Evidence map›Paper›PMID 38994496›Full record

ArticleCardiology research and practice2024

Exploring Hypertrophic Cardiomyopathy Biomarkers through Integrated Bioinformatics Analysis: Uncovering Novel Diagnostic Candidates.

Guanmou Li, Dongqun Lin, Xiaoping Fan, Bo Peng

Abstract read
In one paragraph

Article in Cardiology research and practice, 2024. 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. 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

4 authors.

Guanmou LiZhujiang Hospital of Southern Medical University, Guangzhou 510120, Guangdong, China.
Dongqun LinDepartment of Cardiovascular Surgery Guangdong Provincial Hospital of Chinese Medicine The Second Affiliated Hospital of Guangzhou University of Chinese Medicine The Second Clinical College of Guangzhou University of Chinese Medicine, Guangzhou 510120, Guangdong, China.
Xiaoping FanDepartment of Cardiovascular Surgery Guangdong Provincial Hospital of Chinese Medicine The Second Affiliated Hospital of Guangzhou University of Chinese Medicine The Second Clinical College of Guangzhou University of Chinese Medicine, Guangzhou 510120, Guangdong, China.
Bo PengDepartment of Cardiovascular Surgery Guangdong Provincial Hospital of Chinese Medicine The Second Affiliated Hospital of Guangzhou University of Chinese Medicine The Second Clinical College of Guangzhou University of Chinese Medicine, Guangzhou 510120, Guangdong, China.ORCID https://orcid.org/0009-0002-3434-1885

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

HCM is a heterogeneous monogenic cardiac disease that can lead to arrhythmia, heart failure, and atrial fibrillation. This study aims to identify biomarkers that have a positive impact on the treatment, diagnosis, and prediction of HCM through bioinformatics analysis. We selected the GSE36961 and GSE180313 datasets from the Gene Expression Omnibus (GEO) database for differential analysis. GSE36961 generated 6 modules through weighted gene co-expression network analysis (WGCNA), with the green and grey modules showing the highest positive correlation with HCM (green module: cor = 0.88,

Identifiers

PMID38994496
PMCPMC11239233

What OpenQuestion 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 OpenQuestion graph.