Abstract 363: Cerebrovascular Events and Associated Risk Factors in Cervical Fibromuscular Dysplasia: A Systematic Review and Meta‐Analysis
Bibliographic record
Abstract
Introduction Cervical fibromuscular dysplasia (FMD) is a non‐inflammatory arteriopathy of cervical arteries that causes arterial stenosis and structural fragility. Due to multifactorial pathophysiology causing arterial dissection, aneurysm formation, and thromboembolic mechanisms, cervical FMD results in cerebrovascular events. We conducted a review to assess the risk of transient ischemic attack, ischemic, and hemorrhagic stroke in cervical FMD. Methods We searched PubMed, EMBASE, Scopus, and Cochrane Library from inception through March 2025. Our primary objective was to estimate the pooled incidence of cerebrovascular events (ischemic stroke, TIA, hemorrhagic stroke) in patients with cervical FMD. We included observational studies involving adults diagnosed with cervical FMD. Two reviewers independently assessed study quality using Newcastle‐Ottawa scale. Pooled incidence proportions were calculated using DerSimonian‐Laird method, given anticipated heterogeneity. Results The search identified 1363 records. 868 titles and abstracts were screened and 69 full‐texts were assessed for eligibility. Ultimately, 16 studies met the inclusion criteria. Of the 1785 FMD cases, 902 (50.53%) had ischemic strokes. The pooled proportion for ischemic stroke was 53% (95%. CI: 27‐ 78; I2 = 99.52%; P<0.01) shown in Figure 1. Of the 3527 FMD cases, 376 (10.66%) had TIA. The pooled proportion for TIA was 15% (95%. CI:4‐ 26; I2 = 78.19%; P=0.01). Of the 648 FMD cases, 24 (3.70%) had hemorrhagic strokes. The pooled proportion for hemorrhagic stroke was 6% (95%. CI:1‐ 12; I2 = 80.85%; P=0.03). The Eggers and Beggs tests for incidence of ischemic stroke yielded non‐significant results with p‐values of 0.42 and 0.75, respectively. Female predominance (70‐90%) and multisite disease increase risk of stroke in FMD. Hemorrhagic events are uncommon (4%) but more frequent with multiple CeAD. Recurrent events are highest in carotid webs (20‐30%) compared to other FMD types. Conclusion Our study establishes a significant link between cervical FMD and cerebrovascular events, with a high aggregated incidence of ischemic stroke. The considerable heterogeneity observed across studies necessitates cautious interpretation of these findings. Most centers from the study consider carotid stenting and EVT as generally safe and effective.Our results collectively emphasize the importance of maintaining a high clinical suspicion for stroke, especially in young women presenting with FMD. image
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".