Evidence map›Paper›PMID 31072117›Full record

ReviewAmerican journal of Alzheimer's disease and other dementias2019

Plasma Biomarkers: Potent Screeners of Alzheimer's Disease.

Muhammad Naveed, Shamsa Mubeen, Abeer Khan, Sehrish Ibrahim, Bisma Meer

Open access · bronzeAbstract readReview
In one paragraph

Review in American journal of Alzheimer's disease and other dementias, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
1.2field-weighted citation impact, top 21% 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

12 citing papers in PubMed, 19 citations in OpenAlex.

  1. Review
  2. Review
  3. Article
  4. Article
  5. Review
  6. Article
  7. Aberrant Energy Metabolism in Alzheimer's Disease.Journal of translational internal medicine · 2022
    Article
  8. Review
  9. Article
  10. Review
  11. Review
  12. Review
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

5 authors at 2 institutions in 1 country.

Muhammad Naveed1 Department of Biotechnology, Faculty of Life Sciences, University of Central Punjab, Lahore, Pakistan.ORCID 0000-0002-4333-8226
Shamsa Mubeen2 Department of Biochemistry and Molecular Biology, University of Gujrat, Gujrat, Pakistan.
Abeer Khan3 Department of Biotechnology, University of Gujrat, Gujrat, Pakistan.
Sehrish Ibrahim3 Department of Biotechnology, University of Gujrat, Gujrat, Pakistan.
Bisma Meer3 Department of Biotechnology, University of Gujrat, Gujrat, Pakistan.
University of Gujrat · PKUniversity of Central Punjab · PK

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Alzheimer's disease (AD), a neurological disorder, is as a complex chronic disease of brain cell death that usher to cognitive decline and loss of memory. Its prevalence differs according to risk factors associated with it and necropsy performs vital role in its definite diagnosis. The stages of AD vary from preclinical to severe that proceeds to death of patient with no availability of treatment. Biomarker may be a biochemical change that can be recognized by different emerging technologies such as proteomics and metabolomics. Plasma biomarkers, 5-protein classifiers, are readily being used for the diagnosis of AD and can also predict its progression with a great accuracy, specificity, and sensitivity. In this review, upregulation or downregulation of few plasma proteins in patients with AD has also been discussed, when juxtaposed with control, and thus serves as potent biomarker in the diagnosis of AD.

Indexed as

Alzheimer DiseaseBiomarkersHumansBiomarkersAlzheimer’s diseasebrain cell deathdiagnosisplasma biomarkers

Identifiers

PMID31072117
PMCPMC10852434
OpenAlexW2944072843

What OpenQuestion holds

Textmetadata
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.