ArticleEuropean journal of neurology2025
Data-Driven Clustering Approach to Identify Different Phenotypes of Primary Central Nervous System Vasculitis.
Article in European journal of neurology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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1 citing paper in PubMed.
- Inside the Heterogeneity of Primary CNS Vasculitis: A Single-Center 40-Year Experience.Neurology(R) neuroimmunology & neuroinflammation · 2026Article
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37 authors.
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Abstract
backgroundTo determine whether hierarchical unsupervised cluster analysis identifies a phenotypic distinction in adult patients with primary CNS vasculitis (PCNSV).
methodsAn agglomerative hierarchical cluster analysis based on the Ward method was conducted, including 153 patients with complete baseline phenotypic characterization in the COVAC' registry.
resultsThe hierarchical analysis identified two main clusters. In Cluster 1 (n = 109 patients, 71%), patients more frequently had a motor deficit (p = 0.039), ≥ 1 acute brain infarct (p < 0.001), and ≥ 1 intracranial stenosis on CT or MR angiogram (p < 0.001) than patients in Cluster 2 (n = 44 patients, 29%). Conversely, patients in Cluster 2 more frequently had seizures (p < 0.001), cognitive impairment (p = 0.002), gadolinium-enhanced parenchymal lesions (p < 0.001), leptomeningeal enhancement (p < 0.001), ≥ 1 cerebral microbleed (p < 0.001), and intracranial hemorrhage(s) (p < 0.001). In multivariable logistic regression, gadolinium-enhanced parenchymal lesions were significantly associated with Cluster 2 lesions (OR = 35.53 [95% CI: 3.91-322.81], p = 0.002). Conversely, ≥ 1 acute brain infarct was significantly associated with Cluster 1 (OR = 0.003 [95% CI: 0.01-0.03], p < 0.001). A CNS biopsy was positive in 11/40 (28%) patients from Cluster 1 and 35/37 (95%) patients from Cluster 2 (p < 0.001). At 12 months, functional independence (modified Rankin scale score ≤ 2) did not differ between the two groups (p = 0.17). Relapse and mortality rates did not differ between the clusters (p = 0.17 and p = 0.23, respectively).
conclusionThis unsupervised analysis of a large PCNSV cohort identified two different clinical and radiological phenotypes with different diagnostic work-ups, which confirms the relevance of distinguishing PCNSV phenotypes according to the sizes of affected vessels.
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