Evidence map›Paper›PMID 39484123›Full record

ArticleReviews in cardiovascular medicine2024

Causal Association of Chronic Venous Insufficiency and Cardiovascular Diseases: A Univariable and Multivariable Mendelian Randomization Study.

Xiaobo Guo, Kui Zhang, Yiping Sun, Ran Dong

Abstract read
In one paragraph

Article in Reviews in cardiovascular medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

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

  1. The cardiovascular impact of chronic venous disease: A systematic review and meta-analysis.Journal of vascular surgery. Venous and lymphatic disorders · 2026
    Pooled it
  2. Review
  3. Article
  4. 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.

Xiaobo GuoDepartment of Cardiac Surgery, Beijing Anzhen Hospital, Capital Medical University, 100029 Beijing, China.
Kui ZhangDepartment of Cardiac Surgery, Beijing Anzhen Hospital, Capital Medical University, 100029 Beijing, China.
Yiping SunDepartment of Cardiac Surgery, Beijing Anzhen Hospital, Capital Medical University, 100029 Beijing, China.
Ran DongDepartment of Cardiac Surgery, Beijing Anzhen Hospital, Capital Medical University, 100029 Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The causal relationship between chronic venous insufficiency (CVI) and cardiovascular diseases (CVDs) has yet to be elucidated. Herein, we implement Mendelian randomization (MR) analysis to investigate the causal association. Methods: A two-sample MR approach using genetic data from FinnGen and genome-wide association studies (GWAS) Catalog was applied to investigate the causal relationship between CVI and CVDs. This study assessed 77 single nucleotide polymorphisms (SNPs) as instrumental variables, employing random-effect inverse-variance-weighted MR, weighted median, Egger regression, Mendelian Randomization Pleiotropy RESidual Sum and Outlier (MR-PRESSO), and Robust Adjusted Profile Score (RAPS) methods. Multivariable MR (MVMR) considered confounding factors. Results: Genetically predicted CVI was associated with reduced heart failure risk (odds ratio (OR) = 0.96, 95% confidence interval (95% CI): 0.93-0.99, Conclusions: This MR study supports an association between CVI and CVDs, which may imply CVI should be monitored during the treatment of heart failure and atrial fibrillation.

Indexed as

atrial fibrillationcardiovascular diseaseschronic venous insufficiencyheart failureMendelian randomization

Identifiers

PMID39484123
PMCPMC11522777

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.