Evidence map›Paper›PMID 28299524›Full record

ArticleInternational urology and nephrology2017

Lung function and impaired kidney function in relation to metabolic syndrome.

Kayoung Lee

Abstract read
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In one paragraph

Article in International urology and nephrology, 2017. 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
1.8field-weighted citation impact, top 14% 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

2 citing papers in PubMed, 12 citations in OpenAlex.

  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

1 author at 1 institution in 1 country.

Kayoung LeeDepartment of Family Medicine, Busan Paik Hospital, Inje University College of Medicine, 633-165 Gaegum-dong, Busan Jin-Gu, Busan, 614-735, Republic of Korea. fmlky@inje.ac.kr.ORCID http://orcid.org/0000-0002-2816-554X
Inje University Busan Paik Hospital · KR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeThis study aimed to assess the relationships between abnormal lung function and indicators of chronic kidney disease in relation to metabolic syndrome (MetS) by using data from the 2011-2013 Korea National Health and Nutrition Examination Survey.

methodsUsing the data of 8551 Korean adults (3798 men, 4753 women, ≥40 years), lung function categories [obstructive lung disease (OLD), restrictive lung disease (RLD), and non-obstructive/non-restrictive lung disease (reference group)] were defined for each gender. Albuminuria and low estimated glomerular filtration rate (eGFR) were defined as urine albumin-to-creatinine ratio ≥30 mg/g and eGFR < 60 mL/min/1.73 m

resultsCompared to the reference group, low eGFR was associated with higher odds for RLD in men and RLD or OLD in women when they did not have MetS. In those with MetS, low eGFR was associated with higher odds for OLD in men and RLD or OLD in women. Albuminuria was associated with higher odds for RLD in men who did not have MetS, while it was associated with higher odds for RLD or OLD in men and women who had MetS.

conclusionsAbnormal lung function was associated with increased odds for chronic kidney disease indicators, when combined with MetS in both gender. Even in those without MetS, RLD in men was associated with increased odds for low eGFR or albuminuria, while RLD or OLD in women was associated with increased odds for low eGFR.

Indexed as

AdultAgedAlbuminuriaBlood GlucoseBlood PressureCholesterol, HDLCreatinineCross-Sectional StudiesFemaleForced Expiratory VolumeGlomerular Filtration RateHumansHyperglycemiaHypertensionLung Diseases, ObstructiveMaleBlood GlucoseCholesterol, HDLCreatinineTriglyceridesAlbuminuriaEstimated glomerular filtration rateLung functionMetabolic syndrome

Identifiers

PMID28299524
OpenAlexW2606152172

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.