Evidence map›Paper›PMID 28453479›Full record

ArticleJournal of Alzheimer's disease : JAD2017

Cognitive Domain Dispersion Association with Alzheimer's Disease Pathology.

Michael Malek-Ahmadi, Sophie Lu, YanYan Chan, Sylvia E Perez, Kewei Chen, Elliott J Mufson

Abstract read
In one paragraph

Article in Journal of Alzheimer's disease : JAD, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed, 2 pooled it
1.3field-weighted citation impact, top 21% of its field
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

21 citing papers in PubMed, 2 syntheses or guidelines pooled it, 29 citations in OpenAlex.

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  7. Characterizing Cognitive Dispersion and Its Correlates Across the Adult Lifespan in MIDUS.The journals of gerontology. Series B, Psychological sciences and social sciences · 2025
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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

6 authors at 4 institutions in 1 country.

Michael Malek-AhmadiBanner Alzheimer's Institute, Phoenix, AZ, USA.
Sophie LuWilliams College, Williamstown, MA, USA.
YanYan ChanArizona State University, Tempe, AZ, USA.
Sylvia E PerezDepartment of Neurobiology and Neurology, Barrow Neurological Institute, Phoenix, AZ, USA.
Kewei ChenBanner Alzheimer's Institute, Phoenix, AZ, USA.
Elliott J MufsonDepartment of Neurobiology and Neurology, Barrow Neurological Institute, Phoenix, AZ, USA.
Banner Alzheimer’s InstituteBarrow Neurological Institute · USArizona State University · USWilliams College · US

Funding

SUPPLEMENT TO RUSH ALZHEIMERS DISEASE CENTER COREP30AG010161 · NIA · RUSH UNIVERSITY MEDICAL CENTER · PI BENNETT, DAVID ALAN · 1991 to 2020
$49.1M
TAU, AB, SYNUCLEIN AND NITRATIVE/OXIDATIVE DAMAGE IN MCIP01AG014449 · NIA · UNIVERSITY OF PITTSBURGH · PI COUNTS, SCOTT E · 1997 to 2024
$39.7M
Cellular and Molecular Medial Temporal Lobe Pathology in Elderly PreMCI subjectsR01AG043375 · NIA · ST. JOSEPH'S HOSPITAL AND MEDICAL CENTER · PI GINSBERG, STEPHEN D, MUFSON, ELLIOTT JAY · 2013 to 2017
$3.6M
NUTRITIONAL REGULATION OF BONE TURNOVERR01AG012161 · NIA · RUTGERS THE ST UNIV OF NJ NEW BRUNSWICK · PI SHAPSES, SUE AMY · 2000 to 2014
$3.4M
Neuroprotective microRNA pathwaysR21AG042146 · NIA · RUSH UNIVERSITY MEDICAL CENTER · PI COUNTS, SCOTT E · 2012 to 2013
$409k
NIA NIH HHS P01 AG014449NIA NIH HHS P30 AG010161NIA NIH HHS R01 AG012161NIA NIH HHS R01 AG043375NIA NIH HHS R21 AG042146
6 · The paper itself

Abstract

Within neuropsychology, the term dispersion refers to the degree of variation in performance between different cognitive domains for an individual. Previous studies have demonstrated that cognitively normal individuals with higher dispersion are at an increased risk for progressing to mild cognitive impairment (MCI) and Alzheimer's disease (AD). Therefore, we determined 1) whether increased dispersion in older adults was associated with amyloid plaques and neurofibrillary tangles (NFTs) and 2) whether increased cognitive dispersion accurately differentiated MCI and AD from non-cognitively impaired (NCI) individuals. The intra-subject standard deviation (ISD) was used to quantify cognitive dispersion, and receiver operator characteristic (ROC) analysis determined whether ISD differentiated MCI and AD from NCI. Neuropathological scores for diffuse plaques (DPs), neuritic plaques (NPs), and NFTs were used as outcome measures in a series of negative binomial regression models. Regression analyses found that increased ISD was associated with increased NFT pathology (β= 10.93, SE = 3.82, p = 0.004), but not with DPs (β= 1.33, SE = 8.85, p = 0.88) or NPs (β= 14.64, SE = 8.45, p = 0.08) after adjusting for age at death, gender, education, APOE ɛ4 status, and clinical diagnosis. An interaction term of ISD with age at death also showed a significant negative association (β= -0.13, SE = 0.04, p = 0.004), revealing an age-dependent association between ISD with NFTs. The ISD failed to show an acceptable level of diagnostic accuracy for MCI (AUC = 0.60). These findings suggest that increased cognitive dispersion is related to NFT pathology where age significantly affects this association.

Indexed as

AgedAged, 80 and overAlzheimer DiseaseCognitive DysfunctionCohort StudiesFemaleHumansMaleNeurofibrillary TanglesNeuropsychological TestsPsychiatric Status Rating ScalesStatistics as TopicStatistics, NonparametricAgingAlzheimer’s diseasecognitiondispersionmild cognitive impairmentneuropathology

Identifiers

PMID28453479
PMCPMC6314665
OpenAlexW2609616348

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

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.