Validation of DRAGON Versus a Simplified DRAGON/Machine Learning

Last updated: September 16, 2019
Sponsor: Ziekenhuis Oost-Limburg
Overall Status: Active - Recruiting

Phase

N/A

Condition

Stroke

Cerebral Ischemia

Treatment

N/A

Clinical Study ID

NCT04092543
DRAGON
  • All Genders

Study Summary

The CT-DRAGON score can predict long-term functional outcome after acute stroke treated by thrombolysis. However, implementation in clinical practice is hampered by a lack of validation in the broad spectrum of stroke patients undergoing thrombectomy, whether or not in combination with thrombolysis or conservative treatment. Furthermore, the CT-DRAGON score considers multiple items, which are not always readily available in every setting. This study aims to investigate whether either a simplified version of the CT-DRAGON score with only three clinical items or a machine learning technique could be as powerful and more feasible.

Eligibility Criteria

Inclusion

Inclusion Criteria:

  • all patients diagnosed with a stroke

Exclusion

Exclusion Criteria:

Study Design

Total Participants: 700
Study Start date:
March 01, 2019
Estimated Completion Date:
November 01, 2021

Study Description

The investigators aim to validate the CT-DRAGON score in all ischaemic stroke localisations and for all treatment options, including a conservative treatment policy. The predictability will then be compared with on the one hand simplified prognostic models that include only a selective set of highly predictive parameters that have already been described in the literature, such as patient age, National Institutes of Health Stroke Scale (NIHSS) and pre-stroke modified Rankin Scale (mRS). On the other hand, machine learning techniques, that incorporate a large set of variables and have recently shown some promising results, will also be applied to predict long-term outcome after ischaemic stroke.

Connect with a study center

  • Ziekenhuis Oost-Limburg

    Genk, 3600
    Belgium

    Active - Recruiting

Not the study for you?

Let us help you find the best match. Sign up as a volunteer and receive email notifications when clinical trials are posted in the medical category of interest to you.