Scale-Upper extremity (FMA-UE); Motricity Index; modified Ashworth Scale; Numerical Rating Scale; Box & Block Test; Frenchay Activity Index. Functional measures will be taken at baseline, at 2 weeks, at 4 weeks, at discharge, and at follow-up, except FMA-UE. AI algorithms will be developed to automatically assess movement quality and predict assistance intensity.

The protocol tests a novel wearable device for the recovery of UL in stroke survivors overcoming the limitations of currently used robot equipment and promoting a new approach to rehabilitation outside the institutional setting. AI associated to robot rehabilitation could enhance the patient's recovery and open the way to novel therapeutic practices.

Although mechanical thrombectomy (MT) achieves high recanalization rates in acute ischemic stroke (AIS), functional outcomes remain highly inconsistent. We aimed to evaluate the effectiveness of radiomics and deep learning features (DLFs) extracted from both intra-thrombus and peri-thrombus regions on baseline CT in predicting prognosis following MT.

This retrospective, multicenter study included 471 AIS patients who underwent MT. Patients from Center A (n = 315) constituted the training cohort, while those from Center B and C (n = 156) served as an external test cohort. Thrombus regions were manually segmented, with a subsequent 1 mm expansion to define the peri-thrombus regions. A total of 428 radiomics features and 128 DLFs were extracted from non-contrast CT (NCCT) and CTA images. After feature selection, ten machine learning classifiers were employed to build prediction models. Combined models were developed based on two strategies including early feature-level fusion and late decision-level fusion. Model performance was evaluated using ROC analysis, DeLong test, NRI and IDI. Subgroup analyses were also performed.

A total of 191 patients (40.6%) achieved a favorable outcome (90-day mRS ≤ 2). In the test cohort, the late-fusion combined model achieved the highest discriminative performance (AUC = 0.836, 95% CI: 0.769-0.891). It significantly outperformed both the peri-thrombus model (AUC = 0.758, p = 0.005) and the early-fusion combined model (AUC = 0.763, p = 0.009). Compared with the intra-thrombus model, the late-fusion combined model also demonstrated improved reclassification, with an NRI of 0.935 and an IDI of 0.278. Subgroup analyses showed consistent discriminative performance of the late-fusion combined model across the prespecified subgroups.

The late-fusion combined model, integrating CT-derived radiomic and DLFs from both intra-thrombus and peri-thrombus regions, may provide an effective approach for predicting 90-day functional outcome after mechanical thrombectomy.

Spontaneous intracerebral hemorrhage (ICH) carries high early mortality and long-term disability; however, circulating biomarkers that capture both bleeding severity and prognosis are lacking. Neutrophil extracellular trap formation (NETosis), quantifiable in plasma as citrullinated histone H3 (H3Cit), cell-free DNA (cfDNA), and nucleosomes, is implicated in secondary brain injury after ICH.

Three hundred fifteen adults with first-ever spontaneous ICH within 24 h of onset and 160 community controls were enrolled. Plasma H3Cit, cfDNA and nucleosomes, admission hematoma volume, NIHSS, and GCS were recorded; the modified Rankin Scale (mRS) was assessed at 12 months. NETosis biomarkers entered linear, logistic, and Cox regressions as log2-transformed continuous variables and were adjusted progressively for time-to-sampling, demographics, vascular risk factors, surgical treatment, NIHSS, and hematoma volume. Incremental predictive value over a clinical baseline model was assessed using area under the receiver operating characteristic curve (AUC)/concordance index (C-index), continuous net reclassification improvement (NRI), and integrated discrimination improvement (IDI).

All three biomarkers were higher in ICH than controls (all p < 0.001) and were several-fold higher in 12-month decedents than survivors, despite no difference in absolute neutrophil count. After adjustment, H3Cit was independently associated with hematoma volume, NIHSS and GCS; cfDNA and nucleosomes were independently associated with hematoma volume. After full adjustment for demographics, vascular risk factors, surgical treatment, NIHSS, and hematoma volume, each doubling of H3Cit (OR: 1.577, 95% CI: 1.368-1.838), cfDNA (OR: 1.687, 95% CI: 1.259-2.291), and nucleosomes (OR: 1.622, 95% CI: 1.297-2.057) independently predicted 12-month mRS ≥ 3 (all p < 0.001); per doubling, H3Cit (HR: 1.358, 95% CI: 1.207-1.528), cfDNA (HR: 1.619, 95% CI: 1.287-2.038), and nucleosomes (HR: 1.568, 95% CI: 1.310-1.877) independently predicted 12-month death. Adding H3Cit raised the AUC for mRS ≥ 3 from 0.814 to 0.869 (ΔAUC: 0.055, p < 0.001) and the C-index for death from 0.765 to 0.818 (ΔC: 0.052, p < 0.001); for cfDNA and nucleosomes, the gains in discrimination were not significant, although NRI and IDI improved.

