AIMC Topic: Thrombolytic Therapy
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Metabolomic biomarkers could be molecular clocks in timing stroke onset.
Scientific reports
Jul 1, 2025
The preferred treatment for acute ischaemic stroke (AIS) is intravenous thrombolysis (IVT) administered within 4.5 hours (h) of symptom onset. This study aimed to identify metabolomic biomarkers for distinguishing AIS patients within 4.5 h of symptom...
Risk Factors and Outcomes of Hemorrhagic Transformation in Acute Ischemic Stroke Following Thrombolysis: Analysis of a Single-Center Experience and Review of the Literature.
Medicina (Kaunas, Lithuania)
Apr 14, 2025
: This is a retrospective study conducted at the Clinical County Hospital of Craiova, Romania, providing valuable insights into hemorrhagic transformation (HT) in thrombolyzed patients with acute ischemic stroke (AIS). Hemorrhagic complications remai...
Automated Identification of Stroke Thrombolysis Contraindications from Synthetic Clinical Notes: A Proof-of-Concept Study.
Cerebrovascular diseases extra
Mar 17, 2025
INTRODUCTION: Timely thrombolytic therapy improves outcomes in acute ischemic stroke. Manual chart review to screen for thrombolysis contraindications may be time-consuming and prone to errors. We developed and tested a large language model (LLM)-bas...
Rapid Blood Clot Removal via Remote Delamination and Magnetization of Clot Debris.
Advanced science (Weinheim, Baden-Wurttemberg, Germany)
Mar 8, 2025
Micro/nano-scale robotic devices are emerging as a cutting-edge approach for precision intravascular therapies, offering the potential for highly targeted drug delivery. While employing micro/nanorobotics for stroke treatment is a promising strategy ...
Deep learning of noncontrast CT for fast prediction of hemorrhagic transformation of acute ischemic stroke: a multicenter study.
European radiology experimental
Jan 15, 2025
BACKGROUND: Hemorrhagic transformation (HT) is a complication of reperfusion therapy following acute ischemic stroke (AIS). We aimed to develop and validate a model for predicting HT and its subtypes with poor prognosis-parenchymal hemorrhage (PH), i...
Influence of renal function on blood pressure control and outcome in thrombolyzed patients after acute ischemic stroke: analysis of the ENCHANTED trial.
Frontiers in endocrinology
Dec 9, 2024
BACKGROUND: The effect of renal impairment in patients who receive intravenous thrombolysis for acute ischemic stroke (AIS) is unclear. We aimed to determine the associations of renal impairment and clinical outcomes and any modification of the effec...
SDS-Net: A Synchronized Dual-Stage Network for Predicting Patients Within 4.5-h Thrombolytic Treatment Window Using MRI.
Journal of imaging informatics in medicine
Oct 28, 2024
Timely and precise identification of acute ischemic stroke (AIS) within 4.5 h is imperative for effective treatment decision-making. This study aims to construct a novel network that utilizes limited datasets to recognize AIS patients within this cri...
Machine learning-based predictive model for the development of thrombolysis resistance in patients with acute ischemic stroke.
BMC neurology
Aug 26, 2024
BACKGROUND: The objective of this study was to establish a predictive model utilizing machine learning techniques to anticipate the likelihood of thrombolysis resistance (TR) in acute ischaemic stroke (AIS) patients undergoing recombinant tissue plas...
Deep learning-based white matter lesion volume on CT is associated with outcome after acute ischemic stroke.
European radiology
Jan 29, 2024
BACKGROUND: Intravenous thrombolysis (IVT) before endovascular treatment (EVT) for acute ischemic stroke might induce intracerebral hemorrhages which could negatively affect patient outcomes. Measuring white matter lesions size using deep learning (D...
Development and validation of outcome prediction model for reperfusion therapy in acute ischemic stroke using nomogram and machine learning.
Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology
Jan 26, 2024
OBJECTIVE: To develop logistic regression nomogram and machine learning (ML)-based models to predict 3-month unfavorable functional outcome for acute ischemic stroke (AIS) patients undergoing reperfusion therapy.
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