Evidence map›Paper›PMID 40137399›Full record

ArticleJournal of personalized medicine2025

Sex-Specific Associations Between Dynapenia and Risk of Atherosclerotic Cardiovascular Disease: A Machine-Learning-Based Approach.

Gyumin Lee, Hye-Jin Kim, Heeji Choi, Seung-Ho Shin, Chulho Kim, Sang-Hwa Lee, Jong-Hee Sohn, Jae Jun Lee

Abstract read
In one paragraph

Article in Journal of personalized medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

8 authors.

Gyumin LeeArtificial Intelligence Research Center, Hallym University Sacred Heart Hospital, Chuncheon 24253, Republic of Korea.
Hye-Jin KimArtificial Intelligence Research Center, Hallym University Sacred Heart Hospital, Chuncheon 24253, Republic of Korea.
Heeji ChoiArtificial Intelligence Research Center, Hallym University Sacred Heart Hospital, Chuncheon 24253, Republic of Korea.ORCID 0009-0003-7249-7941
Seung-Ho ShinArtificial Intelligence Research Center, Hallym University Sacred Heart Hospital, Chuncheon 24253, Republic of Korea.ORCID 0000-0001-5624-1821
Chulho KimDepartment of Neurology, Hallym University College of Medicine, Chuncheon 24252, Republic of Korea.ORCID 0000-0001-8762-8340
Sang-Hwa LeeDepartment of Neurology, Hallym University College of Medicine, Chuncheon 24252, Republic of Korea.ORCID 0000-0002-0609-1551
Jong-Hee SohnDepartment of Neurology, Hallym University College of Medicine, Chuncheon 24252, Republic of Korea.ORCID 0000-0003-2656-9222
Jae Jun LeeDepartment of Anesthesiology, Hallym University College of Medicine, Chuncheon 24252, Republic of Korea.

Funding

Hallym University Research Fund (HURF)Korea Health Technology R&D Project through the Korea Health Industry Development Institute (KHIDI), funded by the Ministry of Health & Welfare, Republic of Korea HR21C0198, HI22C1498the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) 2022R1A5A8019303
6 · The paper itself

Abstract

PubMed holds no abstract for this paper.

Indexed as

atherosclerotic cardiovascular diseasecardiovascular disease risk predictiondynapeniamachine learningsex difference

Identifiers

PMID40137399
PMCPMC11942907

What Socratic holds

Textmetadata
LicenceCC BY
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.