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Background: The role of brain atrophy in cognitive decline related to cerebral small vessel disease (CSVD) remains unclear. This study used AccuBrain™ to identify major CSVD-related brain changes and verified the relationship between brain atrophy and different cognition domains in CSVD patients. Methods: All enrolled 242 CSVD patients and 76 healthy participants underwent magnetic resonance imaging examinations and detailed neuropsychological scale assessments were collected at the same time. The AccuBrain™ technology was applied to fully automated image segmentation, measurement, and calculation of the acquired imaging results to obtain the volumes of different brain partitions and the volume of WMH for quantitative analysis. Correlation analyses were used to estimate the relationship between MRI features and different cognitive domains. Multifactor linear regression models were performed to analyze independent predictors of MTA and cognitive decline. Results: CSVD patients exhibited multiple gray matter nucleus volume decreases in the basal ganglia regions and brain lobes, including the temporal lobe (P = 0.019), especially in the medial temporal lobe (p < 0.001), parietal lobe (p = 0.013), and cingulate lobe (p = 0.036) compare to HC. The volume of PWMH was an independent predictor of MTA for CSVD patients. Both medial temporal atrophy (MTA) and PWMH were associated with cognition impairment in CSVD-CI patients. MTA mediated the effect of PWMH on executive function in CSVD-CI patients. Conclusions: Our results showed that MTA was related to cognition impairment in CSVD patients, which might become a potential imaging marker for CSVD-CI. [ABSTRACT FROM AUTHOR]

Aims: We aimed to determine whether preprocedural renal function affects the outcome of acute ischemic stroke (AIS) patients with mechanical thrombectomy (MT) and whether this effect is modified by the onset‐to‐reperfusion time (OTR) and mediated by collateral status. Methods: Eligible patients with anterior circulation large vessel occlusion (LVO) who underwent MT between August 2018 and August 2020 were reviewed. The main outcome was good functional outcome [defined as modified Rankin Scale (mRS) of 0–2] at 3 months. Multivariable logistic regression analyses were conducted to explore the relationship between renal function and good functional outcome. A moderation analysis and the Johnson‐Neyman technique were performed to assess the interaction between renal function and OTR to predict the outcome of AIS patients with MT. Results: Among 100 enrolled patients, 36 (36%) exhibited good functional outcome. A decreased preprocedural estimated glomerular filtration rate (pre‐eGFR) was significantly associated with worse functional outcome [adjusted OR, 1.059 (1.012–1.108); p, 0.014], and this effect was partly mediated by collateral circulation. An interaction between OTR and pre‐eGFR on functional outcome was observed (P for interaction, 0.22), and pre‐eGFR only had a significant effect on functional outcome when OTR exceeded 455.8 min. Moreover, the adverse effect of OTR on functional outcome became no longer significant when the pre‐eGFR was higher than 89.0 mL/min/1.73 mL/min/1.73 m². Conclusions: Renal function was related to functional outcome at 3 months, and this relationship could be modified by OTR. The results suggested that reducing OTR and improving collateral circulation may mitigate the adverse effect of reduced kidney function on functional outcome. [ABSTRACT FROM AUTHOR]

Background: There is high variability in the clinical outcomes of patients with acute ischemic stroke (AIS) after mechanical thrombectomy (MT)., Methods: 217 consecutive patients with anterior circulation large vessel occlusion who underwent MT between August 2018 and January 2022 were analysed. The primary outcome was functional independence defined as a modified Rankin Scale score of 0-2 at 3 months. In the derivation cohort (August 2018 to December 2020), 7 ensemble ML models were trained on 70% of patients and tested on the remaining 30%. The model's performance was further validated on the temporal validation cohort (January 2021 to January 2022). The SHapley Additive exPlanations (SHAP) framework was applied to interpret the prediction model., Results: Derivation analyses generated a 9-item score (PFCML-MT) comprising age, National Institutes of Health Stroke Scale score, collateral status, and postoperative laboratory indices (albumin-to-globulin ratio, estimated glomerular filtration rate, blood neutrophil count, C-reactive protein, albumin and serum glucose levels). The area under the curve was 0.87 for the test set and 0.84 for the temporal validation cohort. SHAP analysis further determined the thresholds for the top continuous features. This model has been translated into an online calculator that is freely available to the public (https://zhelvyao-123-60-sial5s.streamlitapp.com)., Conclusions: Using ML and readily available features, we developed an ML model that can potentially be used in clinical practice to generate real-time, accurate predictions of the outcome of patients with AIS treated with MT., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2023. Re-use permitted under CC BY. Published by BMJ.)