ArticleAnnals of clinical and translational neurology2024
Prediction of stroke severity: systematic evaluation of lesion representations.
Article in Annals of clinical and translational neurology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- Acute Stroke Severity Assessment: The Impact of Lesion Size and Functional Connectivity.Brain sciences · 2025Article
- Large-scale network topography of stroke predicts functional outcome after mechanical thrombectomy.Brain communications · 2025Article
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Authors and funding
23 authors.
Funding
Abstract
objectiveTo systematically evaluate which lesion-based imaging features and methods allow for the best statistical prediction of poststroke deficits across independent datasets.
methodsWe utilized imaging and clinical data from three independent datasets of patients experiencing acute stroke (N
resultsWe found that prediction models trained on small single-center datasets could perform well using within-dataset cross-validation, but results did not generalize to independent datasets (median R
interpretationWe conclude that (1) prediction performance in independent datasets of patients with acute stroke cannot be inferred from cross-validated results within a dataset, as performance results obtained via these two methods differed consistently, (2) prediction performance can be improved by training on large and, importantly, multicenter datasets, and (3) structural and functional disconnection allow for improved prediction of acute stroke severity.
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