Evidence map›Paper›PMID 32848707›Full record

ArticleFrontiers in aging neuroscience2020

Detecting Amyloid Positivity in Elderly With Increased Risk of Cognitive Decline.

Timo Pekkala, Anette Hall, Tiia Ngandu, Mark van Gils, Seppo Helisalmi, Tuomo Hänninen, Nina Kemppainen, Yawu Liu, Jyrki Lötjönen, Teemu Paajanen and 4 more

Abstract read
In one paragraph

Article in Frontiers in aging neuroscience, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed, 1 pooled it
–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

12 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Deep Learning-Based Prediction of PET Amyloid Status Using MRI.AJNR. American journal of neuroradiology · 2025
    Article
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  11. Cortical Morphometry Analysis based on Worst Transportation Theory.Information processing in medical imaging : proceedings of the ... conference · 2021
    Article
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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

14 authors.

Timo PekkalaInstitute of Clinical Medicine/Neurology, University of Eastern Finland, Kuopio, Finland.
Anette HallInstitute of Clinical Medicine/Neurology, University of Eastern Finland, Kuopio, Finland.
Tiia NganduPublic Health Promotion Unit, Finnish Institute for Health and Welfare, Helsinki, Finland.
Mark van GilsVTT Technical Research Centre of Finland Ltd., Tampere, Finland.
Seppo HelisalmiInstitute of Clinical Medicine/Neurology, University of Eastern Finland, Kuopio, Finland.
Tuomo HänninenNeurocenter/Neurology, Kuopio University Hospital, Kuopio, Finland.
Nina KemppainenTurku PET Centre, University of Turku, Turku, Finland.
Yawu LiuInstitute of Clinical Medicine/Neurology, University of Eastern Finland, Kuopio, Finland.
Jyrki LötjönenCombinostics, Tampere, Finland.
Teemu PaajanenFinnish Institute of Occupational Health, Helsinki, Finland.
Juha O RinneTurku PET Centre, University of Turku, Turku, Finland.
Hilkka SoininenInstitute of Clinical Medicine/Neurology, University of Eastern Finland, Kuopio, Finland.
Miia KivipeltoInstitute of Clinical Medicine/Neurology, University of Eastern Finland, Kuopio, Finland.
Alina SolomonInstitute of Clinical Medicine/Neurology, University of Eastern Finland, Kuopio, Finland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The importance of early interventions in Alzheimer's disease (AD) emphasizes the need to accurately and efficiently identify at-risk individuals. Although many dementia prediction models have been developed, there are fewer studies focusing on detection of brain pathology. We developed a model for identification of amyloid-PET positivity using data on demographics, vascular factors, cognition,

Indexed as

Alzheimer’s diseaseamyloid betaapolipoprotein Ecognitionmachine learningmagnetic resonance imagingpositron emission tomography

Identifiers

PMID32848707
PMCPMC7406705

What OpenQuestion holds

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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.