A Causal Classification System for Intracerebral Hemorrhage Subtypes

Autor: Nicolas Raposo, Maria Clara Zanon Zotin, David J. Seiffge, Qi Li, Martina B. Goeldlin, Andreas Charidimou, Ashkan Shoamanesh, Hans Rolf Jäger, Charlotte Cordonnier, Catharina JM Klijn, Eric E. Smith, Steven M. Greenberg, David J. Werring, Anand Viswanathan
Rok vydání: 2022
Předmět:
Zdroj: Annals of Neurology, 93, 1, pp. 16-28
Annals of Neurology, 93, 16-28
ISSN: 1531-8249
0364-5134
DOI: 10.1002/ana.26519
Popis: Contains fulltext : 290906.pdf (Publisher’s version ) (Open Access) OBJECTIVE: Determining the underlying causes of intracerebral hemorrhage (ICH) is of major importance, because risk factors, prognosis, and management differ by ICH subtype. We developed a new causal CLASsification system for ICH Subtypes, termed CLAS-ICH, based on recent advances in neuroimaging. METHODS: CLAS-ICH defines 5 ICH subtypes: arteriolosclerosis, cerebral amyloid angiopathy, mixed small vessel disease (SVD), other rare forms of SVD (genetic SVD and others), and secondary causes (macrovascular causes, tumor, and other rare causes). Every patient is scored in each category according to the level of diagnostic evidence: (1) well-defined ICH subtype; (2) possible underlying disease; and (0) no evidence of the disease. We evaluated CLAS-ICH in a derivation cohort of 113 patients with ICH from Massachusetts General Hospital, Boston, USA, and in a derivation cohort of 203 patients from Inselspital, Bern, Switzerland. RESULTS: In the derivation cohort, a well-defined ICH subtype could be identified in 74 (65.5%) patients, including 24 (21.2%) with arteriolosclerosis, 23 (20.4%) with cerebral amyloid angiopathy, 18 (15.9%) with mixed SVD, and 9 (8.0%) with a secondary cause. One or more possible causes were identified in 42 (37.2%) patients. Interobserver agreement was excellent for each category (kappa value ranging from 0.86 to 1.00). Despite substantial differences in imaging modalities, we obtained similar results in the validation cohort. INTERPRETATION: CLAS-ICH is a simple and reliable classification system for ICH subtyping, that captures overlap between causes and the level of diagnostic evidence. CLAS-ICH may guide clinicians to identify ICH causes, and improve ICH classification in multicenter studies. ANN NEUROL 2023;93:16-28. 01 januari 2023
Databáze: OpenAIRE
Externí odkaz: