Evidence map›Paper›PMID 34829370›Full record

ArticleDiagnostics (Basel, Switzerland)2021

Alzheimer's Disease-Related Metabolic Pattern in Diverse Forms of Neurodegenerative Diseases.

Angus Lau, Iman Beheshti, Mandana Modirrousta, Tiffany A Kolesar, Andrew L Goertzen, Ji Hyun Ko

Abstract read
In one paragraph

Article in Diagnostics (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
–field-weighted citation impact
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

11 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Article
  5. Review
  6. Review
  7. Article
  8. Article
  9. Review
  10. Article
  11. Combined 18F-FDG PET-CT markers in dementia with Lewy bodies.Alzheimer's & dementia (Amsterdam, Netherlands)
    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.

Angus LauDepartment of Human Anatomy and Cell Science, University of Manitoba, Winnipeg, MB R3E 0J9, Canada.ORCID 0000-0001-7046-604X
Iman BeheshtiDepartment of Human Anatomy and Cell Science, University of Manitoba, Winnipeg, MB R3E 0J9, Canada.
Mandana ModirroustaDepartment of Psychiatry, University of Manitoba, Winnipeg, MB R3E 3N4, Canada.
Tiffany A KolesarDepartment of Human Anatomy and Cell Science, University of Manitoba, Winnipeg, MB R3E 0J9, Canada.
Andrew L GoertzenDepartment of Radiology, University of Manitoba, Winnipeg, MB R3T 2N2, Canada.
Ji Hyun KoDepartment of Human Anatomy and Cell Science, University of Manitoba, Winnipeg, MB R3E 0J9, Canada.

Funding

Alzheimer's Disease Neuroimaging Initiative - SupplementU01AG024904 · NIA · NORTHERN CALIFORNIA INSTITUTE RES &EDUC · PI WEINER, MICHAEL W · 2004 to 2015
$121.0M
Natural Sciences and Engineering Research Council PDF-545615-2020Natural Sciences and Engineering Research Council RGPIN-2016-05964NIA NIH HHS U01 AG024904
6 · The paper itself

Abstract

Dementia is broadly characterized by cognitive and psychological dysfunction that significantly impairs daily functioning. Dementia has many causes including Alzheimer's disease (AD), dementia with Lewy bodies (DLB), and frontotemporal lobar degeneration (FTLD). Detection and differential diagnosis in the early stages of dementia remains challenging. Fueled by AD Neuroimaging Initiatives (ADNI) (Data used in preparation of this article were obtained from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. As such, the investigators within ADNI contributed to the design and implementation of ADNI and/or provided data but did not participate in analysis or writing of this report.), a number of neuroimaging biomarkers for AD have been proposed, yet it remains to be seen whether these markers are also sensitive to other types of dementia. We assessed AD-related metabolic patterns in 27 patients with diverse forms of dementia (five had probable/possible AD while others had atypical cases) and 20 non-demented individuals. All participants had positron emission tomography (PET) scans on file. We used a pre-trained machine learning-based AD designation (MAD) framework to investigate the AD-related metabolic pattern among the participants under study. The MAD algorithm showed a sensitivity of 0.67 and specificity of 0.90 for distinguishing dementia patients from non-dementia participants. A total of 18/27 dementia patients and 2/20 non-dementia patients were identified as having AD-like patterns of metabolism. These results highlight that many underlying causes of dementia have similar hypometabolic pattern as AD and this similarity is an interesting avenue for future research.

Indexed as

Alzheimer’s diseasebiomarkerdementiadementia with Lewy bodiesFDG-PETfrontotemporal lobar degenerationmachine learningmetabolic classificationneurodegenerative diseasesupport vector machine

Identifiers

PMID34829370
PMCPMC8624480

What Socratic holds

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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 Socratic graph.