Evidence map›Paper›PMID 34186536›Full record

ArticleDementia and geriatric cognitive disorders2021

Neuropsychological Equivalence of the Clinical Diagnosis of Mild Cognitive Impairment in the National Alzheimer's Coordinating Center Uniform Data Set and Alzheimer's Disease Neuroimaging Initiative.

Andrew M Kiselica, Jared F Benge, Alzheimer’s Disease Neuroimaging Initiative

Abstract read
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In one paragraph

Article in Dementia and geriatric cognitive disorders, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–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

2 citing papers in PubMed.

  1. Review
  2. Article
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

3 authors.

Andrew M KiselicaDepartment of Health Psychology, University of Missouri, Columbia, Missouri, USA.
Jared F BengeDepartment of Neurology, University of Texas - Austin, Austin, Texas, USA.
Alzheimer’s Disease Neuroimaging Initiative

Funding

Project 1U19AG024904 · NIA · NORTHERN CALIFORNIA INSTITUTE/RES/EDU · PI MICHAEL W WEINER · 2016 to 2026
$226.7M
Alzheimer's Disease Neuroimaging Initiative - SupplementU01AG024904 · NIA · NORTHERN CALIFORNIA INSTITUTE RES &EDUC · PI WEINER, MICHAEL W · 2004 to 2015
$121.0M
NATIONAL ALZHEIMERS COORDINATING CENTER (NACC)U01AG016976 · NIA · UNIVERSITY OF WASHINGTON · PI KUKULL, WALTER ANTHONY · 1999 to 2020
$72.8M
THERAPEUTIC EFFECTS OF INTRA-NASAL INSULIN DETEMIRP50AG005136 · NIA · UNIVERSITY OF WASHINGTON · PI JAYADEY, SUMAN · 1985 to 2019
$57.2M
WASHINGTON UNIVERSITY ALZHEIMERS DISEASE RESEARCH CENTERP50AG005681 · NIA · WASHINGTON UNIVERSITY · PI MORRIS, JOHN · 1985 to 2019
$52.1M
SUPPLEMENT TO RUSH ALZHEIMERS DISEASE CENTER COREP30AG010161 · NIA · RUSH UNIVERSITY MEDICAL CENTER · PI BENNETT, DAVID ALAN · 1991 to 2020
$49.1M
Satellite Diagnostic and Treatment Clinic CoreP50AG008702 · NIA · COLUMBIA UNIV NEW YORK MORNINGSIDE · PI DE JAGER, PHILIP L · 1989 to 2019
$46.3M
National Alzheimer's Coordinating CenterU24AG072122 · NIA · UNIVERSITY OF WASHINGTON · PI STEPHENS, KARI A · 2021 to 2025
$45.8M
TREATMENT OF DEPRESSION IN ALZHEIMER'S DISEASEP50AG005133 · NIA · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI BECKER, JAMES T. · 1985 to 2019
$43.0M
VASCULAR RISK AND COGNITIVE STATUS IN A LATINO POPULATIONP50AG005142 · NIA · UNIVERSITY OF SOUTHERN CALIFORNIA · PI ARANDA, MARIA P. · 1985 to 2019
$41.0M
VESICULAR LOCALIZATION AND FUNCTION OF PRESENILIN 1 FRAGMENTP50AG005138 · NIA · MOUNT SINAI SCHOOL OF MEDICINE OF NYU · PI SCHIMMING, CORBETT · 1985 to 2019
$37.9M
'T V ASSESSMENT - MEMORY DISORDERED PATIENTS'P50AG005146 · NIA · JOHNS HOPKINS UNIVERSITY · PI HUGANIR, RICHARD L · 1985 to 2019
$37.6M
CIHRNIA NIH HHS P30 AG008017NIA NIH HHS P30 AG008051NIA NIH HHS P30 AG010124NIA NIH HHS P30 AG010129NIA NIH HHS P30 AG010133NIA NIH HHS P30 AG010161NIA NIH HHS P30 AG012300NIA NIH HHS P30 AG013846NIA NIH HHS P30 AG013854NIA NIH HHS P30 AG019610NIA NIH HHS P30 AG028383NIA NIH HHS P30 AG035982NIA NIH HHS P30 AG049638NIA NIH HHS P30 AG053760NIA NIH HHS P30 AG062421NIA NIH HHS P30 AG062422NIA NIH HHS P30 AG062428NIA NIH HHS P30 AG062429NIA NIH HHS P30 AG062715NIA NIH HHS P30 AG066444NIA NIH HHS P50 AG005133NIA NIH HHS P50 AG005136NIA NIH HHS P50 AG005138NIA NIH HHS P50 AG005142NIA NIH HHS P50 AG005146NIA NIH HHS P50 AG005681NIA NIH HHS P50 AG008702NIA NIH HHS P50 AG016573NIA NIH HHS P50 AG023501NIA NIH HHS P50 AG025688NIA NIH HHS P50 AG047266NIA NIH HHS P50 AG047270NIA NIH HHS P50 AG047366NIA NIH HHS U01 AG016976NIA NIH HHS U01 AG024904NIA NIH HHS U19 AG024904NIA NIH HHS U24 AG072122
6 · The paper itself

Abstract

introductionOur understanding of Alzheimer's disease may be improved by harmonizing data from large cohort studies of older adults. Differences in the way clinical conditions, like mild cognitive impairment (MCI), are diagnosed may lead to variability among participants that share the same diagnostic label. This variability presents a challenge for cohort harmonization and may lead to inconsistency in research findings. Little research to date has explored the equivalence of the diagnostic label of MCI across 2 of the largest and most influential cohort studies in the USA: the National Alzheimer's Coordinating Center (NACC) and the Alzheimer's Disease Neuroimaging Initiative (ADNI).

methodsParticipants with MCI due to presumed Alzheimer's disease from the NACC Uniform Data Set (n = 789) and ADNI (n = 131) were compared on demographic, psychological, and functional variables, as well as on an abbreviated neuropsychological battery common to the 2 data sets.

resultsThough similar in terms of age, education, and functional status, the NACC sample was more diverse (17.4% non-White participants vs. 7.6% in ADNI; χ2 = 7.923, p = 0.005) and tended to perform worse on some cognitive tests. In particular, participants diagnosed with MCI in NACC were more likely to have clinically significant impairments on language measures (26.36-31.18%) than MCI participants in ADNI (16.03-19.85%). DISCUSSION: The current findings suggest important differences in cognitive performances between 2 large MCI cohorts, likely reflective of differences in diagnostic criteria used in these 2 studies, as well as differences in sample compositions. Such diagnostic heterogeneity may make harmonizing data across these cohorts challenging. However, application of shared psychometric criteria across studies may lead to closer equivalence of MCI groups. Such approaches could pave the way for cohort harmonization and enable "big data" analytic approaches to understanding Alzhei-mer's to be developed.

Indexed as

Alzheimer DiseaseCognitive DysfunctionAgedCohort StudiesDisease ProgressionHumansNeuroimagingNeuropsychological TestsAging researchAlzheimer’s disease neuropsychological testClinical assessment of Alzheimer’s diseaseCognitive testsMild cognitive impairmentNeuropsychological Alzheimer’s disease and mild cognitive impairmentPsychometrics

Identifiers

PMID34186536
PMCPMC8819646

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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.