Spinal Dural Arteriovenous Fistula International Data and Outcomes Registry

Purpose

Given the lack of large multicenter datasets in the context of Spinal arteriovenous fistula, the strength of the evidence surrounding this rare disease is limited. SPIDER hence aims to address that by compiling patient-level data from centers all around the world.

Condition

  • Spinal Dural Arteriovenous Fistula

Eligibility

Eligible Ages
All ages
Eligible Sex
All
Accepts Healthy Volunteers
No

Criteria

Inclusion Criteria:

- Type 1 spinal dural arteriovenous fistula, confirmed on imaging

- Surgically or endovascularly treated

- At least 1 available primary outcome

Study Design

Phase
Study Type
Observational
Observational Model
Cohort
Time Perspective
Retrospective

Recruiting Locations

Thomas Jefferson University Hospital
Philadelphia, Pennsylvania 19102
Contact:
Victor Gabriel El-Hajj, MD
215-955-7000
victorgabriel.el-hajj2@jefferson.edu

More Details

Status
Recruiting
Sponsor
Thomas Jefferson University

Study Contact

Pascal Jabbour, MD
215-955-7000
pascal.jabbour@jefferson.edu

Detailed Description

Type 1 or dural spinal arteriovenous fistulas (SDAVFs) are the most common spinal vascular malformation but remain frequently underdiagnosed due to their insidious onset and nonspecific clinical presentation. Delayed diagnosis is common and often results in progressive, and sometimes irreversible, myelopathy. Despite advances in imaging and treatment, there remains significant variability in diagnostic timelines, treatment strategies (endovascular, surgical, or combined), and reported outcomes across institutions. Existing literature is largely limited to single-center retrospective series or small cohorts, often underpowered to evaluate predictors of outcome, recurrence, and the impact of diagnostic delay. Furthermore, direct comparisons between treatment modalities and long-term functional outcomes using standardized clinical scales are limited. The SPIDER registry is designed to address these gaps by creating the largest international, multicenter dataset of patients with spinal dural AVFs. By pooling de-identified data from high-volume centers worldwide, this study aims to provide robust, generalizable evidence to inform clinical decision-making and optimize patient outcomes.