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Background: Edaravone dexborneol has been reported as an effective neuroprotective agent in the treatment of acute ischemic stroke (AIS). This study aimed at investigating the impact of edaravone dexborneol on functional outcomes and systematic inflammatory response in AIS patient. Methods: All participants were recruited from the AISRNA study (registered 21/11/2019, NCT04175691 [ClinicalTrials.gov]) between January 2022 and December 2022. The AIS patients were divided into two groups based on whether they received the treatment of edaravone dexborneol (37.5 mg/12 hours, IV) within 48 h after stroke onset. Inflammatory response was determined by detecting levels of cytokines (interleukin-2 [IL-2], IL-4, IL-5, IL-8, IL-6, IL-10, IL-12p70, IL-17, tumor necrosis factor-α [TNF-α], interferon-γ [IFN-γ], IFN-α, and IL-1β) within 14 days after stroke onset. Results: Eighty-five AIS patients were included from the AISRNA study. Patients treated with edaravone dexborneol showed a significantly higher proportion of modified Rankin Scale score < 2 compared to those who did not receive this treatment (70.7% versus 47.8%; P = 0.031). Furthermore, individuals receiving edaravone dexborneol injection exhibited lower expression levels of interleukin (IL)-1β, IL-6, and IL-17, along with higher levels of IL-4 and IL-10 expression during the acute phase of ischemic stroke (P < 0.05). These trends were not observed for IL-2, IL-5, IL-8, IL-12p70, tumor necrosis factor-α, interferon-γ [IFN-γ], and IFN-α (P > 0.05). Conclusions: Treatment with edaravone dexborneol resulted in a favorable functional outcome at 90 days post-stroke onset when compared to patients without this intervention; it also suppressed proinflammatory factors expression while increasing anti-inflammatory factors levels. Trial registration: ClinicalTrials.gov NCT04175691. Registered November 21, 2019, https://www.clinicaltrials.gov/ct2/show/NCT04175691. [ABSTRACT FROM AUTHOR]

Introduction: Whether time window affects the intravenous thrombolysis (IVT) effect before endovascular thrombectomy (EVT) is uncertain. We aimed to investigate the effect of different time windows (0–3 h and >3–4.5 h from stroke onset to randomization) on clinical outcomes of EVT with or without IVT in a subgroup analysis of DIRECT-MT. Methods: The primary outcome was the 90-day modified Rankin Scale (mRS) according to time window. Logistic regression models were used to analyze the effect of different treatments (EVT with or without IVT) on outcomes within 0–3 h or >3–4.5 h. Results: Among 656 patients who were included in the analysis, 282 (43.0%) were randomized within >3–4.5 h after stroke onset (125 without IVT and 157 with IVT), and 374 (57.0%) were randomized within 0–3 h (202 without IVT and 172 with IVT). We noted no significant difference in the thrombectomy-alone effect between the time window subgroups according to 90-day ordinal mRS (adjusted common odds ratio [acOR] in patients within 0–3 h: 1.06 [95% CI: 0.73–1.52], acOR in patients within >3–4.5 h: 1.19 [95% CI: 0.78–1.82]) and 90-day functional independence. Thrombectomy alone resulted in an increased proportion of patients with 90-day mRS 0–3 treated within >3–4.5 h (62.90 vs. 48.72%) but not within 0–3 h (65.84 vs. 63.95%). However, there was no interaction effect regarding all outcomes after the Bonferroni correction. Conclusions: Our results did not support thrombectomy-alone administration within 3–4.5 h in patients with acute ischemic stroke from large-vessel occlusion in the subgroup analysis of DIRECT-MT. [ABSTRACT FROM AUTHOR]

Early neurologic deterioration (END) is a common and feared complication for acute ischemic stroke (AIS) patients treated with mechanical thrombectomy (MT). This study aimed to develop an interpretable machine learning (ML) model for individualized prediction to predict END in AIS patients treated with MT. The retrospective cohort of AIS patients who underwent MT was from two hospitals. ML methods applied include logistic regression (LR), random forest (RF), support vector machine (SVM), and extreme gradient boosting (XGBoost). The area under the receiver operating characteristic curve (AUC) was the main evaluation metric used. We also used Shapley Additive Explanation (SHAP) and Local Interpretable Model-Agnostic Explanations (LIME) to interpret the result of the prediction model. A total of 985 patients were enrolled in this study, and the development of END was noted in 157 patients (15.9%). Among the used models, XGBoost had the highest prediction power (AUC = 0.826, 95% CI 0.781–0.871). The Delong test and calibration curve indicated that XGBoost significantly surpassed those of the other models in prediction. In addition, the AUC in the validating set was 0.846, which showed a good performance of the XGBoost. The SHAP method revealed that blood glucose was the most important predictor variable. The constructed interpretable ML model can be used to predict the risk probability of END after MT in AIS patients. It may help clinical decision making in the perioperative period of AIS patients treated with MT. [ABSTRACT FROM AUTHOR]

