Evidence map›Paper›PMID 32878308›Full record

ArticleMetabolites2020

Targeted Metabolic Profiling of Urine Highlights a Potential Biomarker Panel for the Diagnosis of Alzheimer's Disease and Mild Cognitive Impairment: A Pilot Study.

Ali Yilmaz, Zafer Ugur, Halil Bisgin, Sumeyya Akyol, Ray Bahado-Singh, George Wilson, Khaled Imam, Michael E Maddens, Stewart F Graham

Open access · goldAbstract read
In one paragraph

Article in Metabolites, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 38 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
38citing papers in PubMed, 3 pooled it
3.1field-weighted citation impact, top 7% 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

38 citing papers in PubMed, 3 syntheses or guidelines pooled it, 63 citations in OpenAlex.

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  8. Evaluation of exploratory fluid biomarkers from a phase 1 senolytic trial in mild Alzheimer's disease.Neurotherapeutics : the journal of the American Society for Experimental NeuroTherapeutics · 2025
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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

9 authors at 3 institutions in 1 country.

Ali YilmazBeaumont Research Institute, Beaumont Health, 3811 W. 13 Mile Road, Royal Oak, MI 48073, USA.
Zafer UgurBeaumont Research Institute, Beaumont Health, 3811 W. 13 Mile Road, Royal Oak, MI 48073, USA.
Halil BisginDepartment of Computer Science, Engineering and Physics, University of Michigan-Flint, Flint, MI 48073, USA.ORCID 0000-0001-6874-168X
Sumeyya AkyolBeaumont Research Institute, Beaumont Health, 3811 W. 13 Mile Road, Royal Oak, MI 48073, USA.
Ray Bahado-SinghBeaumont Research Institute, Beaumont Health, 3811 W. 13 Mile Road, Royal Oak, MI 48073, USA.
George WilsonBeaumont Research Institute, Beaumont Health, 3811 W. 13 Mile Road, Royal Oak, MI 48073, USA.ORCID 0000-0003-3756-1701
Khaled ImamBeaumont Research Institute, Beaumont Health, 3811 W. 13 Mile Road, Royal Oak, MI 48073, USA.
Michael E MaddensBeaumont Research Institute, Beaumont Health, 3811 W. 13 Mile Road, Royal Oak, MI 48073, USA.
Stewart F GrahamBeaumont Research Institute, Beaumont Health, 3811 W. 13 Mile Road, Royal Oak, MI 48073, USA.ORCID 0000-0003-1001-0002
Oakland University · USBeaumont Health · USUniversity of Michigan–Flint · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The lack of sensitive and specific biomarkers for the early detection of mild cognitive impairment (MCI) and Alzheimer's disease (AD) is a major hurdle to improving patient management. A targeted, quantitative metabolomics approach using both

Indexed as

Alzheimer’s diseasebiomarkersmachine learningmetabolomicsmild cognitive impairmentPACS: J0101urine

Identifiers

PMID32878308
PMCPMC7569858
OpenAlexW3082102321

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.