Evidence map›Paper›PMID 37428365›Full record

ArticleGeroScience2024

Cognitive and physical age gaps in relation to mild cognitive impairment and behavioral phenotypes.

Junhong Yu, Ted Kheng Siang Ng, Rathi Mahendran

Abstract read
In one paragraph

Article in GeroScience, 2024. 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

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

2 citing papers in PubMed.

  1. Review
  2. 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

3 authors.

Junhong YuPsychology, School of Social Sciences, Nanyang Technological University, 48 Nanyang Avenue, 639798, Singapore, Singapore. junhong.yu@ntu.edu.sg.ORCID 0000-0002-2563-9658
Ted Kheng Siang NgDepartment of Internal Medicine, Rush University Medical Center, Illinois, Chicago, USA.ORCID 0000-0001-7348-0410
Rathi MahendranDepartment of Psychological Medicine, Mind Science Centre, Yong Loo Lin School of Medicine, National University of Singapore, 10 Medical Drive, Singapore, 117597, Singapore. pcmrathi@nus.edu.sg.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We can study how fast our biological aging clocks tick by calculating the difference (i.e., age gaps) between machine learning estimations of biological age and chronological age. While this approach has been increasingly used to study various aspects of aging, few had applied this approach to study cognitive and physical age gaps; not much is known about the behavioral and neurocognitive factors associated with these age gaps. In the present study, we examined these age gaps in relation to behavioral phenotypes and mild cognitive impairment (MCI) among community-dwelling older adults. Participants (N = 822, Age

Indexed as

Cognitive DysfunctionAgedAgingCognitionHumansIndependent LivingPhenotypeAttitudesCognitive agingLifestylePhysical fitnessWell-being

Identifiers

PMID37428365
PMCPMC10828169

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.