Evidence map›Paper›PMID 39390048›Full record

ArticleScientific reports2024

Effects of multiple fluid intake on Urolithiasis by mendelian randomization study.

Qian Zhang, Zedan Guo, JinYuan Zhang, Hang Liu, Li Yi

Abstract read
In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

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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

2 citing papers in PubMed.

  1. Article
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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.

Qian ZhangDepartment of Medical Administration, Peking University Shenzhen Hospital, Peking University, Shenzhen, China.
Zedan GuoPKU-Shenzhen Clinical Institute of Shantou University Medical College, Shenzhen, China.
JinYuan ZhangShantou University Medical College, Shantou, China.
Hang LiuDepartment of Neurology, Peking University Shenzhen Hospital, Peking University, Lianhua Road 1120, Futian District, 518036, Shenzhen, Guangdong Province, China.
Li YiDepartment of Neurology, Peking University Shenzhen Hospital, Peking University, Lianhua Road 1120, Futian District, 518036, Shenzhen, Guangdong Province, China. yilitj@hotmail.com.

Funding

National Outstanding Youth Science Fund Project of National Natural Science Foundation of China 22067015The Shenzhen Science and Technology Innovation Project JCYJ20190822090801701
6 · The paper itself

Abstract

Urolithiasis, a common and recurrent condition, imposes a significant global health burden. This study investigates the causal relationship between various types of fluid intake and urolithiasis using univariable and multivariable Mendelian randomization (MR) approaches. Genetic data for urolithiasis were obtained from the FinnGen Consortium (n = 400,681), while genetic measures for nine fluid types were sourced from meta-analyses of genome-wide association studies (GWAS). The analysis revealed that genetically predicted coffee intake (OR: 0.571, 95% confidence interval (CI): 0.341-0.958, p = 0.034) and ground coffee intake (OR: 0.219, 95% CI: 0.005-0.923, p = 0.038) were protective factors for upper urinary calculi. Additionally, a standard deviation (SD) increase in tea intake was associated with a 53% reduction in risk (OR: 0.473, 95% CI: 0.320-0.700, p < 0.001). Conversely, milk intake (OR: 1.072, 95% CI: 1.018-1.130) and alcohol intakefrequency (OR: 1.304, 95% CI: 1.083-1.570, p = 0.005) increased the risk of upper urinary calculi. These findings highlight the association of tea with reduced risk of urolithiasis, instead for milk and alcohol intake, in formulating prevention strategies for urolithiasis.

Indexed as

Genome-Wide Association StudyMendelian Randomization AnalysisTeaUrolithiasisAlcohol DrinkingCoffeeDrinkingFemaleHumansMaleMilkPolymorphism, Single NucleotideRisk FactorsCoffeeTeaBeveragesFinnGenFluid intakeMendelian randomizationUK BiobankUrinary calculi

Identifiers

PMID39390048
PMCPMC11467323

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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.