NCT06010550

Validating a Clinical Decision Support Tool for Stratifying Stroke Risk for Dizziness/Vertigo

Validating a Clinical Decision Support Tool for Stratifying Stroke Risk in Patients Presenting With Dizziness to the Emergency Department

• Status: Unknown
• Phase: —
• Study type: Observational
• Enrollment: 600 (estimated)
• Sponsor: Chiayi Christian Hospital · Academic / Other
• Sex: All
• Age: 20 Years
• Healthy volunteers: Not accepted

Summary

This study aims to validate a machine learning model that stratifies the risk of stroke in patients who present to the emergency department with dizziness or vertigo.

Detailed description

This is a cross-sectional, hospital-based study, with no randomization procedure. Over a 21-month period, approximately 600 subjects will be enrolled. The study will assess the risk of stroke in each patient using a machine-learning model. To detect ischemic or hemorrhagic stroke, each patient will undergo a non-contrast brain magnetic resonance imaging study. The predictive performance of the machine-learning model will be evaluated in terms of accuracy, precision, recall, F1 score, and area under the receiver operating characteristics curve.

Conditions

• Dizziness
• Vertigo

Interventions

Type	Name	Description
RADIATION	Magnetic resonance imaging	Brain magnetic resonance imaging

Timeline

• Start date: 2023-10-01
• Primary completion: 2025-07-31
• Completion: 2025-12-31
• First posted: 2023-08-24
• Last updated: 2023-08-29