Evidence mapPaperPMID 40520802Full record

ArticleFrontiers in medicine2025

Association between the atherogenic index of plasma and mortality in the chronic kidney disease population: evidence from NHANES.

Luohua Li, Jinhan Zhao, Mei Yuan, Hongying Jiang

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Article in Frontiers in medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

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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

5 citing papers in PubMed.

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4 · The record

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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

4 authors.

Luohua Li *Department of Nephrology, The Second Hospital Affiliated to Kunming Medical University, Kunming, China.
Jinhan Zhao *The Third Unit of the Department of Hepatology, Beijing Institute of Hepatology, Beijing Youan Hospital, Capital Medical University, Beijing, China.
Mei YuanDepartment of Nephrology, The Second Hospital Affiliated to Kunming Medical University, Kunming, China.
Hongying JiangDepartment of Nephrology, The Second Hospital Affiliated to Kunming Medical University, Kunming, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The atherosclerosis index (AIP) in plasma is a novel indicator closely associated with various metabolic abnormalities, and the bidirectional relationship between metabolic dysfunction and chronic kidney disease (CKD) has been extensively documented. However, evidence regarding the association between AIP and mortality in CKD population remains scarce. This study aims to elucidate the association between baseline AIP levels and both all-cause and specific mortality in a diverse cohort of US adults. Methods: This cohort study utilized data from the National Health and Nutrition Examination Survey (NHANES) spanning from 1999 to 2018. A total of 4,403 participants were included in the analysis. Mortality rates were determined through linkage with the National Death Index (NDI), with follow-up extending through December 31, 2019. The primary outcome variables were all-cause mortality and cause-specific mortality. Multivariable weighted Cox proportional hazards regression models, restricted cubic spline analysis, subgroup stratification, and sensitivity testing were utilized to evaluate the associations between the AIP and both all-cause and cause-specific mortality. Results: During a median follow-up of 83 months, 1,767 all-cause deaths and 526 CVD deaths occurred. After multivariable adjustment, AIP was independently associated with elevated risks of all-cause mortality (HR: 2.03, 95% CI: 1.62∼2.55, Conclusion: Data from large cohort studies have revealed a significant positive correlation between AIP levels and the risks of all-cause and cardiovascular mortality in the adult population of the United States. This suggests that AIP is associated with an increased risk of adverse outcomes in CKD and may serve as biomarker.

Indexed as

atherogenic index of plasmacardiovascular diseasechronic kidney diseasemortalityNational Health and Nutrition Examination Surveyprognosis

Identifiers

PMID40520802
PMCPMC12163239

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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 Socratic graph.