The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
Cerebral White Matter Lesions and the Risk of Dementia
Abstract
OBJECTIVE: To study the association between white matter lesions (WML) in specific locations and the risk of dementia. DESIGN: The Rotterdam Scan Study, a prospective population-based cohort study. We scored periventricular and subcortical WML on magnetic resonance imaging and observed participants until January 2002 for incident dementia. SETTING: General population. PARTICIPANTS: We included 1077 people aged 60 to 90 years who did not have dementia at baseline. MAIN OUTCOME MEASURE: Incident dementia by Diagnostic and Statistical Manual of Mental Disorders, Third Edition (DSM III-R) criteria. RESULTS: During a mean follow-up of 5.2 years, 45 participants developed dementia. Higher severity of periventricular WML increased the risk of dementia, whereas the association between subcortical WML and dementia was less prominent. The adjusted hazard ratio of dementia for each standard deviation increase in periventricular WML severity was 1.67 (95% confidence interval, 1.25-2.24). This increased risk was independent of other risk factors for dementia and partly independent of other structural brain changes on magnetic resonance imaging. CONCLUSION: White matter lesions, especially in the periventricular region, increase the risk of dementia in elderly people.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Silent Brain Infarcts and the Risk of Dementia and Cognitive Decline
Vermeer, S. E., Prins, N. D., den Heijer, T., Hofman, A., Koudstaal, P. J., & Breteler, M. M. B. (2003) · New England Journal of Medicine · doi:10.1056/nejmoa022066 · Cited by 2,313
Self-citationRoth, M., Tym, E., Mountjoy, C. Q., Huppert, F. A., Hendrie, H., Verma, S., & Goddard, R. (1986) · British Journal of Psychiatry · doi:10.1192/bjp.149.6.698 · Cited by 2,090
Subcortical ischaemic vascular dementia
Román, G. C., Erkinjuntti, T., Wallin, A., Pantoni, L., & Chui, H. C. (2002) · The Lancet Neurology · doi:10.1016/s1474-4422(02)00190-4 · Cited by 1,067
Cited by
Mancia, G., Fagard, R., Narkiewicz, K., Redón, J., Zanchetti, A., Böhm, M., Christiaens, T., Cifkova, R., De Backer, G., Dominiczak, A., et al. (2013) · Journal of Hypertension · doi:10.1097/01.hjh.0000431740.32696.cc · Cited by 5,655
Pantoni, L. (2010) · The Lancet Neurology · doi:10.1016/s1474-4422(10)70104-6 · Cited by 3,405
Debette, S., & Markus, H. S. (2010) · BMJ · doi:10.1136/bmj.c3666 · Cited by 2,328
White matter hyperintensities, cognitive impairment and dementia: an update
Prins, N. D., & Scheltens, P. (2015) · Nature Reviews Neurology · doi:10.1038/nrneurol.2015.10 · Cited by 1,284
Self-citationMidlife vascular risk factor exposure accelerates structural brain aging and cognitive decline
Debette, S., Seshadri, S., Beiser, A., Au, R., Himali, J. J., Palumbo, C., Wolf, P. A., & DeCarli, C. (2011) · Neurology · doi:10.1212/wnl.0b013e318227b227 · Cited by 772
MISRA, C., FAN, Y., & DAVATZIKOS, C. (2009) · NeuroImage · doi:10.1016/j.neuroimage.2008.10.031 · Cited by 552
Classification of white matter lesions on magnetic resonance imaging in elderly persons
Kim, K. W., MacFall, J. R., & Payne, M. E. (2008) · Biological Psychiatry · doi:10.1016/j.biopsych.2008.03.024 · Cited by 539
