Evidence map›Paper›PMID 36102601›Full record

ArticleJournal of the American Geriatrics Society2023

It's all about cognitive trajectory: Accuracy of the cognitive charts-MoCA in normal aging, MCI, and dementia.

Patrick J Bernier, Christian Gourdeau, Pierre-Hugues Carmichael, Jean-Pierre Beauchemin, Philippe Voyer, Carol Hudon, Robert Laforce

Abstract read
In one paragraph

Article in Journal of the American Geriatrics Society, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing 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

20 citing papers in PubMed.

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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

7 authors.

Patrick J BernierServices Gériatriques Spécialisés, CIUSSS de la Capitale-Nationale, Québec, Canada.
Christian GourdeauDépartement de Physique, Cégep Limoilou, Québec City, Canada.
Pierre-Hugues CarmichaelDépartement de Médecine, Centre d'Excellence sur le Vieillissement de Québec, Québec City, Canada.
Jean-Pierre BeaucheminServices Gériatriques Spécialisés, CIUSSS de la Capitale-Nationale, Québec, Canada.
Philippe VoyerDépartement de Médecine, Centre d'Excellence sur le Vieillissement de Québec, Québec City, Canada.
Carol HudonDépartement de Psychologie, École de Psychologie, Université Laval, Québec City, Canada.
Robert LaforceDépartement de neurologie, Clinique Interdisciplinaire de Mémoire du CHU de Québec, Québec City, Canada.

Funding

NATIONAL ALZHEIMERS COORDINATING CENTER (NACC)U01AG016976 · NIA · UNIVERSITY OF WASHINGTON · PI KUKULL, WALTER ANTHONY · 1999 to 2020
$72.8M
National Alzheimer's Coordinating CenterU24AG072122 · NIA · UNIVERSITY OF WASHINGTON · PI STEPHENS, KARI A · 2021 to 2025
$45.8M
Regulatory T cells impose specific translatome changes in effector CD4 T cellsF32AI145283 · NIAID · UNIVERSITY OF WASHINGTON · PI SO, LOMON · 2020 to 2020
$29k
Boehringer-Ingelheim 17349La Chaire de recherche sur les aphasies primaires progressives - Fondation de la Famille Lemaire 0647NIAID NIH HHS F32 AI145283NIA NIH HHS U01 AG016976NIA NIH HHS U24 AG072122
6 · The paper itself

Abstract

backgroundThe Montreal Cognitive Assessment (MoCA) is an established cognitive screening tool in older adults. It remains unclear, however, how to interpret its scores over time and distinguish age-associated cognitive decline (AACD) from early neurodegeneration. We aimed to create cognitive charts using the MoCA for longitudinal evaluation of AACD in clinical practice.

methodsWe analyzed data from the National Alzheimer's Coordinating Center (9684 participants aged 60 years or older) who completed the MoCA at baseline. We developed a linear regression model for the MoCA score as a function of age and education. Based on this model, we generated the Cognitive Charts-MoCA designed to optimize accuracy for distinguishing participants with MCI and dementia from healthy controls. We validated our model using two separate data sets.

resultsFor longitudinal evaluation of the Cognitive Charts-MoCA, sensitivity (SE) was 89%, 95% confidence interval (CI): [86%, 92%] and specificity (SP) 79%, 95% CI: [77%, 81%], hence showing better performance than fixed cutoffs of MoCA (SE 82%, 95% CI: [79%, 85%], SP 68%, 95% CI: [67%, 70%]). For current cognitive status or baseline measurement, the Cognitive Charts-MoCA had a SE of 81%, 95% CI: [79%, 82%], SP of 84%, 95% CI: [83%, 85%] in distinguishing healthy controls from mild cognitive impairment or dementia. Results in two additional validation samples were comparable.

conclusionsThe Cognitive Charts-MoCA showed high validity and diagnostic accuracy for determining whether older individuals show abnormal performance on serial MoCAs. This innovative model allows longitudinal cognitive evaluation and enables prompt initiation of investigation and treatment when appropriate.

Indexed as

Cognitive DysfunctionDementiaAgedAgingCognitionHumansMental Status and Dementia TestsNeuropsychological TestsSensitivity and Specificityage-associated cognitive declinecognitiondementiaearly detectionmild cognitive impairmentMontreal cognitive assessmentscreening

Identifiers

PMID36102601
PMCPMC9870845

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.