Evidence map›Paper›PMID 40249462›Full record

ArticleHormones (Athens, Greece)2025

Association of long-term remnant cholesterol with the incidence of chronic kidney disease in a high-risk population.

Ping Zhang, Yu-Hong Liu, Wen-Yan Xiong, Yi-Bing Fan, Xiao-Lin Zhu, Kun Zhou, Hui Li

Abstract read
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In one paragraph

Article in Hormones (Athens, Greece), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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

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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

7 authors.

Ping Zhang *Nanchang First Hospital, Nanchang, China.
Yu-Hong Liu *The Collaboration Unit for State Key Laboratory of Infectious Disease Prevention and Control, Jiangxi Provincial Health Commission Key Laboratory of Pathogenic Diagnosis and Genomics of Emerging Infectious Diseases, Nanchang Center for Disease Control and Prevention, Nanchang, China.
Wen-Yan XiongThe Collaboration Unit for State Key Laboratory of Infectious Disease Prevention and Control, Jiangxi Provincial Health Commission Key Laboratory of Pathogenic Diagnosis and Genomics of Emerging Infectious Diseases, Nanchang Center for Disease Control and Prevention, Nanchang, China.
Yi-Bing FanThe Collaboration Unit for State Key Laboratory of Infectious Disease Prevention and Control, Jiangxi Provincial Health Commission Key Laboratory of Pathogenic Diagnosis and Genomics of Emerging Infectious Diseases, Nanchang Center for Disease Control and Prevention, Nanchang, China.
Xiao-Lin ZhuThe Collaboration Unit for State Key Laboratory of Infectious Disease Prevention and Control, Jiangxi Provincial Health Commission Key Laboratory of Pathogenic Diagnosis and Genomics of Emerging Infectious Diseases, Nanchang Center for Disease Control and Prevention, Nanchang, China.
Kun ZhouThe Collaboration Unit for State Key Laboratory of Infectious Disease Prevention and Control, Jiangxi Provincial Health Commission Key Laboratory of Pathogenic Diagnosis and Genomics of Emerging Infectious Diseases, Nanchang Center for Disease Control and Prevention, Nanchang, China.
Hui LiThe Collaboration Unit for State Key Laboratory of Infectious Disease Prevention and Control, Jiangxi Provincial Health Commission Key Laboratory of Pathogenic Diagnosis and Genomics of Emerging Infectious Diseases, Nanchang Center for Disease Control and Prevention, Nanchang, China. lihuinccdc@163.com.ORCID http://orcid.org/0009-0003-8341-7740

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BACKGROUND AND

aimsChronic kidney disease (CKD) is creating an ever heavier global health burden with population ageing. This study aimed to examine the longitudinal associations of remnant cholesterol (RC) with CKD morbidity in a large high-risk population (type 2 diabetes and hypertension).

methodsA total of 11,881 participants who participated in annual health examinations from 2021 to 2023 were included in our analysis. The Cox proportional hazards model was performed to analyze the associations of baseline RC, cumulative RC, and variability of RC with CKD morbidity. The cross-lagged panel analysis was used to examine the temporal relationship between RC and renal function.

resultsThe results of the multivariable-adjusted models showed that higher baseline, cumulative RC, and variability of RC were related to higher risks of developing CKD, the adjusted HR (95% CI) comparing tertile 3 with tertile 1 were 1.26 (95% CI 1.10-1.45), 1.33 (95% CI 1.16-1.52), 1.36 (95% CI 1.20-1.55), respectively. Stratified analysis found that gender did not change these associations. Compared with individuals in the low cumulative and variability RC group, those in the high cumulative and variability RC group had a 1.62 times higher risk of CKD (95% CI: 1.34-1.96). The cross-lagged panel analysis showed that the increase in RC levels may precede the decrease in eGFR.

conclusionsHigh baseline level, cumulative exposure to RC, and variability of RC are associated with increased CKD risk. Therefore, monitoring RC-related parameters is crucial to delay the occurrence and development of CKD in high-risk populations.

Indexed as

CholesterolDiabetes Mellitus, Type 2Renal Insufficiency, ChronicAgedFemaleHumansHypertensionIncidenceLongitudinal StudiesMaleMiddle AgedRisk FactorsCholesterolChronic kidney diseaseHypertensionRemnant cholesterolType 2 diabetes

Identifiers

PMID40249462

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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.