Evidence map›Paper›PMID 37035310›Full record

ArticleFrontiers in medicine2023

Genetically predicted green tea intake and the risk of arterial embolism and thrombosis.

Lingmei Jia, Yali Chen, Chang Liu, Yinyin Luan, Min Jia

Open access · goldAbstract read
In one paragraph

Article in Frontiers in medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
1.3field-weighted citation impact, top 21% of its field
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

3 citing papers in PubMed, 5 citations in OpenAlex.

  1. Review
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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

5 authors at 2 institutions in 1 country.

Lingmei JiaCardiovascular Medicine Department, The Second Hospital of Hebei Medical University, Shijiazhuang, China.
Yali ChenCardiovascular Medicine Department, The Second Hospital of Hebei Medical University, Shijiazhuang, China.
Chang LiuCardiovascular Medicine Department, The Second Hospital of Hebei Medical University, Shijiazhuang, China.
Yinyin LuanCardiovascular Medicine Department, The Second Hospital of Hebei Medical University, Shijiazhuang, China.
Min JiaCardiovascular Medicine Department, The Second Hospital of Hebei Medical University, Shijiazhuang, China.
Second Hospital of Hebei Medical University · CNHebei Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: In previous observational studies, green tea intake has been demonstrated to protect against arterial embolism and thrombosis. However, whether there is a causative connection between green tea intake and arterial embolism and thrombosis is currently unclear. Methods: A two-sample Mendelian randomization (MR) study has been designed to explore whether there is a causal association between green tea intake and arterial embolism and thrombosis by acquiring exposure and outcome data from previously published research. Data from the MRC-IEU (data on green tea intake, 64,949 participants) consortium and the FinnGen project (data on arterial embolism and thrombosis, 278 cases of arterial thrombosis and 92,349 control participants) has been utilized to determine the causal impact of green tea intake on arterial embolism and thrombosis. Results: We found that genetically predicted green tea intake was causally associated with a lower risk of arterial embolism and thrombosis (IVW odds ratio [OR] per SD decrease in green tea intake = 0.92 [95% confidence interval, 0.85-0.99]; Conclusions: Our study provided causal evidence that genetically predicted green tea intake may be a protective factor against arterial embolism and thrombosis.

Indexed as

arterial embolism and thrombosisgenome-wide association studygreen tea intakeischemic heart diseaseMendelian randomizationstroke

Identifiers

PMID37035310
PMCPMC10075307
OpenAlexW4353082264

What OpenQuestion holds

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LicenceCC BY
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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.