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Background and Purpose: Predicting poor outcome for stroke patients with chronic kidney disease (CKD) in clinical practice is difficult. There are no tools available to use for predicting poor outcome in these patients. We aimed to construct and validate a dynamic nomogram to identify CKD-stroke patients at high risk of a 3-month poor outcome., Patients and Methods: We used data for 502 CKD patients who had an acute ischemic stroke, from Nanjing First Hospital, between September 2014 and September 2020, to train the nomogram. An additional 108 patients enrolled from October 2020 to May 2021 were used for temporal external validation. The performance of the nomogram was evaluated by the area under the receiver operating characteristics curve (AUC) and a calibration plot. The clinical utility of the nomogram was measured by decision curve analysis (DCA) and the clinical impact curve (CIC)., Results: The median age of the cohort was 79 (70-84) years. Age, urea, premorbid modified Rankin Scale (mRS), National Institutes of Health Stroke Scale (NIHSS) on admission, hemiplegia, mechanical thrombectomy, early neurological deterioration, and respiratory infection were used as predictors of 3-month poor outcome to develop the nomogram. In the training set, the AUC of the dynamic nomogram was 0.873 and the calibration plot showed good predictive ability, and both DCA and CIC indicated the excellent clinical usefulness and applicability of the nomogram. In the external validation set, the AUC was 0.875 and the calibration plot also showed good agreement., Conclusion: This is the first dynamic nomogram constructed for CKD-stroke patients to precisely and expediently identify patients with a high risk of 3-month poor outcome. The outstanding performance and great clinical predictive utility demonstrated the ability of the dynamic nomogram to help clinicians to deploy preventive interventions., Competing Interests: The authors report no conflicts of interest in this work., (© 2022 Wang et al.)

Background: Selecting best candidates for prolonged poststroke cardiac monitoring in acute ischemic stroke (AIS) patients is still challenging. We aimed to develop a machine learning (ML) model to select AIS patients at high risk of poststroke atrial fibrillation (AF) for prolonged cardiac monitoring and then to compare ML model with traditional risk scores and classic statistical logistic regression (classic-LR) model., Methods: AIS patients from July 2012 to September 2020 across Nanjing First Hospital were collected. We performed the LASSO regression for selecting the critical features and built five ML models to assess the risk of poststroke AF. The SHAP and partial dependence plot (PDP) method were introduced to interpret the optimal model. We also compared ML model with CHADS 2 score, CHA 2 DS 2 -VASc score, AS5F score, HAVOC score, and classic-LR model., Results: A total of 3929 AIS patients were included. Among the five ML models, deep neural network (DNN) was the model with best performance. It also exhibited superior performance compared with CHADS 2 score, CHA 2 DS 2 -VASc score, AS5F score, HAVOC score and classic-LR model. The results of SHAP and PDP method revealed age, cardioembolic stroke, large-artery atherosclerosis stroke, and NIHSS score at admission were the top four important features and revealed the DNN model had good interpretability and reliability., Conclusion: The DNN model achieved best performance and improved prediction performance compared with traditional risk scores and classic-LR model. The DNN model can be applied to identify AIS patients at high risk of poststroke AF as best candidates for prolonged poststroke cardiac monitoring., (Copyright © 2021 Elsevier B.V. All rights reserved.)

