Evidence map›Paper›PMID 38616180›Full record

ArticleRenal failure2024

Text mining of hypertension researches in the west Asia region: a 12-year trend analysis.

Mohammad Rezapour, Mohsen Yazdinejad, Faezeh Rajabi Kouchi, Masoomeh Habibi Baghi, Zahra Khorrami, Morteza Khavanin Zadeh, Elmira Pourbaghi, Hassan Rezapour

Abstract read
In one paragraph

Article in Renal failure, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

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

6 citing papers in PubMed.

  1. Article
  2. Review
  3. Review
  4. 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

8 authors.

Mohammad RezapourFaculty Member of the Iranian Ministry of Science, Research and Technology, Tehran, Iran.ORCID 0000-0001-7255-0261
Mohsen YazdinejadArtificial Intelligence, University of Isfahan, Isfahan, Iran.ORCID 0000-0001-7805-6344
Faezeh Rajabi KouchiDepartment of Computer Engineering, Central Tehran Branch, Islamic Azad University, Tehran, Iran.ORCID 0000-0002-4703-9741
Masoomeh Habibi BaghiDepartment of Educational Science, Shahid Beheshti University, Tehran, Iran.ORCID 0000-0002-3683-0490
Zahra KhorramiOphthalmic Epidemiology Research Center, Research Institute for Ophthalmology and Vision Science, Shahid Beheshti University of Medical Sciences, Tehran, Iran.ORCID 0000-0003-0590-4650
Morteza Khavanin ZadehHasheminejad Kidney Center, School of Medicine, Iran University of Medical Sciences, Tehran, Iran.ORCID 0000-0002-5269-4740
Elmira PourbaghiFaculty of Advanced Sciences and Technology, Tehran Medical Sciences, Islamic Azad University, Tehran, Iran.ORCID 0000-0003-2292-3175
Hassan RezapourDepartment of Transportation and Urban Infrastructure Studies, Morgan State University, Baltimore, MD, USA.ORCID 0000-0001-5722-5938

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

More than half of the world population lives in Asia and hypertension (HTN) is the most prevalent risk factor found in Asia. There are numerous articles published about HTN in Eastern Mediterranean Region (EMRO) and artificial intelligence (AI) methods can analyze articles and extract top trends in each country. Present analysis uses Latent Dirichlet allocation (LDA) as an algorithm of topic modeling (TM) in text mining, to obtain subjective topic-word distribution from the 2790 studies over the EMRO. The period of checked studied is last 12 years and results of LDA analyses show that HTN researches published in EMRO discuss on changes in BP and the factors affecting it. Among the countries in the region, most of these articles are related to I.R Iran and Egypt, which have an increasing trend from 2017 to 2018 and reached the highest level in 2021. Meanwhile, Iraq and Lebanon have been conducting research since 2010. The EMRO word cloud illustrates 'BMI', 'mortality', 'age', and 'meal', which represent important indicators, dangerous outcomes of high BP, and gender of HTN patients in EMRO, respectively.

Indexed as

Artificial IntelligenceHypertensionAlgorithmsAsiaData MiningHumansartificial intelligenceChronic kidney diseasehypertensiontext miningtrend detection

Identifiers

PMID38616180
PMCPMC11018045

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.