Evidence map›Paper›PMID 38411289›Full record

ArticleEuropean journal of neurology2024

Clinical variables contributing to the identification of biologically defined subgroups within cognitively unimpaired and mild cognitive impairment individuals.

Sofia Marcolini, Jaime D Mondragón, Zeus T Dominguez-Vega, Peter P De Deyn, Natasha M Maurits, Alzheimer's Disease Neuroimaging Initiative

Open access · goldAbstract read
In one paragraph

Article in European journal of neurology, 2024. 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
1.2field-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

2 citing papers in PubMed, 3 citations in OpenAlex.

  1. Article
  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

6 authors at 2 institutions in 3 countries.

Sofia MarcoliniUniversity Medical Center Groningen, Department of Neurology, University of Groningen, Groningen, The Netherlands.ORCID https://orcid.org/0000-0002-1856-9348
Jaime D MondragónUniversity Medical Center Groningen, Department of Neurology, University of Groningen, Groningen, The Netherlands.
Zeus T Dominguez-VegaUniversity Medical Center Groningen, Department of Neurology, University of Groningen, Groningen, The Netherlands.
Peter P De DeynUniversity Medical Center Groningen, Department of Neurology, University of Groningen, Groningen, The Netherlands.
Natasha M MauritsUniversity Medical Center Groningen, Department of Neurology, University of Groningen, Groningen, The Netherlands.
Alzheimer's Disease Neuroimaging Initiative
University Medical Center Groningen · NLAlzheimer’s Disease Neuroimaging Initiative · US

Funding

Institutional grant PUSH: Partnership of UMCG - Siemens Healthineers for building the future of HealthJoint Programming Initiative Neurodegenerative Diseases (JPND) HEROES 733051072
6 · The paper itself

Abstract

backgroundA lack of consensus exists in linking demographic, behavioral, and cognitive characteristics to biological stages of dementia, defined by the ATN (amyloid, tau, neurodegeneration) classification incorporating amyloid, tau, and neuronal injury biomarkers.

methodsUsing a random forest classifier we investigated whether 27 demographic, behavioral, and cognitive characteristics allowed distinction between ATN-defined groups with the same cognitive profile. This was done separately for three cognitively unimpaired (CU) (112 A-T-N-; 46 A+T+N+/-; 65 A-T+/-N+/-) and three mild cognitive impairment (MCI) (128 A-T-N-; 223 A+T+N+/-; 94 A-T+/-N+/-) subgroups.

resultsClassification-balanced accuracy reached 39% for the CU and 52% for the MCI subgroups. Logical Delayed Recall (explaining 16% of the variance), followed by the Alzheimer's Disease Assessment Scale 13 (14%) and Everyday Cognition Informant (10%), were the most relevant characteristics for classification of the MCI subgroups. Race and ethnicity, marital status, and Everyday Cognition Patient were not relevant (0%).

conclusionsThe demographic, behavioral, and cognitive measures used in our model were not informative in differentiating ATN-defined CU profiles. Measures of delayed memory, general cognition, and activities of daily living were the most informative in differentiating ATN-defined MCI profiles; however, these measures alone were not sufficient to reach high classification performance.

Indexed as

Alzheimer DiseaseCognitive DysfunctionActivities of Daily LivingAmyloid beta-PeptidesBiomarkersHumanstau ProteinsAmyloid beta-PeptidesBiomarkerstau ProteinsAlzheimer's diseasebiomarkersdiagnosispsychological testsrandom forest

Identifiers

PMID38411289
PMCPMC11235959
OpenAlexW4392198987

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.