Stroke induces disorder of gut microbiota, however, whether this disorder differs according to stroke severity and its role in the evolution and outcome of stroke is currently unknown. Here we explored the composition and structure of fecal microbiome based on 68 acute ischemic stroke patients presenting with minor symptoms (admission National Institute of Health Stroke Scale (NIHSS) ≤ 3) and 67 patients with non-minor stroke (admission NIHSS 4-34) using high-throughput Illumina sequencing of the 16S rRNA. There was no significant difference in α-diversity indices, but the principal coordinate analysis of the microbiota indicated clear separation of the two groups. The significantly enriched butyrate-producing genus Roseburia in the minor stroke group was negatively correlated with fasting glucose, while the Erysipelotrichaceae incertae sedis abundant in non-minor stroke patients was positively correlated with stress hyperglycemia (i.e. fasting glucose/glycated hemoglobin ratio). Moreover, the relative abundance of genus Roseburia was also significantly associated with the dynamic changes of NIHSS score, as well as short-term and long-term functional outcomes. Our results suggested that stroke affects microbiota composition in a manner differentiated by stroke severity, and the enrichment of genus Roseburia may play a protective role in stroke evolution and outcome. Our findings strengthen the relevance of specific taxa for stroke severity that might allow targeted therapy in acute ischemic stroke., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Gu, Chen, Sun, Li, Chen, Zhou and Zhang.)

Introduction: Concern over the potential severe bleeding risk of dual antiplatelet therapy for patients with minor stroke after intravenous thrombolysis (IVT) leads to different antiplatelet strategies in the secondary prevention of stroke. Our aim was to investigate the effect of dual antiplatelet therapy on patients with minor ischemic stroke receiving IVT. Methods: From November 2016 to April 2021, a total of 855 consecutive patients who received IVT were observed. We collected and analyzed demographic characteristics, medical history, clinical information, and important time metrics of patients with minor ischemic stroke. Comparative and multivariate logistic regression analyses were used to explore the clinical significance of single or dual antiplatelet therapy after IVT. Propensity score matching analyses (1:1 matching including baseline characteristics of patients) were also performed. Results: A total of 245 patients were enrolled in the study (118 patients in the single antiplatelet therapy group and 127 patients in the dual antiplatelet group). No significant difference was found in baseline characteristics except stroke etiology (p < 0.001) for patients with minor stroke. The dual antiplatelet group showed a higher proportion of 90-day modified Rankin Scale (mRS) (0–1) than the single antiplatelet group (p = 0.030). Furthermore, patients receiving dual antiplatelet therapy had excellent outcomes (90-day mRS 0–1) after adjustment (odds ratio [ OR ] 2.76, 95% CI 1.27–6.01, p = 0.010). Other secondary outcomes (recurrent stroke within 90 days, symptomatic intracerebral hemorrhage, and early neurological deterioration) were not significantly different between the two groups. These findings were generally consistent in propensity score analyses. Conclusions: Dual antiplatelet therapy may be a potential therapeutic approach in patients with minor stroke receiving IVT. Further randomized controlled trials are required to confirm this finding. [ABSTRACT FROM AUTHOR]

Background: Fluid-attenuated inversion recovery vascular hyperintensity (FVH) can reflect the collateral status, which may be a valuable indicator to predict the functional outcome of acute stroke (AS) patients. Methods: A total of 190 AS patients with large vessel occlusion (LVO) were retrospectively investigated. All patients completed a 6-month follow-up and their modified Rankin Scale (mRS) scores were recorded at 1, 3, and 6 months after intravenous thrombolysis (IVT). Based on their mRS at 3 months, patients were divided into two groups: poor prognosis (131 patients; 68.9% of all subjects) and favorable prognosis (59 patients; 31.1% of all subjects). The death records of 28 patients were also analyzed in the poor prognosis group. Results: (1) Univariate and multivariate analyses showed that the higher National Institutes of Health Stroke Scale (NIHSS) score at admission, higher fasting blood glucose, and lower FVH score were independent risk factors to predict the poor prognosis of IVT. (2) Survival analysis indicated that FVH score was the only baseline factor to predict the 6-month survival after IVT. (3) Baseline FVH score had great prediction performance for the prognosis of IVT (area under the curve = 0.853). (4) Baseline FVH score were negatively correlated with the NIHSS score at discharge and mRS score at 1, 3, and 6 months. Conclusion: Among various baseline clinical factors, only the FVH score might have implications for 3-month outcome and 6-month survival of AS patients after IVT. Baseline FVH score showed great potential to predict the prognosis of the AS patients. [ABSTRACT FROM AUTHOR]