Background: Hyperglycaemia is thought to be connected to worse functional outcomes after ischaemic stroke. However, the association between hyperglycaemia and acute kidney injury (AKI) after endovascular treatment (EVT) remains elusive. The purpose of this study was to investigate the influence of glycaemic on AKI after EVT. Methods: We retrospectively collected the clinical information of patients who underwent EVT from April 2015 to August 2021. Blood glucose after EVT was recorded as acute glycaemia. Chronic glucose levels were estimated by glycosylated haemoglobin (HbA1c) using the following formula: chronic glucose levels (mg/dL) = 28.7 × HbA1c (%) − 46.7. AKI was defined as an increase in maximum serum creatinine to ≥1.5 baseline. We evaluated the association of AKI with blood glucose. A nomogram was established to predict the risk of AKI, and its diagnostic efficiency was determined by decision curve analysis. Results: We enrolled 717 acute ischaemic stroke patients who underwent EVT. Of them, 205 (28.6%) experienced AKI. Acute glycaemia (OR: 1.007, 95% CI: 1.003–1.011, p < 0.001), the acute/chronic glycaemic ratio (OR: 4.455, 95% CI: 2.237–8.871, p < 0.001) and the difference between acute and chronic glycaemia (ΔA-C) (OR: 1.008, 95% CI: 1.004–1.013, p < 0.001) were associated with the incidence of AKI. Additionally, age, atrial fibrillation, ASITN/SIR collateral grading, postoperative mTICI scale, and admission NIHSS were also significantly correlated with AKI. We then created a glycaemia-based nomogram, and its concordance index was 0.743. The net benefit of the nomogram was further confirmed by decision curve analysis. Conclusions: The glycaemia-based nomogram may be used to predict AKI in ischaemic stroke patients receiving EVT. [ABSTRACT FROM AUTHOR]

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 and purpose: To investigate the association of neutrophil to lymphocyte ratio (NLR), platelet to lymphocyte ratio (PLR), and lymphocyte to monocyte ratio (LMR) with post-thrombolysis early neurological outcomes including early neurological improvement (ENI) and early neurological deterioration (END) in patients with acute ischemic stroke (AIS). Methods: AIS patients undergoing intravenous thrombolysis were enrolled from April 2016 to September 2019. Blood cell counts were sampled before thrombolysis. Post-thrombolysis END was defined as the National Institutes of Health Stroke Scale (NIHSS) score increase of ≥ 4 within 24 h after thrombolysis. Post-thrombolysis ENI was defined as NIHSS score decrease of ≥ 4 or complete recovery within 24 h. Multinomial logistic regression analysis was performed to explore the relationship of NLR, PLR, and LMR to post-thrombolysis END and ENI. We also used receiver operating characteristic curve analysis to assess the discriminative ability of three ratios in predicting END and ENI. Results: Among 1060 recruited patients, a total of 193 (18.2%) were diagnosed with END and 398 (37.5%) were diagnosed with ENI. Multinomial logistic model indicated that NLR (odds ratio [OR], 1.385; 95% confidence interval [CI] 1.238–1.551, P = 0.001), PLR (OR, 1.013; 95% CI 1.009–1.016, P = 0.001), and LMR (OR, 0.680; 95% CI 0.560–0.825, P = 0.001) were independent factors for post-thrombolysis END. Moreover, NLR (OR, 0.713; 95% CI 0.643–0.791, P = 0.001) served as an independent factor for post-thrombolysis ENI. Area under curve (AUC) of NLR, PLR, and LMR to discriminate END were 0.763, 0.703, and 0.551, respectively. AUC of NLR, PLR, and LMR to discriminate ENI were 0.695, 0.530, and 0.547, respectively. Conclusions: NLR, PLR, and LMR were associated with post-thrombolysis END. NLR and PLR may predict post-thrombolysis END. NLR was related to post-thrombolysis ENI. [ABSTRACT FROM AUTHOR]