Evidence mapPaperPMID 39834557Full record

ArticleAnnals of neurosciences2025

Association Between BMI and Neurocognitive Functions Among Middle-aged Obese Adults: Preliminary Findings Using Machine-learning (ML)-based Approach.

Dipti Magan, Raj Kumar Yadav, Jitender Aneja, Shivam Pandey

Abstract read
In one paragraph

Article in Annals of neurosciences, 2025. 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
field-weighted citation impact
1 · What the graph read from it

What it found

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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

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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.

  1. 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

4 authors.

Dipti MaganDepartment of Physiology, All India Institute of Medical Sciences, Bathinda, Punjab, India.ORCID https://orcid.org/0000-0003-2982-1294
Raj Kumar YadavDepartment of Physiology, All India Institute of Medical Sciences, New Delhi, Delhi, India.
Jitender AnejaDepartment of Psychiatry, All India Institute of Medical Sciences, Bathinda, Punjab, India.
Shivam PandeyDepartment of Biostatistics, All India Institute of Medical Sciences, New Delhi, Delhi, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Studies suggest that obesity predisposes individuals to developing cognitive dysfunction and an increased risk of dementia, but the nature of the relationship remains largely unexplored for better prognostic predictors. Purpose: This study, the first of its kind in Indian participants with obesity, was intended to explore the use of quantification of different neurocognitive indices with increasing body mass index (BMI) among middle-aged participants with obesity. Additionally, machine-learning models were used to analyse the predictive performance of BMI for different cognitive functions. Methods: In the cross-sectional analytical study, a total of 137 ( Results: Significant ( Conclusion: The preliminary results of the present study support that increased BMI is an important physiological indicator that influences neurocognition and neuroplasticity in individuals with obesity.

Indexed as

body mass indexbrain-derived neurotrophic factorcognitive declinerHealthcaremachine-learning modelsmini-mental state examinationMontreal cognitive assessment

Identifiers

PMID39834557
PMCPMC11742150

What Socratic holds

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LicenceCC BY-NC
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Registered trials

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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.