Evidence Hub

Risk factors for cervical artery dissection: a systematic review with meta-analysis

Jacobs W, Wright DS, Pohlman K, Rosenbaum R, Hutten BA, Scholten-Peeters GG, Haldeman S, Ket JC et al.

Stroke and vascular neurology, 2026

6 citations

Abstract

Background: Cervical artery dissection (CAD) is a rare cause of stroke. This is an update of an earlier systematic review, which focuses on the risk of CAD in the general population. The objective was to identify the risk factors for CAD.

Methods: A comprehensive search was conducted in MEDLINE, EMBASE and Web of Science on 20 September 2024. Observational studies (cohort, case-control studies and case-crossover studies) that studied patients with CAD and a control group were included. Risk of bias was assessed with the ROBINS-E tool, and certainty of the evidence was assessed using Grading of Recommendations Assessment, Development and Evaluation (GRADE). The results were stratified by healthy controls (primary analyses) and other control groups, notably ischaemic non-CAD stroke (secondary analyses).

Findings: In total, 128 study reports were identified, of which 54 used one or more healthy control groups. Of these reports, 49 (91%) used a case-control design. The risk of bias was generally high (93%). For the following categories, effects were identified: (1) genetic factors or factors with a familial predisposition: migraine, methylenetetrahydrofolate reductase (MTHFR), TT homozygosity, matrix metalloproteinases (MMP) concentration, and connective tissue disorders; (2) external factors: recent infection, winter or autumn-winter season and oral contraceptive use; (3) minor trauma; (4) cardiovascular factors: hypertension, hypercholesterolaemia, relative vasodilatation of…

How strong is the evidence?

Evidence Hub reads this as a meta-analysis, done in people. Its evidence level is 1 of 5 (Highest · pooled evidence). Pooled evidence from several studies sits at the top of the evidence pyramid.

How the five levels of evidence work. The level is assigned automatically from the abstract and can be wrong, so check the paper.

Read the paper

Related studies

Go deeper in Evidence Hub

Evidence Hub adds a study data sheet (design, sample size, evidence level, key numbers), an AI summary and a chat grounded in the paper's text.

Open this study Sign up free