Plasma H3Cit, cfDNA, and nucleosomes within 24 h of ICH track hemorrhage severity and predict 12-month mRS ≥ 3 and death beyond established clinical scores, with H3Cit showing the most consistent incremental value.

Randomized trials favor direct oral anticoagulants (DOACs) over warfarin for eligible atrial fibrillation (AF), but whether cerebral microbleeds (CMBs) and anemia identify older patients with narrower benefit-harm margins remain uncertain. We estimated 2-year net clinical benefit (NCB) overall and by CMB/anemia strata.

This single-center, MRI-selected prospective observational cohort included patients aged ≥65 years with non-valvular AF receiving a DOAC or warfarin. Follow-up began at susceptibility MRI; CMB presence (0 vs ≥1) was rated by two blinded raters, and anemia used World Health Organization hemoglobin thresholds. DOAC-warfarin associations were estimated using propensity-score overlap weighting and competing-risk models for ischemic stroke/systemic embolism (IS/SE) and intracranial hemorrhage (ICH). Two-year NCB was expressed as net events prevented per 1000 with bootstrap 95% confidence intervals (CIs).

Among 797 patients (DOAC n=517; warfarin n=280), 31.0% had ≥1 CMB and 33.8% had anemia. During 2463 person-years, 40 first IS/SE events, 22 first ICH events, and 89 deaths occurred as first components of net adverse clinical events (NACE). After weighting, DOAC use was associated with lower NACE (2-year risk 14.9% vs 21.8%; hazard ratio 0.69, 95% CI 0.52-0.91), ICH (1.4% vs 4.3%; subdistribution hazard ratio 0.39, 95% CI 0.21-0.72), and IS/SE (3.9% vs 6.4%; subdistribution hazard ratio 0.63, 95% CI 0.41-0.96). Estimated NCB favored DOACs overall (67.0/1,000; 95% CI 28.4-102.7) and was attenuated in patients with both CMBs and anemia (38.0/1,000; 95% CI 4.2-71.5).

DOAC use was associated with a favorable estimated 2-year NCB vs warfarin in this MRI-selected cohort. Combined CMB/anemia findings are exploratory and hypothesis-generating and should not guide prescribing without multicenter validation.

Ambient air pollution poses substantial cardiovascular health and economic burdens worldwide, yet existing evidence largely focuses on high-pollution regions and clinical endpoints such as incidence or mortality. Few studies have quantified air pollution-attributable hospitalization costs for acute myocardial infarction (AMI), especially under low air quality conditions. Combined with China's Diagnosis-Related Groups (DRG) / Diagnosis-Intervention Packet (DIP) case-mix medical payment reform, hospitalization expenses can serve as a reliable proxy reflecting AMI disease severity and healthcare resource consumption, providing a unique health-economic perspective for environmental public health policy-making.

A single-center retrospective cohort study was conducted including 3,650 percutaneous coronary intervention (PCI)-treated AMI patients admitted to Jiangmen Central Hospital (2018-2024), a subtropical city with year-round air pollutant concentrations meeting China Grade II standards. Lag-stratified Gamma generalized linear models with log link were applied to evaluate associations between pre-admission 0-6 day exposure to six criteria pollutants (PM_2.5, PM₁₀, SO₂, NO₂, CO, O₃) and AMI hospitalization costs. All single-pollutant models were fully adjusted for demographics, comorbidities, seasons, weekdays, and non-linear meteorological confounders. Benjamini-Hochberg false discovery rate (FDR) correction was used to control multiple testing bias. A sensitivity analysis restricted to 1,590 never-smoking patients was performed.

Short-term exposure to SO₂, PM_2.5, PM₁₀, NO₂, and CO was significantly associated with elevated AMI medical expenditures, while O₃ showed no overall significant correlation. Per natural log-unit elevation, SO₂ generated the largest cost increase (average 2.40%, ~729 CNY) with consistent adverse effects across all lag days; particulate pollutants PM_2.5 and PM₁₀ exhibited delayed peak risks at lag 4-5 days. In never-smokers, O₃ triggered significant cost rises at lag 3 and lag 5, indicating non-smokers as vulnerable subgroups susceptible to ozone toxicity. Multicollinearity diagnostics validated the rationality of single-pollutant modeling.

Even low-level ambient air pollution compliant with current national standards increases the economic burden of AMI treatment, with SO₂ showing the strongest association. Smoking modifies cardiovascular cost-related effects of ozone. This population-level health-economic evidence supports stricter air quality regulations, and the integration of ambient exposure indicators into AMI risk stratification and public health resource allocation under the DRG/DIP payment system.

