Evidence map›Paper›PMID 40123646›Full record

ReviewJRSM cardiovascular disease

Non-alcoholic fatty liver disease (NAFLD) and its association to cardiovascular disease: A comprehensive meta-analysis.

Irina Lubomirova Mladenova, Eu Fon Tan, Jing Yong Ng, Pankaj Sharma

Abstract readReview
In one paragraph

Review in JRSM cardiovascular disease. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

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

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. 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

4 authors.

Irina Lubomirova MladenovaImperial College School of Medicine, Imperial College London, London, UK.ORCID https://orcid.org/0009-0003-9274-484X
Eu Fon TanQueen Mary University of London, London, UK.
Jing Yong NgQueen Mary University of London, London, UK.
Pankaj SharmaInstitute of Cardiovascular Research, Royal Holloway University, Egham, Greater London, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Non-alcoholic fatty liver disease (NAFLD) affects up to nearly a third of the Western population and has been inconsistently associated with cardiovascular diseases (CVDs). Therefore, we conducted a comprehensive meta-analysis to quantify the correlation of NAFLD with all major vascular diseases, acute coronary syndrome (ACS), subclinical atherosclerosis and endothelial dysfunction. Methods: We searched PubMed and Embase for studies looking at the relationship between NAFLD and cardiovascular diseases published through September 2023. The parameters we used to assess cardiovascular diseases include acute coronary syndrome, brachial flow-mediated dilatation (FMD), serum asymmetric dimethylarginine (ADMA), carotid intima-media thickness (CIMT), and carotid stenosis (>50%). Data from these studies were then collected and meta-analysis was performed using the random effects model. RevMan v5.4 was used for statistical analysis. Results: We interrogated a total of 114 publications which met our inclusion criteria. NAFLD patients showed statistically significant reduction in FMD% [MD: -4.83 (95% CI: -5.84 to 3.81, Conclusion: NAFLD is a strong predictor for endothelial dysfunction, subclinical atherosclerosis and cardiovascular disease. Further studies are required to determine whether incidental findings of fatty liver on abdominal ultrasonography should prompt the need for detailed assessment of other CVD risk factors.

Indexed as

atherosclerosiscardiovascularmeta-analysisNon-alcoholic fatty liver diseaseprediction

Identifiers

PMID40123646
PMCPMC11930486

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.