Article ; Online: Novel grading system for CADASIL severity: A multicenter cross-sectional study.
Cerebral circulation - cognition and behavior
2023 Volume 5, Page(s) 100170
Abstract: Background: Cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL) is an inherited progressive cerebral microangiopathy with considerable phenotypic variability. The purpose of this study was to describe the ...
| Abstract | Background: Cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL) is an inherited progressive cerebral microangiopathy with considerable phenotypic variability. The purpose of this study was to describe the generalizability of a recently proposed grading system of CADASIL across multiple centers in the United States. Methods: Electronic medical records (EMR) of an initial neurological assessment of adult patients with confirmed CADASIL were reviewed across 5 tertiary referral medical centers with expertise in CADASIL. Demographic, vascular risk factors, and neuroimaging data were abstracted from EMR. Patients were categorized into groups according to the proposed CADASIL grading system: Grade 0 (asymptomatic), Grade 1 (migraine only), Grade 2 (stroke, TIA, or MCI), Grade 3 (gait assistance or dementia), and Grade 4 (bedbound or end-stage). Inter-rater reliability (IRR) of grading was tested in a subset of cases. Results: We identified 138 patients with a mean age of 50.9 ± 13.1 years, and 57.2% were female. The IRR was acceptable over 33 cases (κ=0.855, SD 0.078, Conclusion: The CADASIL severity grading system is a pragmatic, reliable system for characterizing CADASIL phenotype that does not require testing beyond that done in standard clinical practice. Higher severity grades tended to have a higher vascular risk factor burden. This system offers a simple method of categorizing CADASIL patients which may help to describe populations in observational and interventional studies. |
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| Language | English |
| Publishing date | 2023-06-11 |
| Publishing country | Netherlands |
| Document type | Journal Article |
| ISSN | 2666-2450 |
| ISSN (online) | 2666-2450 |
| DOI | 10.1016/j.cccb.2023.100170 |
| Database | MEDical Literature Analysis and Retrieval System OnLINE |
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