High-sensitivity C-reactive protein-triglyceride-glucose index (CTI) is an innovative biomarker of insulin resistance and inflammation. The objective of this study was to explore the association of high-sensitivity CTI with functional outcome in elderly patients with acute ischemic stroke (AIS) undergoing intravenous thrombolysis (IVT).

Elderly AIS patients treated with IVT were enrolled in three centers. Unfavorable functional outcome was defined as Modified Rankin Scale score ranging from 3-6. Logistic regression models were used to calculate the odds ratio (OR) and 95% confidence interval (95% CI) for the association between high-sensitivity CTI and 3-month functional outcome. Restricted cubic splines (RCS) were performed to explore the shape of this association. Receiver operating characteristic curve was applied to evaluate the discriminatory capacity of high-sensitivity CTI. Furthermore, subgroup and sensitivity analyses were performed to examine the consistency of the observed association.

A total of 708 elderly patients were enrolled, among whom 231 (32.6%) developed unfavorable functional outcome at 3 month follow up. In Model 3, higher continuous high sensitivity CTI levels were independently associated with 3 month unfavorable functional outcome among elderly AIS patients receiving IVT (OR = 1.64; 95% CI, 1.28-2.11). Taking the first quartile of high sensitivity CTI as the reference group, patients in the fourth quartile exhibited the highest risk of unfavorable functional outcome in Model 3 (OR = 2.62, 95% CI, 1.48-4.64). RCS revealed a significant overall association between high sensitivity CTI and unfavorable functional outcome, with no statistically significant nonlinear component (P for overall < 0.001; P for nonlinearity = 0.743). Subgroup and sensitivity analyses demonstrated consistent directions of associations.

High-sensitivity CTI was independently associated with functional outcome at 3 months in elderly AIS patients treated with IVT.

The main limitation of the National Institutes of Health Stroke Scale (NIHSS) is the underestimation of clinical severity in posterior circulation (PC) strokes, which has been hypothesized to contribute to diagnostic delay and to reduce eligibility for reperfusion treatments in some patients. We aimed to evaluate the diagnostic performance of a previously developed modified version of the NIHSS, the Expanded NIHSS (e-NIHSS), for clinical assessment and outcome prediction in patients with anterior circulation (AC) and PC strokes.

Prospective observational study of 249 consecutive stroke patients admitted to a Comprehensive Stroke Center during 1 year. NIHSS and e-NIHSS were administered by two independent examiners within 48 h of onset. The primary outcome measure was an unfavorable outcome, defined as a modified Rankin Scale score of 3 to 6 at 3 months. The discriminative performance of the e-NIHSS to predict unfavorable outcome was evaluated by calculating the area under the receiver operating characteristic curve (AUC-ROC).

The inter-rater reliability of the e-NIHSS between the two independent observers was excellent (intraclass correlation coefficient, 0.992 [95% CI 0.990-0.994]). The mean e-NIHSS score was higher than the mean classical NIHSS score (p < 0.001). An unfavourable outcome at 3 months was detected in 113 (45%) patients. The e-NIHSS showed a discriminative performance to predict unfavorable functional outcome comparable to the classical NIHSS for the total amount of strokes (AUC-ROC of the e-NIHSS for the first observer, 0.867 [95% CI, 0.823-0.911]; AUC-ROC of the e-NIHSS for the second observer, 0.871 [95% CI, 0.827-0.914]; AUC-ROC of the classical NIHSS, 0.849 [95% CI, 0.802-0.897]), AC strokes (AUC-ROC of the e-NIHSS for the first observer, 0.886 [95% CI, 0.841-0.932]; AUC-ROC of the e-NIHSS for the second observer, 0.892 [95% CI, 0.848-0.936]; AUC-ROC of the classical NIHSS, 0.870 [95% CI, 0.821-0.920]), and PC strokes (AUC-ROC of the e-NIHSS for the first observer, 0.800 [95% CI, 0.685-0.916]; AUC-ROC of the e-NIHSS for the second observer, 0.791 [95% CI, 0.672-0.910]; AUC-ROC of the classical NIHSS, 0.804 [95% CI, 0.689-0.920]). Net reclassification improvement, integrated discrimination improvement, and decision curve analysis showed a modest apparent incremental prognostic benefit of the e-NIHSS over the classical NIHSS in the whole cohort and in AC strokes, but not in PC strokes.

Compared to the classical NIHSS, the e-NIHSS showed a similar discriminative performance to predict 3-month functional outcome, capturing and quantifying additional PC-relevant clinical signs not fully represented in the classical NIHSS, with excellent inter-rater reliability.

