Predicting recovery after endovascular therapy for acute ischemic stroke
Builds a prediction model for adults with acute ischemic stroke treated with endovascular therapy.
Plain-language title generated from the registry record
Registry title: Prognostic Prediction Model of Patients With AcUte Stroke undeRgoing EndOvascular TheRApy (AURORA)
Key facts
- Where
- Beijing, ChinaSee the site
Could this be for you?
Answer for yourself. This is not a decision: only the study team can say whether you can take part.
- Are you between 18 and 100 years old?
Source: NCT06009315, who can take part
Where in China
- Beijing Tiantan Hospital,Capital Medical UniversityBeijing, ChinaTaking people
Questions to ask the study team
- How often do I need to come in, and for how long each time?
- Are travel costs paid?
- Can I keep my own doctor?
- What happens if I want to stop?
Trial details
- Who runs it
- Beijing Tiantan Hospital
- Trial code
- NCT06009315
- Record updated
- 1 August 2024
- Original description
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.Read full original descriptionShow less
Development and Validation for Prognostic Prediction Model of Patients With AcUte Stroke undeRgoing EndOvascular TheRApy (AURORA)
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.
Inclusion: Age ≥18 years; NIHSS score ≥4; Image-confirmed (CTA/MRA/DSA) intracranial large artery occlusion; ASPECT (anterior circulation) or PC-ASPECT (posterior circulation) score ≥3; Endovascular treatment including arterial thrombolysis, mechanical thrombolysis, and angioplasty (onset to puncture time is recommended to be less than 8 hours for anterior circulation and less than 12 hours for posterior circulation; those exceeding the time window will be determined by the neurointerventionalist through imaging assessment); Signed informed consent by the patient or legal representative.
Exclusion: Pre-stroke mRS score >2; Intracranial bleeding disorders: cerebral hemorrhage, subarachnoid hemorrhage, etc; presence of coagulation disorders, history of systemic bleeding, history of thrombocytopenia or neutropenia; Presence of severe cardiopulmonary disease that, in the opinion of the investigator, makes participation in this study unsuitable; patients with a life expectancy of less than 3 months or otherwise unable to complete this study; Those who are unable to complete the study due to psychiatric disorders, cognitive or mood disorders; Renal insufficiency with elevated blood creatinine (greater than 2 times the upper limit of normal); Contraindication to DSA examination, severe contrast allergy or absolute contraindication to iodine contrast; women of childbearing age who have a negative pregnancy test but refuse to use effective contraception, are pregnant or breast feeding; Other patients who, in the opinion of the investigator, are not suitable for enrollment in the study (specify reason).