Evidence map›Paper›PMID 35571962›Full record

ArticleAlzheimer's & dementia (Amsterdam, Netherlands)2022

Verbal fluency response times predict incident cognitive impairment.

Matthew R Ayers, Justin Bushnell, Sujuan Gao, Frederick Unverzagt, John Del Gaizo, Virginia G Wadley, Richard Kennedy, David Glenn Clark

Open access · goldAbstract read
In one paragraph

Article in Alzheimer's & dementia (Amsterdam, Netherlands), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
1.5field-weighted citation impact, top 18% 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

10 citing papers in PubMed, 10 citations in OpenAlex.

  1. Article
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  8. Verbal fluency response times predict incident cognitive impairment.Alzheimer's & dementia (Amsterdam, Netherlands) · 2022
    Article
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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

8 authors at 6 institutions in 1 country.

Matthew R AyersDepartment of Psychiatry Richard L. Roudebush VA Medical Center Indianapolis Indiana USA.
Justin BushnellDepartment of Neurology Indiana University Indianapolis Indiana USA.
Sujuan GaoDepartment of Biostatistics Indiana University Indianapolis Indiana USA.
Frederick UnverzagtDepartment of Psychology Indiana University Indianapolis Indiana USA.
John Del GaizoBiomedical Informatics Center Medical University of South Carolina Charleston South Carolina USA.
Virginia G WadleyDepartment of Medicine University of Alabama at Birmingham Birmingham Alabama USA.
Richard KennedyDepartment of Medicine University of Alabama at Birmingham Birmingham Alabama USA.
David Glenn ClarkDepartment of Neurology Indiana University Indianapolis Indiana USA.
Indiana University – Purdue University Indianapolis · USUniversity of Alabama at Birmingham · USIndiana University Health · USIndiana University IndianapolisMedical University of South Carolina · USRichard L. Roudebush VA Medical Center · US

Funding

VCID and Stroke in a Bi-racial National CohortU01NS041588 · NINDS · UNIVERSITY OF ALABAMA AT BIRMINGHAM · PI CUSHMAN, MARY, HOWARD, GEORGE · 2002 to 2022
$96.0M
NINDS NIH HHS U01 NS041588
6 · The paper itself

Abstract

Introduction: In recent decades, researchers have defined novel methods for scoring verbal fluency tasks. In this work, we evaluate novel scores based on speed of word responses. Methods: We transcribed verbal fluency recordings from 641 cases of incident cognitive impairment (ICI) and matched controls, all participants in a large national epidemiological study. Timing measurements of utterances were used to calculate a speed score for each recording. Traditional raw and speed scores were entered into Cox proportional hazards (CPH) regression models predicting time to ICI. Results: Concordance of the CPH model with speed scores was 0.599, an improvement of 3.4% over a model with only raw scores and demographics. Scores with significant effects included animals raw and speed scores, and letter F speed score. Discussion: Novel verbal fluency scores based on response times could enable use of remotely administered fluency tasks for early detection of cognitive decline. Highlights: The current work evaluates prognostication with verbal fluency speed scores. These speed scores improve survival models predicting cognitive decline. Cases with progressive decline have some characteristics suggestive of Alzheimer's disease. The subset of acute decliners is probably pathologically heterogeneous.

Indexed as

Alzheimer's diseasecognitive impairmentcognitive neuropsychologydementiamemory impairmentsemantic memorysurvival analysisverbal fluency

Identifiers

PMID35571962
PMCPMC9074715
OpenAlexW4285193653

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.