Debette, S., Beiser, A., DeCarli, C., Au, R., Himali, J. J., Kelly-Hayes, M., Romero, J. R., Kase, C. S., Wolf, P. A., & Seshadri, S. (2010) · Stroke · doi:10.1161/strokeaha.109.570044 · Cited by 508
Fan, Y., Batmanghelich, N., Clark, C. M., & Davatzikos, C. (2008) · NeuroImage · doi:10.1016/j.neuroimage.2007.10.031 · Cited by 477
Inzitari, D., Pracucci, G., Poggesi, A., Carlucci, G., Barkhof, F., Chabriat, H., Erkinjuntti, T., Fazekas, F., Ferro, J. M., Hennerici, M., et al. (2009) · BMJ · doi:10.1136/bmj.b2477 · Cited by 415
Clinical, imaging, and pathological heterogeneity of the Alzheimer's disease syndrome
Lam, B., Masellis, M., Freedman, M., Stuss, D. T., & Black, S. E. (2013) · Alzheimer's Research & Therapy · doi:10.1186/alzrt155 · Cited by 386
Herold, F., Törpel, A., Schega, L., & Müller, N. G. (2019) · European Review of Aging and Physical Activity · doi:10.1186/s11556-019-0217-2 · Cited by 349
Vascular pathology in the aged human brain
Grinberg, L. T., & Thal, D. R. (2010) · Acta Neuropathologica · doi:10.1007/s00401-010-0652-7 · Cited by 345
White matter pathology isolates the hippocampal formation in Alzheimer's disease
Salat, D. H., Tuch, D. S., van der Kouwe, A. J. W., Greve, D. N., Pappu, V., Lee, S. Y., Hevelone, N. D., Zaleta, A. K., Growdon, J. H., Corkin, S., et al. (2010) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2008.03.013 · Cited by 279
The Impact of Disease Comorbidities in Alzheimer’s Disease
Santiago, J. A., & Potashkin, J. A. (2021) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2021.631770 · Cited by 259
Power, M. C., Weuve, J., Gagne, J. J., McQueen, M. B., Viswanathan, A., & Blacker, D. (2011) · Epidemiology · doi:10.1097/ede.0b013e31822708b5 · Cited by 213
Provenzano, F. A., Muraskin, J., Tosto, G., Narkhede, A., Wasserman, B. T., Griffith, E. Y., Guzman, V. A., Meier, I. B., Zimmerman, M. E., Brickman, A. M., et al. (2013) · JAMA Neurology · doi:10.1001/jamaneurol.2013.1321 · Cited by 192
Bos, D., Wolters, F. J., Darweesh, S. K. L., Vernooij, M. W., de Wolf, F., Ikram, M. A., & Hofman, A. (2018) · Alzheimer's & Dementia · doi:10.1016/j.jalz.2018.04.007 · Cited by 192
Self-citationBrayne, C., the Cambridge City over-75s Cohort (CC75C) study neuropathology collaboration, Richardson, K., Matthews, F. E., Fleming, J., Hunter, S., Xuereb, J. H., Paykel, E., Mukaetova-Ladinska, E. B., Huppert, F. A., et al. (2009) · Journal of Alzheimer's Disease · doi:10.3233/jad-2009-1182 · Cited by 191
The enigma of vascular cognitive disorder and vascular dementia
Jellinger, K. A. (2007) · Acta Neuropathologica · doi:10.1007/s00401-006-0185-2 · Cited by 166
Burns, J. M., Church, J. A., Johnson, D. K., Xiong, C., Marcus, D., Fotenos, A. F., Snyder, A. Z., Morris, J. C., & Buckner, R. L. (2005) · Archives of Neurology · doi:10.1001/archneur.62.12.1870 · Cited by 155
DELANO-WOOD, L., BONDI, M. W., SACCO, J., ABELES, N., JAK, A. J., LIBON, D. J., & BOZOKI, A. (2009) · Journal of the International Neuropsychological Society · doi:10.1017/s1355617709990257 · Cited by 155
Scuteri, A., Nilsson, P. M., Tzourio, C., Redon, J., & Laurent, S. (2011) · Journal of Hypertension · doi:10.1097/hjh.0b013e328347cc17 · Cited by 151
Is Alzheimer’s a disease of the white matter?
