Neuroinflammation in hemorrhagic transformation after tissue plasminogen activator thrombolysis: Potential mechanisms, targets, therapeutic drugs and biomarkers

Ma, Guodong; Pan, Zirong; Kong, Ling-Lei; Du, Guanhua

doi:10.1016/j.intimp.2020.107216

Cited by 35 publications

(14 citation statements)

References 215 publications

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“…Neuroinflammation is related to the entire pathological process of stroke. The NLR is a readily accessible and reproduces new inflammatory biomarker ( 41 ). It was reported that a high NLR (≥4.255) on admission increases the risk of ICH in patients with AIS after IVT ( 42 ).…”

Section: Discussionmentioning

confidence: 99%

A New Nomogram for Predicting the Risk of Intracranial Hemorrhage in Acute Ischemic Stroke Patients After Intravenous Thrombolysis

et al. 2022

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BackgroundWe aimed to develop and validate a new nomogram for predicting the risk of intracranial hemorrhage (ICH) in patients with acute ischemic stroke (AIS) after intravenous thrombolysis (IVT).MethodsA retrospective study enrolled 553 patients with AIS treated with IVT. The patients were randomly divided into two cohorts: the training set (70%, n = 387) and the testing set (30%, n = 166). The factors in the predictive nomogram were filtered using multivariable logistic regression analysis. The performance of the nomogram was assessed based on the area under the receiver operating characteristic curve (AUC-ROC), calibration plots, and decision curve analysis (DCA).ResultsAfter multivariable logistic regression analysis, certain factors, such as smoking, National Institutes of Health of Stroke Scale (NIHSS) score, blood urea nitrogen-to-creatinine ratio (BUN/Cr), and neutrophil-to-lymphocyte ratio (NLR), were found to be independent predictors of ICH and were used to construct a nomogram. The AUC-ROC values of the nomogram were 0.887 (95% CI: 0.842–0.933) and 0.776 (95% CI: 0.681–0.872) in the training and testing sets, respectively. The AUC-ROC of the nomogram was higher than that of the Multicenter Stroke Survey (MSS), Glucose, Race, Age, Sex, Systolic blood Pressure, and Severity of stroke (GRASPS), and stroke prognostication using age and NIH Stroke Scale-100 positive index (SPAN-100) scores for predicting ICH in both the training and testing sets (p < 0.05). The calibration plot demonstrated good agreement in both the training and testing sets. DCA indicated that the nomogram was clinically useful.ConclusionsThe new nomogram, which included smoking, NIHSS, BUN/Cr, and NLR as variables, had the potential for predicting the risk of ICH in patients with AIS after IVT.

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Section: Discussionmentioning

confidence: 99%

A New Nomogram for Predicting the Risk of Intracranial Hemorrhage in Acute Ischemic Stroke Patients After Intravenous Thrombolysis

et al. 2022

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“…Neutrophils plays a role in the disruption of the blood brain barrier (BBB) through inflammation (30,31) and enhance the expression of matrix metalloproteinase-9 (MMP-9) (32). Rt-PA can not only promote neutrophils to release MMPs but also promote the migration of neutrophils to ischemic tissue (33). Moreover, the stress response leads to an increase in the production of catecholamines in an overactivated sympathetic nervous system, resulting in a decrease in the number and activity of lymphocytes (34).…”

Section: Discussionmentioning

confidence: 99%

Machine Learning-Based Model for Prediction of Hemorrhage Transformation in Acute Ischemic Stroke After Alteplase

Li²,

Wu³

et al. 2022

Front. Neurol.

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Hemorrhage transformation (HT) is the most dreaded complication of intravenous thrombolysis (IVT) in acute ischemic stroke (AIS). The prediction of HT after IVT is important in the treatment decision-making for AIS. We designed and compared different machine learning methods, capable of predicting HT in AIS after IVT. A total of 345 AIS patients who received intravenous alteplase between January 2016 and June 2021 were enrolled in this retrospective study. The demographic characteristics, clinical condition, biochemical data, and neuroimaging variables were included for analysis. HT was confirmed by head computed tomography (CT) or magnetic resonance imaging (MRI) within 48 h after IVT. Based on the neuroimaging results, all of the patients were divided into the non-HT group and the HT group. Then, the variables were applied in logistic regression (LR) and random forest (RF) algorithms to establish HT prediction models. To evaluate the accuracy of the machine learning models, the models were compared to several of the common scales used in clinics, including the multicenter stroke survey (MSS) score, safe implementation of treatments in stroke (SITS) score, and SEDAN score. The performance of these prediction models was evaluated using the receiver operating characteristic (ROC) curve (AUC). Forty-five patients had HT (13.0%) within 48 h after IVT. The ROC curve results showed that the AUCs of HT that were predicted by the RF model, LR model, MSS, SITS, and SEDAN scales after IVT were 0.795 (95% CI, 0.647–0.944), 0.703 (95% CI, 0.515–0.892), 0.657 (95% CI, 0.574–0.741), 0.660 (95% CI, 0.580–0.740) and 0.655 (95% CI, 0.571–0.739), respectively. The RF model performed better than the other models and scales. The top four most influential factors in the RF importance matrix plot were triglyceride, Lpa, the baseline NIHSS, and hemoglobin. The SHapley Additive exPlanation values made the RF prediction model clinically interpretable. In this study, an RF machine learning method was successfully established to predict HT in AIS patients after intravenous alteplase, which the sensitivity was 66.7%, and the specificity was 80.7%.

