Developement of Stroke Prognosis Predictive Precision Medicine Based on a Digital Twin

Seyoung Shin

Status

Enrolling

Conditions

Stroke

Treatments

Other: Stroke

Study type

Observational

Funder types

Other

Identifiers

NCT06035198

RS-2023-00262005

Details and patient eligibility

About

The purpose of this study is to realize customized precision medicine for stroke patients and the visual digitization of patient medical information required in the era of digital transformation.

This study will collect large-scale, high-quality clinical data and daily life exercise pattern data covering the subacute to chronic stages of stroke patients. Based on this, we will use artificial intelligence analysis technology to predict the functional status of stroke patients in the chronic stage after their disability is fixed. We aim to develop the next generation of personalized digital twins by creating a prognostic prediction model.

Enrollment

1,000 estimated patients

Sex

All

Ages

20+ years old

Volunteers

No Healthy Volunteers

Inclusion criteria

Adults over 20 years of age with a history of stroke onset between 2018.01.01 to 2023.07.31.
Patients who exist rehabilitation medical evaluation after stroke onset
Patients who voluntarily decide to participate in this study

Exclusion criteria

Those who have severe internal diseases such as unstable conditions of the cardiovascular system, digestive system, respiratory system, endocrine system, etc. and are in poor overall condition.
Those who have impaired ability to consent (MMSE score less than 10 points) and not accompanied by a care-giver.
In any other cases where the researcher determines that participation in this study is not appropriate.