This study aimed to identify the distribution of orthostatic hypotension (OH) according to changes in internal carotid artery (ICA) blood flow in patients with cervical spinal cord injury (SCI), and to determine whether cognitive impairment is more prominent among patients with a certain level of ICA blood flow reduction.

Forty-one patients diagnosed with cervical SCI were retrospectively analyzed and classified into two groups based on the results of a head-up tilt test and carotid duplex ultrasonography to measure ICA blood flow: those with a reduction of 21% or more (n = 26) and those without such a reduction (n = 15). Cognitive function tests were compared between the two groups.

Patients with an ICA blood flow reduction of 21% or greater demonstrated significantly lower cognitive scores than those without such a reduction (K-MMSE p = 0.028, MoCA-K p = 0.048; Hedges' g = -0.65 for both). In multivariable regression adjusted for age, sex, and education, greater ICA blood flow reduction remained associated with lower scores on both instruments (p = 0.038 and p = 0.033). Among 13 cognitive subdomains, only language and visuospatial construction remained significantly lower after correction for multiple comparisons.

This study suggests that the early assessment of ICA blood flow and cognitive function may be informative in the rehabilitation process for patients with cervical SCI. Whether such assessment can help identify patients who should be prioritized for formal cognitive assessment requires prospective evaluation.

Aging is a systemic decline in physiological integrity, driving chronic diseases such as neurodegeneration, cardiovascular disorders, and metabolic syndromes. Rapid global population aging urgently demands effective interventions. Traditional Chinese medicine (TCM) formulas, characterized by multi-component, multi-target, and multi-pathway synergy, offer a promising paradigm for delaying aging. This review systematically integrates recent advances in TCM formula-based anti-aging research, bridging classical TCM gerontology with the 14 modern hallmarks of aging. We categorize representative formulas into four mechanistic groups targeting mitochondrial homeostasis and autophagy, cellular senescence and inflammatory microenvironment, stem cell maintenance and epigenetic reprogramming, and gut microbiota and systemic metabolism, and explore their holistic efficacy, key bioactive constituents, and multi-component synergy. In terms of methodological innovations, we introduced network pharmacology combined with AI-driven target screening and proteomic aging clocks to assess biological age. We discussed challenges in chemical complexity, mechanistic completeness, and clinical translation, and proposed a roadmap for development. This review establishes an integrative model that integrates TCM principles with modern aging biology, offering insights for translational research toward healthy longevity.

To investigate the natural course of cerebral small vessel disease (CSVD) manifested as pure thalamic infarction (PTI) and identify predictors of 90-day clinical prognosis and 1-year recurrent major adverse cardiovascular/cerebrovascular events (MACE).

This retrospective cohort study analyzed 251 consecutive thalamic infarction patients admitted between January 2016 and May 2024. Participants were classified into PTI (n = 187) or combined-type thalamic infarction (CTI, n = 64). Primary endpoints included poor 90-day clinical prognosis (modified Rankin Scale [mRS] ≥ 2) and 1-year MACE (composite of stroke, acute myocardial infarction, and cardiovascular death). Intergroup comparisons utilized Pearson Chi-square or Mann-Whitney U tests, with variables showing p ≤ 0.10 in univariate analysis entered into multivariate logistic regression models.

Compared with CTI, PTI patients demonstrated lower baseline National Institutes of Health Stroke Scale (NIHSS) scores (median 1 vs. 3, p < 0.001) and reduced prevalence of atrial fibrillation (2.7% vs. 12.5%), intracranial artery stenosis (ICAS; 48.1% vs. 76.6%), and early neurological deterioration (24.6% vs. 56.3%; all p < 0.05). The 90-day poor prognosis rate was significantly lower in PTI (4.8% vs. 20.3%, p < 0.001), whereas 1-year MACE rates did not differ between groups (12.3% vs. 15.6%, p = 0.497). Among PTI cases, territorial distributions comprised inferolateral (80.2%), tuberothalamic (13.4%), paramedian (including Percheron artery, 5.9%), and posterior choroidal arteries (0.5%). Tuberothalamic artery infarctions exhibited higher cognitive impairment rates (36.0%) than other subgroups. Multivariate analysis identified baseline NIHSS as an independent predictor of 90-day poor prognosis (OR = 1.634, 95% CI 1.152-2.320, p = 0.006), while ICAS was associated with 1-year MACE (OR = 3.908; 95% CI, 1.188-12.849; p = 0.025) in PTI patients.

PTI presented favorable short-term outcomes, consistent with initial stroke severity, yet carried a 12.3% annual MACE risk, particularly in patients with coexisting ICAS. These findings underscore the importance of addressing intracranial stenosis in secondary prevention strategies for CSVD.