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Prognostic Prediction Model of Patients With AcUte Stroke undeRgoing EndOvascular TheRApy (AURORA) — AURORA  

Acute Ischemic Stroke Clinical Trial

Official title:
Development and Validation for Prognostic Prediction Model of Patients With AcUte Stroke undeRgoing EndOvascular TheRApy (AURORA)

Clinical Trial Summary

Stroke is the leading cause of disability-adjusted life years (DALYs) in China, imposing a heavy burden on society and families. Endovascular therapy (EVT) has opened the 2.0 era of acute ischemic stroke (AIS) treatment, but still up to 1/3 of patients have poor neurological prognosis. The results of several studies at home and abroad and by our team indicate that anesthesia method and perioperative management are one of the key factors affecting the neurological prognosis of EVT treatment in AIS patients. Based on machine learning big data analysis methods, a prognostic model for EVT treatment of AIS patients can be established to guide individualized treatment decisions. Current prediction models only include patients' baseline variables, and lack the inclusion of intraoperative (anesthesia management and interventional process) and postoperative (intensive monitoring treatment) variables, which limits the clinical application of prediction tools. We will establish a large prospective cohort database including preoperative, intraoperative, and postoperative variables, integrate heterogeneous information from multiple sources based on artificial intelligence machine learning algorithms, and build prognostic prediction models with better clinical applicability and calibration, with the aim of optimizing perioperative management of endovascular therapy, guiding individualized clinical decision-making, and improving patients' clinical prognosis.

Clinical Trial Description

n/a

Study Design

Related Conditions & MeSH terms

Clinical Trial Details
NCT number NCT06009315
Study type Observational
Source Beijing Tiantan Hospital
Contact Ruquan Han
Phone 8610-59976660
Email ruquan.han@gmail.com
Status Not yet recruiting
Phase
Start date September 10, 2023
Completion date December 31, 2026
View Details
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