Evidence map›Paper›PMID 35033174›Full record

ArticleDiabetology & metabolic syndrome2022

Association of metabolic syndrome traits with urinary biomarkers in Japanese adults.

Keiko Kabasawa, Michihiro Hosojima, Yumi Ito, Kazuo Matsushima, Junta Tanaka, Masanori Hara, Kazutoshi Nakamura, Ichiei Narita, Akihiko Saito

Abstract read
In one paragraph

Article in Diabetology & metabolic syndrome, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Review
  3. Cardio-kidney-metabolic (CKM) framework: A nephrologist's perspective.Archives of endocrinology and metabolism · 2025
    Review
  4. Review
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

9 authors.

Keiko KabasawaDepartment of Health Promotion Medicine, Niigata University Graduate School of Medical and Dental Sciences, Niigata, Japan. keikoyk@med.niigata-u.ac.jp.
Michihiro HosojimaDepartment of Clinical Nutrition Science, Kidney Research Center, Niigata University Graduate School of Medical and Dental Sciences, Niigata, Japan.
Yumi ItoDepartment of Health Promotion Medicine, Niigata University Graduate School of Medical and Dental Sciences, Niigata, Japan.
Kazuo MatsushimaYukiguni Yamato City Hospital, Minamiuonuma, Niigata, Japan.
Junta TanakaDepartment of Health Promotion Medicine, Niigata University Graduate School of Medical and Dental Sciences, Niigata, Japan.
Masanori HaraIwamuro Health Promotion Center, Niigata, Japan.
Kazutoshi NakamuraDivision of Preventive Medicine, Niigata University Graduate School of Medical and Dental Sciences, Niigata, Japan.
Ichiei NaritaDepartment of Health Promotion Medicine, Niigata University Graduate School of Medical and Dental Sciences, Niigata, Japan.
Akihiko SaitoDepartment of Applied Molecular Medicine, Kidney Research Center, Niigata University Graduate School of Medical and Dental Sciences, Niigata, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAlthough metabolic syndrome traits are risk factors for chronic kidney disease, few studies have examined their association with urinary biomarkers.

methodsUrinary biomarkers, including A-megalin, C-megalin, podocalyxin, albumin, α

resultsParticipants had a mean body mass index, estimated glomerular filtration rate (eGFR), and median ACR of 23.0 kg/m

conclusionsBoth urinary A-megalin and albumin are associated with the clustering number of metabolic syndrome traits. Further research on urinary A-megalin is warranted to examine its role as a potential marker of kidney damage from metabolic risk factors.

Indexed as

AlbuminuriaChronic kidney diseaseMegalinMetabolic syndromeProximal renal tubuleUrinary biomarker

Identifiers

PMID35033174
PMCPMC8760661

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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.