1
|
Meinel TR, Wardlaw JM, Kent DM. Is Incidentally Discovered Covert Cerebrovascular Disease Ignorable? JAMA Neurol 2024; 81:437-438. [PMID: 38315490 DOI: 10.1001/jamaneurol.2023.5456] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2024]
Abstract
This Viewpoint discusses the clinical implications of incidentally discovered covert cerebrovascular disease.
Collapse
Affiliation(s)
- Thomas R Meinel
- Neurology, Stroke Research Center Bern, Bern University Hospital, University of Bern, Bern, Switzerland
| | - Joanna M Wardlaw
- Brain Research Imaging Centre, Division of Neuroimaging Sciences, Centre for Clinical Brain Sciences, UK Dementia Research Institute at the University of Edinburgh, Edinburgh, United Kingdom
| | - David M Kent
- Predictive Analytics and Comparative Effectiveness Center, Institute for Clinical Research and Health Policy Studies, Tufts Medical Center, Boston, Massachusetts
| |
Collapse
|
2
|
Clancy Ú, Puttock EJ, Chen W, Whiteley W, Vickery EM, Leung LY, Luetmer PH, Kallmes DF, Fu S, Zheng C, Liu H, Kent DM. Mortality Outcomes in a Large Population with and without Covert Cerebrovascular Disease. Aging Dis 2024:AD.2024.0211. [PMID: 38421836 DOI: 10.14336/ad.2024.0211] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2023] [Accepted: 02/11/2024] [Indexed: 03/02/2024] Open
Abstract
Covert cerebrovascular disease (CCD) is frequently reported on neuroimaging and associates with increased dementia and stroke risk. We aimed to determine how incidentally-discovered CCD during clinical neuroimaging in a large population associates with mortality. We screened CT and MRI reports of adults aged ≥50 in the Kaiser Permanente Southern California health system who underwent neuroimaging for a non-stroke clinical indication from 2009-2019. Natural language processing identified incidental covert brain infarcts (CBI) and/or white matter hyperintensities (WMH), grading WMH as mild/moderate/severe. Models adjusted for age, sex, ethnicity, multimorbidity, vascular risks, depression, exercise, and imaging modality. Of n=241,028, the mean age was 64.9 (SD=10.4); mean follow-up 4.46 years; 178,554 (74.1%) had CT; 62,474 (25.9%) had MRI; 11,328 (4.7%) had CBI; and 69,927 (29.0%) had WMH. The mortality rate per 1,000 person-years with CBI was 59.0 (95%CI 57.0-61.1); with WMH=46.5 (45.7-47.2); with neither=17.4 (17.1-17.7). In adjusted models, mortality risk associated with CBI was modified by age, e.g. HR 1.34 [1.21-1.48] at age 56.1 years vs HR 1.22 [1.17-1.28] at age 72 years. Mortality associated with WMH was modified by both age and imaging modality e.g., WMH on MRI at age 56.1 HR = 1.26 [1.18-1.35]; WMH on MRI at age 72 HR 1.15 [1.09-1.21]; WMH on CT at age 56.1 HR 1.41 [1.33-1.50]; WMH on CT at age 72 HR 1.28 [1.24-1.32], vs. patients without CBI or without WMH, respectively. Increasing WMH severity associated with higher mortality, e.g. mild WMH on MRI had adjusted HR=1.13 [1.06-1.20] while severe WMH on CT had HR=1.45 [1.33-1.59]. Incidentally-detected CBI and WMH on population-based clinical neuroimaging can predict higher mortality rates. We need treatments and healthcare planning for individuals with CCD.
