Evidence map›Paper›PMID 38356476›Full record

ArticleAlzheimer's & dementia (New York, N. Y.)

Differentiating MCI from depression through verbal memory scores.

Seyda Cankaya, Betul Yalciner, Melek Kandemir Yilmaz, Burak Yulug

Open access · goldAbstract read
In one paragraph

Article in Alzheimer's & dementia (New York, N. Y.). The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.7field-weighted citation impact, top 35% 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

1 citing paper in PubMed, 2 citations in OpenAlex.

  1. 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

4 authors at 3 institutions in 1 country.

Seyda CankayaAlaaddin Keykubat University, Faculty of Medicine Department of Neurology and Neuroscience Alanya Turkey.
Betul YalcinerOkan University, Faculty of Medicine Department of Neurology Istanbul Turkey.
Melek Kandemir YilmazAmerican Hospital Department of Neurology Bodrum Turkey.
Burak YulugAlaaddin Keykubat University, Faculty of Medicine Department of Neurology and Neuroscience Alanya Turkey.
Alanya University · TRAmerikan Hastanesi · TROkan University · TR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionThe present study aims to assess the differences between major depressive disorder (MDD) and mild cognitive impairment (MCI) in terms of verbal learning profile together with structural changes in the brain on magnetic resonance imaging (MRI) and to reveal predictive factors for MCI.

methodsFifty-six patients with MDD and 31 MCI subjects were assessed using the Turkish Verbal Memory Processes Test (VMPT). Brain MRI was used to evaluate sulcal atrophy (SA), ventricular atrophy, periventricular white matter hyperintensity (WMH), subcortical WMH, basal ganglia infarct, medial temporal lobe atrophy, and infratentorial infarct scores based on the Modified Visual MRI Rating Scale (MVMRS). The symptoms of depression were evaluated with the Beck Depression Inventory in both groups. Demographic factors, VMPT scores, and MVMRS scores between MDD and MCI groups were compared. Also, potential predictors of MCI were analyzed by binary logistic regression analyses.

resultsThe total scores of VMPT and the scores of VMPT subgroups, including immediate memory, highest learning, total learning, and delayed recall, were significantly higher in the MDD groups compared to MCI patients (Mann-Whitney

conclusionOur findings suggest that VMPT may potentially represent a novel neuropsychiatric test that might be combined with MRI-based morphometric evaluation methods, such as MVMRS.

Indexed as

depressionMCIMRIVMPT

Identifiers

PMID38356476
PMCPMC10865486
OpenAlexW4391607281

What OpenQuestion holds

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LicenceCC BY-NC
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Registered trials

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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.