Evidence map›Paper›PMID 30400932›Full record

ArticleLipids in health and disease2018

Impact of dyslipidemia on 24-h urine composition in adults without urolithiasis.

Chao Cai, Zanlin Mai, Tuo Deng, Zhijian Zhao, Wei Zhu, Yaoan Wen, Xiaolu Duan, Wenqi Wu, Guohua Zeng

Open access · goldAbstract read
In one paragraph

Article in Lipids in health and disease, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
1.3field-weighted citation impact, top 18% 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

15 citing papers in PubMed, 24 citations in OpenAlex.

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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

9 authors at 4 institutions in 1 country.

Chao CaiDepartment of Urology, Minimally Invasive Surgery Center, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.
Zanlin MaiDepartment of Urology, Minimally Invasive Surgery Center, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.
Tuo DengDepartment of Urology, Minimally Invasive Surgery Center, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.
Zhijian ZhaoDepartment of Urology, Minimally Invasive Surgery Center, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.
Wei ZhuDepartment of Urology, Minimally Invasive Surgery Center, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.
Yaoan WenDepartment of Urology, Minimally Invasive Surgery Center, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.
Xiaolu DuanDepartment of Urology, Minimally Invasive Surgery Center, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.
Wenqi WuDepartment of Urology, Minimally Invasive Surgery Center, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.
Guohua ZengDepartment of Urology, Minimally Invasive Surgery Center, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China. gzgyzgh@vip.sina.com.
Key Laboratory of Guangdong Province · CNGuangzhou Medical University · CNFirst Affiliated Hospital of Guangzhou Medical University · CNGuangzhou Institute of Dermatology · CN

Funding

Foundation for the National Institutes of Health 81670643Guangzhou Science, Technology and Innovation Commission 201604020001National Natural Science Foundation of China 81402430National Natural Science Foundation of China 81602541Natural Science Foundation of Guangdong Province 2016A030310276the Collaborative Innovation Project of Guangzhou Education Bureau 1201620011the Guangzhou Science Technology and Innovation Commission 201704020193the Science and Technology Planning Project of Guangdong Province 2017B030314108
6 · The paper itself

Abstract

purposesTo evaluate the influence of dyslipidemia on 24-h urine composition in adults who were non-stone formers (NF).

methodsSamples for 24-h urine composition were analyzed from 584 NF adults without urolithiasis in a national six-city-based epidemiologic study. The samples were divided into groups based on total cholesterol (TC), triglycerides (TG), high-density lipoprotein (HDL), and low-density lipoprotein (LDL). The groups were compared based on demographic data and each component of 24-h urinalysis.

resultsThe numbers of participants in high TG, high TC, high LDL, and low HDL were 106, 175, 147, and 59, respectively. The high TG group had increased urinary excretions of oxalate [mean difference (MD) = 0.032 mmol, 95% confidence interval (CI): 0.000-0.065] and potassium (MD = 4.298 mmol, 95%CI: 0.182-8.414). Increased urinary excretion of calcium (MD = 0.531 mmol, 95%CI: 0.061-1.001), sodium (MD = 41.561 mmol, 95%CI: 9.179-73.942), and chloride (MD = 45.209 mmol, 95%CI: 12.118-78.299) were found in the high TC group. Interestingly, the high LDL group had a decreased urinary excretion of calcium (MD = - 0.573 mmol, 95%CI: -1.048 to - 0.097), oxalate (MD = - 0.038 mmol, 95%CI: -0.07 to - 0.006), sodium (MD = - 53.285 mmol, 95%CI: -85.823 to - 20.748), and chloride (MD = - 55.809 mmol, 95%CI: -89.035 to - 22.583). Increased urinary excretions of citrate (MD = 0.455 mmol, 95%CI: 0.076-0.835) and magnesium (MD = 0.697 mmol, 95%CI: 0.244-1.149) were found in the low HDL group.

conclusionsThe present study first investigated the effects of dyslipidemia on 24-h urinalysis in NF adults. Of note, high LDL and low HDL were found to be adversely related to kidney stone formation. However, people with high TG and high TC should be cautious of getting kidney stones.

Indexed as

AdultAgedDyslipidemiasFemaleHumansMaleMiddle AgedUrineUrolithiasis24-h urine compositionDyslipidemiaEffectsNon-stone formers

Identifiers

PMID30400932
PMCPMC6220564
OpenAlexW2900446731

What OpenQuestion holds

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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.