Evidence map›Paper›PMID 26925303›Full record

ArticleBrain and behavior2016

Peripheral (deep) but not periventricular MRI white matter hyperintensities are increased in clinical vascular dementia compared to Alzheimer's disease.

Charles D Smith, Eleanor S Johnson, Linda J Van Eldik, Gregory A Jicha, Frederick A Schmitt, Peter T Nelson, Richard J Kryscio, Ronan R Murphy, Clinton V Wellnitz

Abstract read
In one paragraph

Article in Brain and behavior, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 39 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
39citing papers in PubMed, 2 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

39 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
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  3. Linking cortical atrophy to white matter hyperintensities of presumed vascular origin.Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism · 2021
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Charles D SmithDepartment of Neurology University of Kentucky College of Medicine Lexington Kentucky; Magnetic Resonance Imaging and Spectroscopy Center University of Kentucky Lexington Kentucky.
Eleanor S JohnsonMagnetic Resonance Imaging and Spectroscopy Center University of Kentucky Lexington Kentucky.
Linda J Van EldikAlzheimers Disease Center Sanders-Brown Center on Aging University of Kentucky Lexington Kentucky; Department of Anatomy and Neurobiology University of Kentucky College of Medicine Lexington Kentucky.
Gregory A JichaDepartment of Neurology University of Kentucky College of Medicine Lexington Kentucky; Alzheimers Disease Center Sanders-Brown Center on Aging University of Kentucky Lexington Kentucky.
Frederick A SchmittDepartment of Neurology University of Kentucky College of Medicine Lexington Kentucky; Alzheimers Disease Center Sanders-Brown Center on Aging University of Kentucky Lexington Kentucky.
Peter T NelsonAlzheimers Disease Center Sanders-Brown Center on Aging University of Kentucky Lexington Kentucky; Department of Pathology & Laboratory Medicine University of Kentucky College of Medicine Lexington Kentucky.
Richard J KryscioAlzheimers Disease Center Sanders-Brown Center on Aging University of Kentucky Lexington Kentucky; Department of Statistics University of Kentucky Lexington Kentucky.
Ronan R MurphyDepartment of Neurology University of Kentucky College of Medicine Lexington Kentucky; Alzheimers Disease Center Sanders-Brown Center on Aging University of Kentucky Lexington Kentucky.
Clinton V WellnitzDepartment of Diagnostic Radiology Mayo Clinic Scottsdale Arizona.

Funding

University of Kentucky Alzheimer's Disease Core Center - Biomarker CoreP30AG028383 · NIA · UNIVERSITY OF KENTUCKY · PI SCHMITT, FREDERICK · 2006 to 2020
$23.3M
NIA NIH HHS P30 AG028383
6 · The paper itself

Abstract

background and purposeVascular dementia (VAD) is a complex diagnosis at times difficult to distinguish from Alzheimer's disease (AD). MRI scans often show white matter hyperintensities (WMH) in both conditions. WMH increase with age, and both VAD and AD are associated with aging, thus presenting an attribution conundrum. In this study, we sought to show whether the amount of WMH in deep white matter (dWMH), versus periventricular white matter (PVH), would aid in the distinction between VAD and AD, independent of age.

methodsBlinded semiquantitative ratings of WMH validated by objective quantitation of WMH volume from standardized MRI image acquisitions. PVH and dWMH were rated separately and independently by two different examiners using the Scheltens scale. Receiver operator characteristic (ROC) curves were generated using logistic regression to assess classification of VAD (13 patients) versus AD (129 patients). Clinical diagnoses were made in a specialty memory disorders clinic.

resultsUsing PVH rating alone, overall classification (area under the ROC curve, AUC) was 75%, due only to the difference in age between VAD and AD patients in our study and not PVH. In contrast, dWMH rating produced 86% classification accuracy with no independent contribution from age. A global Longstreth rating that combines dWMH and PVH gave an 88% AUC.

conclusionsIncreased dWMH indicate a higher likelihood of VAD versus AD. Assessment of dWMH on MRI scans using Scheltens and Longstreth scales may aid the clinician in distinguishing the two conditions.

Indexed as

AgedAged, 80 and overAlzheimer DiseaseBrainDementia, VascularFemaleHumansMagnetic Resonance ImagingMaleROC CurveWhite MatterImage quantitationmagnetic resonance imagingvascular dementiawhite matter ratings

Identifiers

PMID26925303
PMCPMC4754499

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.