Collapse
Affiliation(s)
- Úna Clancy
- Centre for Clinical Brain Sciences, Edinburgh Imaging, and UK Dementia Research Institute, University of Edinburgh, Edinburgh EH16 4SB, United Kingdom
| | - Eric J Puttock
- Department of Research and Evaluation, Kaiser Permanente Southern California, Pasadena, California, USA
| | - Wansu Chen
- Department of Research and Evaluation, Kaiser Permanente Southern California, Pasadena, California, USA
| | - William Whiteley
- Centre for Clinical Brain Sciences, Edinburgh Imaging, and UK Dementia Research Institute, University of Edinburgh, Edinburgh EH16 4SB, United Kingdom
| | - Ellen M Vickery
- Predictive Analytics and Comparative Effectiveness Center, Tufts Medical Center, Boston, Massachusetts, USA
| | - Lester Y Leung
- Department of Neurology, Tufts Medical Center, Boston, Massachusetts, USA
| | | | - David F Kallmes
- Department of Radiology, Mayo Clinic, Rochester, Minnesota, USA
| | - Sunyang Fu
- Center for Translational AI Excellence and Applications in Medicine, University of Texas Health Science Center, Houston, Texas, USA
| | - Chengyi Zheng
- Department of Research and Evaluation, Kaiser Permanente Southern California, Pasadena, California, USA
| | - Hongfang Liu
- Center for Translational AI Excellence and Applications in Medicine, University of Texas Health Science Center, Houston, Texas, USA
| | - David M Kent
- Predictive Analytics and Comparative Effectiveness Center, Tufts Medical Center, Boston, Massachusetts, USA
| |
Collapse
|
3
|
Umarova RM, Gallucci L, Hakim A, Wiest R, Fischer U, Arnold M. Adaptation of the Concept of Brain Reserve for the Prediction of Stroke Outcome: Proxies, Neural Mechanisms, and Significance for Research. Brain Sci 2024; 14:77. [PMID: 38248292 PMCID: PMC10813468 DOI: 10.3390/brainsci14010077] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2023] [Revised: 12/22/2023] [Accepted: 01/10/2024] [Indexed: 01/23/2024] Open
Abstract
The prediction of stroke outcome is challenging due to the high inter-individual variability in stroke patients. We recently suggested the adaptation of the concept of brain reserve (BR) to improve the prediction of stroke outcome. This concept was initially developed alongside the one for the cognitive reserve for neurodegeneration and forms a valuable theoretical framework to capture high inter-individual variability in stroke patients. In the present work, we suggest and discuss (i) BR-proxies-quantitative brain characteristics at the time stroke occurs (e.g., brain volume, hippocampus volume), and (ii) proxies of brain pathology reducing BR (e.g., brain atrophy, severity of white matter hyperintensities), parameters easily available from a routine MRI examination that might improve the prediction of stroke outcome. Though the influence of these parameters on stroke outcome has been partly reported individually, their independent and combined impact is yet to be determined. Conceptually, BR is a continuous measure determining the amount of brain structure available to mitigate and compensate for stroke damage, thus reflecting individual differences in neural resources and a capacity to maintain performance and recover after stroke. We suggest that stroke outcome might be defined as an interaction between BR at the time stroke occurs and lesion load. BR in stroke can potentially be influenced, e.g., by modifying cardiovascular risk factors. In addition to the potential power of the BR concept in a mechanistic understanding of inter-individual variability in stroke outcome and establishing individualized therapeutic approaches, it might help to strengthen the synergy of preventive measures in stroke, neurodegeneration, and healthy aging.
Collapse
Affiliation(s)
- Roza M. Umarova
- Department of Neurology, University Hospital Inselspital, University of Bern, 3010 Bern, Switzerland; (L.G.); (U.F.); (M.A.)
| | - Laura Gallucci
- Department of Neurology, University Hospital Inselspital, University of Bern, 3010 Bern, Switzerland; (L.G.); (U.F.); (M.A.)
| | - Arsany Hakim
- Department of Neuroradiology, University Hospital Inselspital, University of Bern, 3010 Bern, Switzerland; (A.H.); (R.W.)
| | - Roland Wiest
- Department of Neuroradiology, University Hospital Inselspital, University of Bern, 3010 Bern, Switzerland; (A.H.); (R.W.)
| | - Urs Fischer
- Department of Neurology, University Hospital Inselspital, University of Bern, 3010 Bern, Switzerland; (L.G.); (U.F.); (M.A.)
- Department of Neurology, University Hospital Basel, University of Basel, 4003 Basel, Switzerland
| | - Marcel Arnold
- Department of Neurology, University Hospital Inselspital, University of Bern, 3010 Bern, Switzerland; (L.G.); (U.F.); (M.A.)
| |
Collapse
|