N-Terminal Pro-brain Natriuretic Peptide Is Associated With Hemorrhagic Transformation and Poor Outcomes in Patients With Stroke Treated With Intravenous Thrombolysis

Zhang, Kejia; Jin, Hang; Xu, Rui; Zhang, Peng; Guo, Zhen‐Ni; Yang, Yi

doi:10.3389/fnmol.2021.758915

Cited by 9 publications

(9 citation statements)

References 35 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Finally, NT-proBNP is an inactive fragment derived from the cleavage of BNP [ 35 ]. In line with earlier studies [ 36 – 38 ], our findings showed that NT-proBNP level was independently associated with HT in patients with stroke who had received IVT. One possible explanation was that HT exacerbated the brain damage caused by ischemic stroke [ 39 ].…”

Section: Discussionsupporting

confidence: 93%

A clinical–radiomics model based on noncontrast computed tomography to predict hemorrhagic transformation after stroke by machine learning: a multicenter study

et al. 2023

View full text Add to dashboard Cite

Objective To build a clinical–radiomics model based on noncontrast computed tomography images to identify the risk of hemorrhagic transformation (HT) in patients with acute ischemic stroke (AIS) following intravenous thrombolysis (IVT). Materials and methods A total of 517 consecutive patients with AIS were screened for inclusion. Datasets from six hospitals were randomly divided into a training cohort and an internal cohort with an 8:2 ratio. The dataset of the seventh hospital was used for an independent external verification. The best dimensionality reduction method to choose features and the best machine learning (ML) algorithm to develop a model were selected. Then, the clinical, radiomics and clinical–radiomics models were developed. Finally, the performance of the models was measured using the area under the receiver operating characteristic curve (AUC). Results Of 517 from seven hospitals, 249 (48%) had HT. The best method for choosing features was recursive feature elimination, and the best ML algorithm to build models was extreme gradient boosting. In distinguishing patients with HT, the AUC of the clinical model was 0.898 (95% CI 0.873–0.921) in the internal validation cohort, and 0.911 (95% CI 0.891–0.928) in the external validation cohort; the AUC of radiomics model was 0.922 (95% CI 0.896–0.941) and 0.883 (95% CI 0.851–0.902), while the AUC of clinical–radiomics model was 0.950 (95% CI 0.925–0.967) and 0.942 (95% CI 0.927–0.958) respectively. Conclusion The proposed clinical–radiomics model is a dependable approach that could provide risk assessment of HT for patients who receive IVT after stroke.

show abstract

Section: Discussionsupporting

confidence: 93%

A clinical–radiomics model based on noncontrast computed tomography to predict hemorrhagic transformation after stroke by machine learning: a multicenter study

et al. 2023

View full text Add to dashboard Cite

show abstract

“…In addition, elevated NT-ProBNP is the strongest independent predictor of long-term adverse clinical outcomes in patients with acute ischemic stroke ( Yang et al, 2018 ). Recent studies have shown that NT-proBNP is associated with bleeding transformation and poor prognosis in stroke patients treated with intravenous thrombolytic therapy ( Zhang et al, 2021 ). In a preliminary single-center study, 4.9% of AIS patients without pre-existing cardiovascular comorbidities developed heart failure during hospitalization, where only one third of heart failure is caused by acute myocardial infarction after stroke ( Micheli et al, 2012 ).…”

Section: Cardiac Dysfunctionmentioning

confidence: 99%

Advances in brain-heart syndrome: Attention to cardiac complications after ischemic stroke

Wang

Peng²

2022

Front. Mol. Neurosci.

View full text Add to dashboard Cite

Neurocardiology is an emerging field that studies the interaction between the brain and the heart, namely the effects of heart injury on the brain and the effects of brain damage on the heart. Acute ischemic stroke has long been known to induce heart damage. Most post-stroke deaths are attributed to nerve damage, and cardiac complications are the second leading cause of death after stroke. In clinical practice, the proper interpretation and optimal treatment for the patients with heart injury complicated by acute ischemic stroke, recently described as stroke-heart syndrome (SHS), are still unclear. Here, We describe a wide range of clinical features and potential mechanisms of cardiac complications after ischemic stroke. Autonomic dysfunction, microvascular dysfunction and coronary ischemia process are interdependent and play an important role in the process of cardiac complications caused by stroke. As a unique comprehensive view, SHS can provide theoretical basis for research and clinical diagnosis and treatment.

show abstract

“…Early prediction is crucial for effective doctor-patient communication and the timely implementation of preventive measures to reduce the incidence of END. Many indicators, such as aquaporin-4 levels or active N-terminal pro-brain natriuretic peptide levels, are typically obtained post-intravenous thrombolysis and are seldom measured in emergency settings [9][10][11] In many studies, it is noted that large artery disease 9,13 , coupled with a low ASPECTS 14,15 , can contribute to the occurrence of END. Large arterial lesions result in extensive ischemic tissue and potentially a signi cant ischemic penumbra.…”

Section: Discussionmentioning

confidence: 99%

A Risk Prediction Model for Unexplained Early Neurological Deterioration Following Intravenous

Zhu,

Wang,

Zuo

et al. 2024

Preprint

View full text Add to dashboard Cite

Background and Objectives: Early neurological deterioration (END) post-intravenous thrombolysis significantly impacts the long-term prognosis of stroke patients. This study aimed to establish a rapid risk prediction model for unexplained END following intravenous thrombolysis. Methods This prospective study consecutively enrolled patients with acute ischemic stroke treated with recombinant tissue plasminogen activator intravenous thrombolysis at the Department of Neurology, Third People's Hospital of Hubei Province, and Yangluo Hospital District between June 2019 and December 2021. Unexplained END was defined as an increase of ≥ 4 points in the National Institutes of Health Stroke Scale (NIHSS) score between admission and 24 hours. A nomogram was developed and assessed by calculating the area under the receiver operating characteristic curve (AUC-ROC). The calibration was assessed using the Hosmer-Lemeshow test. Results A total of 211 patients (130 males and 110 patients aged < 65 years) were included, with 66 experiencing unexplained END. Multivariate logistic regression analysis identified large arterial disease, transient ischemic attack, high blood glucose, high neutrophil/lymphocyte ratio, important perforator disease, and low the Alberta Stroke Program Early CT scores as independent risk factors for END and established the nomogram used above indicators. The nomogram showed an AUC-ROC of 0.809 (95% CI: 0.7429–0.8751), with a specificity of 0.862 and sensitivity of 0.712. The positive predictive value was 0.702, and the negative predictive value was 0.868. The Hosmer-Lemeshow goodness-of-fit test (χ2 = 1.069, P = 0.169) indicated acceptable model calibration. Conclusion This study successfully established a risk prediction model for END following intravenous thrombolysis and the model demonstrates good stability and predictive capacity. Further validation through a prospective, multicenter study is necessary.

show abstract

N-Terminal Pro-brain Natriuretic Peptide Is Associated With Hemorrhagic Transformation and Poor Outcomes in Patients With Stroke Treated With Intravenous Thrombolysis

Cited by 9 publications

References 35 publications

A clinical–radiomics model based on noncontrast computed tomography to predict hemorrhagic transformation after stroke by machine learning: a multicenter study

A clinical–radiomics model based on noncontrast computed tomography to predict hemorrhagic transformation after stroke by machine learning: a multicenter study

Advances in brain-heart syndrome: Attention to cardiac complications after ischemic stroke

A Risk Prediction Model for Unexplained Early Neurological Deterioration Following Intravenous

Contact Info

Product

Resources

About