NCT06796283

Research on AIS Recurrence Risk Prediction Model Using XGBoost Combined With Convolutional Neural Network Algorithm

• Status: Completed
• Phase: —
• Study type: Observational
• Enrollment: 2,628 (actual)
• Sponsor: Second Affiliated Hospital of Nanchang University · Academic / Other
• Sex: All
• Age: 18 Years – 85 Years
• Healthy volunteers: Not accepted

Summary

The purpose of this observational study is to construct a recurrence risk prediction model for ischemic stroke within 1, 3, 6, and 12 months using XGBoost combined with Convolutional Neural Network (CNN) algorithm. Method: Follow up was conducted on the study subjects at 1, 3, 6, and 12 months after discharge. Follow up primary outcome: Whether the study subjects experienced recurrent stroke events. Secondary outcome: Improved Rinkin score. Collect information on research subjects: It includes demographic data, physical examination, medical history, imaging images, medication use, scale scores, CYP2C19 genotype test results, laboratory tests, and other complex multidimensional data.

Detailed description

This project conducts a one-year follow-up on the enrolled subjects (patients with ischemic stroke) to observe the recurrence and modified Rankin scores after discharge. Combining complex multidimensional data such as demographic information, physical examination, medical history, imaging images, medication status, NIHSS scale scores, Glasgow Coma Scale scores, CYP2C19 genotype test results, and laboratory examinations of the subjects; Convolutional Neural Networks (CNNs) are used to segment lesions and extract features from the subjects' imaging images; Cox regression models are employed to obtain factors influencing recurrence; a prediction model for the risk of recurrence within 1, 3, 6, and 12 months for ischemic stroke is constructed using the XGBoost algorithm combined with Convolutional Neural Networks. The exploration aims to provide new insights and methods for the prevention and control of major chronic diseases by evaluating the effectiveness of XGBoost in predicting the risk of ischemic stroke recurrence at different times. 1. Inclusion Criteria： * 18-85 years old; * Diagnosed with ischemic stroke or transient ischemic attack (diagnosis meets the criteria established by the Cerebrovascular Disease Group of the Neurology Branch of the Chinese Medical Association in 2014); * During the acute phase of onset (2 weeks); * Voluntarily participate and sign an informed consent form. 2. Exclusion criteria： * Cancer patients; * Cardiogenic infarction, cerebral infarction of other causes, and cerebral infarction of unknown causes; * Patients with hemorrhagic stroke, mixed stroke, and tumor stroke; * Merge with severe heart, lung, and liver system diseases; * Researchers identify patients with poor compliance and inability to complete long-term follow-up; * Patients currently participating in any clinical trials related to investigational drugs or medical devices.

Conditions

• Ischemic Stroke

Timeline

• Start date: 2021-04-26
• Primary completion: 2023-03-04
• Completion: 2024-12-31
• First posted: 2025-01-28
• Last updated: 2025-02-21

Locations

1 site across 1 country: China