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Clinical Trial Summary

Intracranial aneurysm is the main cause of subarachnoid hemorrhage, and the incidence of subarachnoid hemorrhage in Chinese population is about 5%. The intervention of unruptured intracranial aneurysms is controversial because of its great harm after natural rupture and bleeding, and about a quarter of patients still have poor prognosis through existing invasive treatment methods. How to accurately determine the instability risk of unruptured intracranial aneurysms is the key to resolve this controversy. In previous studies, the stability of intracranial aneurysms involves many characteristics, and the sample size is small. Most of them are retrospective studies and studies on the status after change (rupture/growth). Therefore, the relevant risk factors are not clear at present, and there is still a lack of reliable prediction model. Based on the above facts, this study proposed based on the national hundred regional medical institutions set up the network registration platform of unruptured intracranial aneurysms, real time and openness of Internet, through the way of case resource sharing build unruptured intracranial aneurysm queue, collecting clinical characteristics, imaging features, hemodynamic detection of biological samples and the results of the analysis data, And observe them for two years. The artificial intelligence platform of Tonglian Medical Health was used to integrate and analyze and learn all the data, and then the risk factors related to the stability of intracranial aneurysms within two years were obtained, and the stability prediction model of unruptured intracranial aneurysms was constructed. This study will build the largest network registration platform and population follow-up cohort of unruptured intracranial aneurysms in China, and put forward a prediction model for the stability of unruptured intracranial aneurysms by integrating the multi-dimensional factors of intracranial aneurysms, so as to provide a powerful auxiliary judgment tool for the clinical decision-making of this disease.


Clinical Trial Description

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Study Design


Related Conditions & MeSH terms


NCT number NCT05608122
Study type Observational [Patient Registry]
Source Beijing Tiantan Hospital
Contact
Status Recruiting
Phase
Start date October 30, 2022
Completion date October 1, 2023

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