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“…Ischemic stress-induced DAMP/TLR4/NF-κB pathway activation upregulates the expression and activation of MMPs. MMP-9 can strongly degrade tight junction proteins and the basement membrane, thereby aggravating BBB damage and the propensity for HT that is associated with ischemic brain injury and thrombolytic therapy [ 42 ]. The MMP-9 inhibitor BB-94 effectively decreased tPA-induced hemorrhagic volume and rate in cerebral ischemic animals [ 43 , 44 ].…”

Section: Discussionmentioning

confidence: 99%

Phthalide derivative CD21 attenuates tissue plasminogen activator-induced hemorrhagic transformation in ischemic stroke by enhancing macrophage scavenger receptor 1-mediated DAMP (peroxiredoxin 1) clearance

Liu

Hong

et al. 2021

J Neuroinflammation

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Background Hemorrhagic transformation (HT) is a critical issue in thrombolytic therapy in acute ischemic stroke. Damage-associated molecular pattern (DAMP)-stimulated sterile neuroinflammation plays a crucial role in the development of thrombolysis-associated HT. Our previous study showed that the phthalide derivative CD21 attenuated neuroinflammation and brain injury in rodent models of ischemic stroke. The present study explored the effects and underlying mechanism of action of CD21 on tissue plasminogen activator (tPA)-induced HT in a mouse model of transient middle cerebral artery occlusion (tMCAO) and cultured primary microglial cells. Methods The tMCAO model was induced by 2 h occlusion of the left middle cerebral artery with polylysine-coated sutures in wildtype (WT) mice and macrophage scavenger receptor 1 knockout (MSR1−/−) mice. At the onset of reperfusion, tPA (10 mg/kg) was intravenously administered within 30 min, followed by an intravenous injection of CD21 (13.79 mg/kg/day). Neuropathological changes were detected in mice 3 days after surgery. The effect of CD21 on phagocytosis of the DAMP peroxiredoxin 1 (Prx1) in lysosomes was observed in cultured primary microglial cells from brain tissues of WT and MSR1−/− mice. Results Seventy-two hours after brain ischemia, CD21 significantly attenuated neurobehavioral dysfunction and infarct volume. The tPA-infused group exhibited more severe brain dysfunction and hemorrhage. Compared with tPA alone, combined treatment with tPA and CD21 significantly attenuated ischemic brain injury and hemorrhage. Combined treatment significantly decreased Evans blue extravasation, matrix metalloproteinase 9 expression and activity, extracellular Prx1 content, proinflammatory cytokine mRNA levels, glial cells, and Toll-like receptor 4 (TLR4)/nuclear factor κB (NF-κB) pathway activation and increased the expression of tight junction proteins (zonula occludens-1 and claudin-5), V-maf musculoaponeurotic fibrosarcoma oncogene homolog B, and MSR1. MSR1 knockout significantly abolished the protective effect of CD21 against tPA-induced HT in tMCAO mice. Moreover, the CD21-induced phagocytosis of Prx1 was MSR1-dependent in cultured primary microglial cells from WT and MSR1−/− mice, respectively. Conclusion The phthalide derivative CD21 attenuated tPA-induced HT in acute ischemic stroke by promoting MSR1-induced DAMP (Prx1) clearance and inhibition of the TLR4/NF-κB pathway and neuroinflammation.

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Neuroinflammation in hemorrhagic transformation after tissue plasminogen activator thrombolysis: Potential mechanisms, targets, therapeutic drugs and biomarkers

Cited by 35 publications

References 215 publications

A New Nomogram for Predicting the Risk of Intracranial Hemorrhage in Acute Ischemic Stroke Patients After Intravenous Thrombolysis

A New Nomogram for Predicting the Risk of Intracranial Hemorrhage in Acute Ischemic Stroke Patients After Intravenous Thrombolysis

Machine Learning-Based Model for Prediction of Hemorrhage Transformation in Acute Ischemic Stroke After Alteplase

Phthalide derivative CD21 attenuates tissue plasminogen activator-induced hemorrhagic transformation in ischemic stroke by enhancing macrophage scavenger receptor 1-mediated DAMP (peroxiredoxin 1) clearance

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