Sachdev, P. S., Zhuang, L., Braidy, N., & Wen, W. (2013) · Current Opinion in Psychiatry · doi:10.1097/yco.0b013e32835ed6e8 · Cited by 137
Dufouil, C., Godin, O., Chalmers, J., Coskun, O., MacMahon, S., Tzourio-Mazoyer, N., Bousser, M.-G., Anderson, C., Mazoyer, B., & Tzourio, C. (2009) · Stroke · doi:10.1161/strokeaha.108.540633 · Cited by 130
Selective reduction of blood flow to white matter during hypercapnia corresponds with leukoaraiosis
Mandell, D. M., Han, J. S., Poublanc, J., Crawley, A. P., Kassner, A., Fisher, J. A., & Mikulis, D. J. (2008) · Stroke · doi:10.1161/strokeaha.107.501692 · Cited by 114
Swartz, R. H., Stuss, D. T., Gao, F., & Black, S. E. (2008) · Stroke · doi:10.1161/strokeaha.107.491936 · Cited by 82
Guo, X., Pantoni, L., Simoni, M., Bengtsson, C., Björkelund, C., Lissner, L., Gustafson, D., & Skoog, I. (2009) · Hypertension · doi:10.1161/hypertensionaha.109.129700 · Cited by 73
Weaver, N. A., Doeven, T., Barkhof, F., Biesbroek, J. M., Groeneveld, O. N., Kuijf, H. J., Prins, N. D., Scheltens, P., Teunissen, C. E., van der Flier, W. M., et al. (2019) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2019.08.001 · Cited by 71
Preclinical AD Workgroup staging: Pathological correlates and potential challenges
Jicha, G. A., Abner, E. L., Schmitt, F. A., Kryscio, R. J., Riley, K. P., Cooper, G. E., Stiles, N., Mendiondo, M. S., Smith, C. D., Van Eldik, L. J., et al. (2012) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2011.02.018 · Cited by 71
White-matter lesions without lacunar infarcts in CADASIL
Benisty, S., Reyes, S., Godin, O., Hervé, D., Zieren, N., Jouvent, E., Zhu, Y., During, M., Dichgans, M., & Chabriat, H. (2012) · Journal of Alzheimer's Disease · doi:10.3233/jad-2012-111784 · Cited by 30
Kaskikallio, A., Karrasch, M., Koikkalainen, J., Lötjönen, J., Rinne, J. O., Tuokkola, T., Parkkola, R., & Grönholm-Nyman, P. (2019) · Dementia and Geriatric Cognitive Disorders · doi:10.1159/000506124 · Cited by 28
Ortner, M., Kurz, A., Alexopoulos, P., Auer, F., Diehl-Schmid, J., Drzezga, A., Förster, S., Förstl, H., Perneczky, R., Sorg, C., et al. (2015) · Biological Psychiatry · doi:10.1016/j.biopsych.2014.01.019 · Cited by 17
Kasahara, H., Ikeda, M., Makioka, K., Nakamura, T., Takahashi, R., Kawarabayashi, T., Sanada, E., Suto, T., Higuchi, T., Tsushima, Y., et al. (2025) · Journal of Alzheimer’s Disease · doi:10.1177/13872877251316516
Metadata
- Authors
- Prins, N. D., van Dijk, E. J., den Heijer, T., Vermeer, S. E., Koudstaal, P. J., Oudkerk, M., Hofman, A., & Breteler, M. M. B.
- Venue
- Archives of Neurology
- Publisher
- American Medical Association (AMA)
- Published
- 2004-10-01
- Volume
- 61
- Issue
- 10
- Pages
- 1531
- ISSN
- 0003-9942 (ISSN-L)
- OpenAlex
- W2143615397
- Cited by
- 488
- References
- 3
- FWCI
- 11.39
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.