Evidence map›Paper›PMID 34901208›Full record

ArticleFrontiers in cardiovascular medicine2021

Elucidation of a Causal Relationship Between Platelet Count and Hypertension: A Bi-Directional Mendelian Randomization Study.

Po-Chun Chiu, Amrita Chattopadhyay, Meng-Chun Wu, Tzu-Hung Hsiao, Ching-Heng Lin, Tzu-Pin Lu

Open access · goldAbstract read
In one paragraph

Article in Frontiers in cardiovascular medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
4.0field-weighted citation impact, top 6% 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

12 citing papers in PubMed, 25 citations in OpenAlex.

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  9. Systemic inflammation markers and the prevalence of hypertension: A NHANES cross-sectional study.Hypertension research : official journal of the Japanese Society of Hypertension · 2023
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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

6 authors at 2 institutions in 1 country.

Po-Chun ChiuDepartment of Public Health, National Taiwan University, Taipei, Taiwan.
Amrita ChattopadhyayBioinformatics and Biostatistics Core, Center of Genomic and Precision Medicine, National Taiwan University, Taipei, Taiwan.
Meng-Chun WuDepartment of Public Health, National Taiwan University, Taipei, Taiwan.
Tzu-Hung HsiaoDepartment of Medical Research, Taichung Veterans General Hospital, Taichung, Taiwan.
Ching-Heng LinDepartment of Medical Research, Taichung Veterans General Hospital, Taichung, Taiwan.
Tzu-Pin LuDepartment of Public Health, National Taiwan University, Taipei, Taiwan.
National Taiwan University · TWTaichung Veterans General Hospital · TW

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Hypertension has been reported as a major risk factor for diseases such as cardiovascular disease, and associations between platelet activation and risk for hypertension are well-established. However, the exact nature of causality between them remains unclear. In this study, a bi-directional Mendelian randomization (MR) analysis was conducted on 15,996 healthy Taiwanese individuals aged between 30 and 70 years from the Taiwan Biobank, recorded between 2008 and 2015. The inverse variance weighted (IVW) method was applied to determine the causal relationship between platelet count and hypertension with single nucleotide polymorphisms as instrumental variables (IVs). Furthermore, to check for pleiotropy and validity of the IVs, sensitivity analyses were performed using the MR-Egger, weighted median and simple median methods. This study provided evidence in support of a positive causal effect of platelet count on the risk of hypertension (odds ratio: 1.149, 95% confidence interval: 1.131-1.578,

Indexed as

bi-directional causal estimationhypertensionMendelian randomizationplatelet countTaiwan Biobank

Identifiers

PMID34901208
PMCPMC8661012
OpenAlexW3216689559

What OpenQuestion holds

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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.