Evidence map›Paper›PMID 39910118›Full record

ArticleScientific reports2025

Remnant cholesterol and its variability independent of low density lipoprotein cholesterol predict metabolic dysfunction associated steatotic liver disease.

Yuting Sun, Xinlei Miao, Manling Hu, Xiaoling Xie, Shuang Liu, Ziping Song, Jiayi Deng, Fei Xu, Meng Li, Yangxuan He and 1 more

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Review
  2. Review
  3. Article
  4. Article
  5. Review
  6. Observational
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

11 authors.

Yuting SunHealth Management Center, The Second Hospital of Dalian Medical University, No. 467 Zhongshan Road, Shahekou District, Dalian, 116023, Liaoning, China.
Xinlei MiaoHealth Management Center, The Second Hospital of Dalian Medical University, No. 467 Zhongshan Road, Shahekou District, Dalian, 116023, Liaoning, China.
Manling HuHealth Management Center, The Second Hospital of Dalian Medical University, No. 467 Zhongshan Road, Shahekou District, Dalian, 116023, Liaoning, China.
Xiaoling XieHealth Management Center, The Second Hospital of Dalian Medical University, No. 467 Zhongshan Road, Shahekou District, Dalian, 116023, Liaoning, China.
Shuang LiuHealth Management Center, The Second Hospital of Dalian Medical University, No. 467 Zhongshan Road, Shahekou District, Dalian, 116023, Liaoning, China.
Ziping SongHealth Management Center, The Second Hospital of Dalian Medical University, No. 467 Zhongshan Road, Shahekou District, Dalian, 116023, Liaoning, China.
Jiayi DengHealth Management Center, The Second Hospital of Dalian Medical University, No. 467 Zhongshan Road, Shahekou District, Dalian, 116023, Liaoning, China.
Fei XuHealth Management Center, The Second Hospital of Dalian Medical University, No. 467 Zhongshan Road, Shahekou District, Dalian, 116023, Liaoning, China.
Meng LiHealth Management Center, The Second Hospital of Dalian Medical University, No. 467 Zhongshan Road, Shahekou District, Dalian, 116023, Liaoning, China.
Yangxuan HeHealth Management Center, The Second Hospital of Dalian Medical University, No. 467 Zhongshan Road, Shahekou District, Dalian, 116023, Liaoning, China.
Song LengHealth Management Center, The Second Hospital of Dalian Medical University, No. 467 Zhongshan Road, Shahekou District, Dalian, 116023, Liaoning, China. dllengsong@163.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study aimed to determine whether remnant cholesterol (RC) and its variability can predict the onset of metabolic dysfunction-associated steatotic liver disease (MASLD) independently of low-density lipoprotein cholesterol (LDL-C) levels. A longitudinal cohort study involving 43,065 participants who underwent at least two physical examinations was conducted. This study used Cox proportional hazards models to assess the relationships among RC quartile levels (Q1-Q4), visit-to-visit variability, and the risk of MASLD. This variability was quantified using several metrics: standard deviation (SD), logSD, average real variability (ARV), logARV, mean absolute deviation (MAD), and logMAD. Concurrently, this study utilized a combined analysis of RC and LDL-C groups to assess the independent risk of MASLD associated with RC. During a mean visit-to-visit of 3.19 years (SD 2.06 years), 8374 patients (19.45%) developed MASLD. Compared with Q1, Q4 was associated with a significantly greater risk of MASLD (hazard ratio [HR] 1.309, 95% confidence interval [CI] 1.220-1.403, P < 0.001). The fully adjusted Cox model revealed that the HRs of SD, logSD, ARV, logARV, MAD and logMAD were 1.400 (95% CI 1.305-1.502), 1.278 (95% CI 1.188-1.374), 1.152 (95% CI 1.079-1.229), 1.183 (95% CI 1.140-1.227), 1.578 (95% CI 1.433-1.737) and 1.263 (95% CI 1.175-1.358), respectively. In both LDL-C subgroups (≥ 3.4 mmol/L and < 3.4 mmol/L), high baseline RC was associated with elevated MASLD risk (HR 1.208, 95% CI 1.148-1.270, P < 0.001; HR 1.246, 95% CI 1.129-1.374, P < 0.001). RC levels were independently associated with MASLD in healthy individuals, irrespective of LDL-C level. The variability of RC during visit-to-visit periods provides a predictive marker for identifying individuals at heightened risk of MASLD.

Indexed as

CholesterolCholesterol, LDLFatty LiverTriglyceridesAdultAgedBiomarkersFemaleHumansLongitudinal StudiesMaleMiddle AgedProportional Hazards ModelsRisk FactorsBiomarkersCholesterolCholesterol, LDLTriglyceridesJoint analysisNovel lipid biomarkersParticipation in healthy check-upsPrimary preventionVisit-to-visit variability

Identifiers

PMID39910118
PMCPMC11799198

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.