Evidence map›Paper›PMID 33169874›Full record

ArticleInternational journal of geriatric psychiatry2021

Cognitive variability, brain aging, and cognitive decline in late-life major depression.

Kevin J Manning, Joshua Preciado-Pina, Lihong Wang, Kimberly Fitzgibbon, Grace Chan, David C Steffens

Open access · greenAbstract read
In one paragraph

Article in International journal of geriatric psychiatry, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
1.1field-weighted citation impact, top 23% 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

8 citing papers in PubMed, 16 citations in OpenAlex.

  1. Article
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  3. Article
  4. Review
  5. Article
  6. Article
  7. Pathomechanisms of Vascular Depression in Older Adults.International journal of molecular sciences · 2021
    Review
  8. 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

6 authors at 2 institutions in 1 country.

Kevin J ManningDepartment of Psychiatry, University of Connecticut School of Medicine, Farmington, Connecticut, USA.ORCID 0000-0002-1456-7687
Joshua Preciado-PinaDepartment of Psychology, The University of Texas at El Paso, El Paso, Texas, USA.
Lihong WangDepartment of Psychiatry, University of Connecticut School of Medicine, Farmington, Connecticut, USA.
Kimberly FitzgibbonDepartment of Psychiatry, University of Connecticut School of Medicine, Farmington, Connecticut, USA.
Grace ChanDepartment of Psychiatry, University of Connecticut School of Medicine, Farmington, Connecticut, USA.ORCID 0000-0002-1257-6889
David C SteffensDepartment of Psychiatry, University of Connecticut School of Medicine, Farmington, Connecticut, USA.
University of Connecticut · USThe University of Texas at El Paso · US

Funding

Geriatric Depression: Risk Factors for Adverse OutcomesR01MH054846 · NIMH · UNIVERSITY OF CONNECTICUT SCH OF MED/DNT · PI STEFFENS, DAVID C. · 1995 to 2016
$10.1M
Phenotype Predictors of Cognitive Outcomes in Geriatric DepressionR01MH108578 · NIMH · UNIVERSITY OF CONNECTICUT SCH OF MED/DNT · PI STEFFENS, DAVID C. · 2016 to 2025
$5.5M
NIMH NIH HHS R01 MH054846NIMH NIH HHS R01 MH108578
6 · The paper itself

Abstract

objectivesOlder adults with late-life major depression (LLMD) are at increased risk of dementia. Dispersion, or within-person performance variability across cognitive tests, is a potential marker of cognitive decline. This study examined group differences in dispersion between LLMD and nondepressed healthy controls (HC) and investigated whether dispersion was a predictor of cognitive performance 1 year later in LLMD. We also explored demographic, clinical, and structural imaging correlates of dispersion in LLMD and HC. We hypothesized that dispersion would be greater in LLMD compared with HC and would be associated with worse cognitive performance 1 year later in LLMD.

designParticipants were enrolled in the Neurobiology of Late-Life Depression, a naturalistic longitudinal investigation of the predictors of poor illness course in LLMD.

participantsThe baseline sample consisted of 121 older adults with LLMD and 39 HC; of these subjects, 94 LLMD and 35 HC underwent magnetic resonance imaging (MRI). One-year cognitive data were available for 107 LLMD patients. MEASUREMENTS: All participants underwent detailed clinical and structural MRI at baseline. LLMD participants also completed a comprehensive cognitive evaluation 1 year later.

resultsHigher test dispersion was evident in LLMD when compared with nondepressed controls. Greater baseline dispersion predicted 1-year cognitive decline in LLMD patients even when controlling for baseline cognitive functioning and demographic and clinical confounders. Dispersion was correlated with white matter lesions in LLMD but not HC. Dispersion was also correlated with anxiety in both LLMD and HC.

conclusionsDispersion is a marker of neurocognitive integrity that requires further exploration in LLMD.

Indexed as

Cognitive DysfunctionMajor Depressive DisorderAgedAgingBrainCognitionDepressionHumansMagnetic Resonance ImagingNeuropsychological Testsdispersionintraindividualvariabilitylate-life depressionneuropsychology

Identifiers

PMID33169874
PMCPMC12246991
OpenAlexW3103838924

What OpenQuestion holds

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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.