Evidence map›Paper›PMID 33526971›Full record

ReviewInternational journal of medical sciences2021

Environmental Pollution and Chronic Kidney Disease.

Hui-Ju Tsai, Pei-Yu Wu, Jiun-Chi Huang, Szu-Chia Chen

Open access · goldAbstract readReview
In one paragraph

Review in International journal of medical sciences, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 50 papers.

0numbers the graph read from it
0cells of the map it votes in
50citing papers in PubMed
9.8field-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

50 citing papers in PubMed, 135 citations in OpenAlex.

  1. Article
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  7. Pollutant-regulated mitophagy: new perspectives in environmental toxicology.Apoptosis : an international journal on programmed cell death · 2026
    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

4 authors at 2 institutions in 1 country.

Hui-Ju TsaiDepartment of Family Medicine, Kaohsiung Municipal Ta-Tung Hospital, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohsiung, Taiwan.
Pei-Yu WuDivision of Nephrology, Department of Internal Medicine, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohsiung, Taiwan.
Jiun-Chi HuangDivision of Nephrology, Department of Internal Medicine, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohsiung, Taiwan.
Szu-Chia ChenResearch Center for Environmental Medicine, Kaohsiung Medical University, Kaohsiung, Taiwan.
Kaohsiung Medical University Chung-Ho Memorial Hospital · TWKaohsiung Municipal Hsiao-Kang Hospital · TW

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Chronic kidney disease (CKD) is a global public health problem associated with high rates of morbidity and mortality due to end-stage renal disease and cardiovascular disease. Safe and effective medications to reverse or stabilize renal function in patients with CKD are lacking, and hence it is important to identify modifiable risk factors associated with worsening kidney function. Environmental pollutants, including metals, air pollutant, phthalate and melamine can potentially increase the risk of CKD or accelerate its progression. In this review, we discuss the epidemiological evidence for the association between environmental pollution and kidney disease, including heavy metals, air pollution and other environmental nephrotoxicants in the general population.

Indexed as

Disease ProgressionEnvironmental ExposureEnvironmental PollutantsEnvironmental PollutionHumansRenal Insufficiency, ChronicRisk FactorsEnvironmental Pollutantschronic kidney diseaseenvironmental pollutionheavy metal

Identifiers

PMID33526971
PMCPMC7847614
OpenAlexW3118750883

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.