Evidence map›Paper›PMID 33304270›Full record

ReviewFrontiers in pharmacology2020

Uric Acid and Cardiovascular Disease: An Update From Molecular Mechanism to Clinical Perspective.

Wei Yu, Ji-Dong Cheng

Open access · goldAbstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Frontiers in pharmacology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 176 papers, 7 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
176citing papers in PubMed, 7 pooled it
22.6field-weighted citation impact, top 1% 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

176 citing papers in PubMed, 7 syntheses or guidelines pooled it, 333 citations in OpenAlex.

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116 more citing papers are in PubMed but not listed here.

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

2 authors at 1 institution in 1 country.

Wei YuDepartment of Internal Medicine, Xiang'an Hospital of Xiamen University, Xiamen, China.
Ji-Dong ChengDepartment of Internal Medicine, Xiang'an Hospital of Xiamen University, Xiamen, China.
Xiamen University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Uric acid (UA) is the end product of purine nucleotide metabolism in the human body. Hyperuricemia is an abnormally high level of UA in the blood and may result in arthritis and gout. The prevalence of hyperuricemia has been increasing globally. Epidemiological studies have shown that UA levels are positively correlated with cardiovascular diseases, including hypertension, atherosclerosis, atrial fibrillation (AF), and heart failure (HF). Hyperuricemia promotes the occurrence and development of cardiovascular diseases by regulating molecular signals, such as inflammatory response, oxidative stress, insulin resistance/diabetes, endoplasmic reticulum stress, and endothelial dysfunction. Despite extensive research, the underlying molecular mechanisms are still unclear. Allopurinol, a xanthine oxidase (XO) inhibitor, has been shown to improve cardiovascular outcomes in patients with HF, coronary heart disease (CHD), type 2 diabetes (T2D), and left ventricular hypertrophy (LVH). Whether febuxostat, another XO inhibitor, can improve cardiovascular outcomes as well as allopurinol remains controversial. Furthermore, it is also not clear whether UA-lowering treatment (ULT) can benefit patients with asymptomatic hyperuricemia. In this review, we focus on the latest cellular and molecular findings of cardiovascular disease associated with hyperuricemia and clinical data about the efficacy of ULT in patients with cardiovascular disease.

Indexed as

cardiovascular diseaseclinical prospectmolecular mechanismtherapeuticsuric acid

Identifiers

PMID33304270
PMCPMC7701250
OpenAlexW3098915518

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.