Evidence map›Paper›PMID 39491271›Full record

ArticleRenal failure2024

Lipid metabolism disorders and albuminuria risk: insights from National Health and Nutrition Examination Survey 2001-2018 and Mendelian randomization analyses.

Yangyang Wang, Sen Li

Abstract read
In one paragraph

Article in Renal failure, 2024. 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
–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

2 citing papers in PubMed.

  1. Article
  2. Article
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

2 authors.

Yangyang WangSecond Medical College of Wenzhou Medical University, Wenzhou, China.
Sen LiSchool of Basic Medical Sciences, Wenzhou Medical University, Wenzhou, China.ORCID 0009-0009-5716-8617

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPrevious studies have revealed an underlying connection between abnormal lipid metabolism and albuminuria. We aim to investigate the causal relationship between lipid metabolism disorders and the risk of albuminuria from both a population and genetic perspective.

methodsA cross-sectional study was conducted by using data from the National Health and Nutrition Examination Survey (NHANES) 2001-2018. Multivariable-adjusted logistic regression, subgroup analysis, interaction tests and restricted cubic spline (RCS) were employed statistically. Mendelian randomization (MR) analysis was performed to validate the causal relationship between exposure and outcome to mitigate confounding factors and reverse causation interference.

resultsAfter adjusting for confounders, HDL levels (1.03-2.07 nmol/L) were associated with a reduced risk of albuminuria. In contrast, elevated cholesterol levels (>6.2 nmol/L) and triglyceride levels (>2.3 nmol/L) were associated with an increased risk of albuminuria. Serum triglyceride concentration emerged as a potential risk factor for albuminuria. In MR analysis, a reduced risk of albuminuria was associated with serum total HDL level (IVW: OR = 0.91, 95% CI = 0.86-0.97,

conclusionA causal relationship exists between serum lipid metabolism disorder and albuminuria risk. Further validation of additional blood lipid metabolism biomarkers is imperative for future studies.

Indexed as

AlbuminuriaMendelian Randomization AnalysisNutrition SurveysTriglyceridesAdultAgedCross-Sectional StudiesFemaleHumansLipid Metabolism DisordersLogistic ModelsMaleMiddle AgedRisk FactorsUnited StatesTriglyceridesAlbuminuriaLipid metabolism disorderMendelian randomizationNational Health and Nutrition Examination Survey

Identifiers

PMID39491271
PMCPMC11536668

What Socratic holds

Textmetadata
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 Socratic graph.