Evidence map›Paper›PMID 34345420›Full record

ArticleClinical kidney journal2021

Predictive value of triglyceride/high-density lipoprotein cholesterol for major clinical outcomes in advanced chronic kidney disease: a nationwide population-based study.

Yaerim Kim, Soojin Lee, Yeonhee Lee, Min Woo Kang, Sehoon Park, Sanghyun Park, Kyungdo Han, Jin Hyuk Paek, Woo Yeong Park, Kyubok Jin and 8 more

Open access · goldAbstract read
In one paragraph

Article in Clinical kidney journal, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
2.2field-weighted citation impact, top 11% 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

14 citing papers in PubMed, 19 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

18 authors at 5 institutions in 1 country.

Yaerim KimDepartment of Internal Medicine, Keimyung University School of Medicine, Daegu, Korea.
Soojin LeeDepartment of Internal Medicine, Seoul National University Hospital, Seoul, Korea.
Yeonhee LeeDepartment of Internal Medicine, Seoul National University Hospital, Seoul, Korea.
Min Woo KangDepartment of Internal Medicine, Seoul National University Hospital, Seoul, Korea.
Sehoon ParkDepartment of Biomedical Sciences, Seoul National University College of Medicine, Seoul, Korea.
Sanghyun ParkDepartment of Medical Statistics, College of Medicine, Catholic University of Korea, Seoul, Korea.
Kyungdo HanDepartment of Statistics and Actuarial Science, Soongsil University, Seoul, Korea.
Jin Hyuk PaekDepartment of Internal Medicine, Keimyung University School of Medicine, Daegu, Korea.
Woo Yeong ParkDepartment of Internal Medicine, Keimyung University School of Medicine, Daegu, Korea.
Kyubok JinDepartment of Internal Medicine, Keimyung University School of Medicine, Daegu, Korea.
Seugyeup HanDepartment of Internal Medicine, Keimyung University School of Medicine, Daegu, Korea.
Seung Seok HanDepartment of Internal Medicine, Seoul National University Hospital, Seoul, Korea.
Hajeong LeeDepartment of Internal Medicine, Seoul National University Hospital, Seoul, Korea.
Jung Pyo LeeDepartment of Internal Medicine, SMG-SNU Boramae Medical Center, Seoul, Korea.
Kwon Wook JooDepartment of Internal Medicine, Seoul National University Hospital, Seoul, Korea.
Chun Soo LimDepartment of Internal Medicine, SMG-SNU Boramae Medical Center, Seoul, Korea.
Yon Su KimDepartment of Internal Medicine, Seoul National University Hospital, Seoul, Korea.
Dong Ki KimDepartment of Internal Medicine, Seoul National University Hospital, Seoul, Korea.ORCID https://orcid.org/0000-0003-0137-5261
Seoul National University · KRSeoul National University Hospital · KRKeimyung University · KRSNUH SMG-SNU Boramae Medical Center · KRSoongsil University · KR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDyslipidemia is an essential parameter in the prediction of cardiovascular disease (CVD). We aimed to explore whether lipid profiles could predict major outcomes in patients with advanced chronic kidney disease (CKD).

methodsWe retrospectively reviewed the National Health Insurance Service database for people who received nationwide health screening in 2009. All subjects exposed to a lipid-lowering agent before screening were excluded. The population was divided into control, early [estimated glomerular filtration rate (eGFR) 45-59 mL/min/1.73 m

resultsA total of 3 634 873 participants were included in this study, with 404 298 (11.1%) and 66 805 (1.8%) having early and advanced CKD, respectively. For all populations, levels of triglyceride/high-density lipoprotein cholesterol (TG/HDL-C) showed a linear association with major cardiovascular and cerebrovascular events (MACCEs) and all-cause mortality, while low-density lipoprotein cholesterol (LDL-C) showed a different pattern of association with MACCEs (linear association) from all-cause mortality (U-shaped association). The significance between the levels of LDL-C and outcomes was attenuated in the advanced CKD group. For TG/HDL-C, although the significance was decreased, the linear patterns with both MACCEs and all-cause mortality were maintained in the advanced CKD group.

conclusionsThe pattern and significance of lipid profiles were different according to the grade of kidney function. TG/HDL-C should be additionally considered as a predictive marker for CVD and mortality along with LDL-C in patients with CKD.

Indexed as

all-cause mortalitycardiovascular diseasechronic kidney diseaselipid profilestriglyceride/HDL cholesterol

Identifiers

PMID34345420
PMCPMC8323149
OpenAlexW3118007909

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.