Evidence map›Paper›PMID 39026259›Full record

ArticleRespiratory research2024

Blood lipid profiles as a prognostic biomarker in idiopathic pulmonary fibrosis.

Ju Hyun Oh, Ganghee Chae, Jin Woo Song

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Article in Respiratory research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

Who cites it

9 citing papers in PubMed.

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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

3 authors.

Ju Hyun OhDepartment of Pulmonology and Critical Care Medicine, Sanggye Paik Hospital, Inje University College of Medicine, Seoul, Republic of Korea.
Ganghee ChaeDivision of Pulmonology and Critical Care Medicine, Department of Internal Medicine, Ulsan University Hospital, University of Ulsan College of Medicine, Ulsan, Republic of Korea.
Jin Woo SongDivision of Pulmonology and Critical Care Medicine, Department of Internal Medicine, Asan Medical Center, University of Ulsan College of Medicine, 88 Olympic-ro 43-gil, Songpagu, Seoul, 05505, Republic of Korea. jwsongasan@gmail.com.

Funding

National Research Foundation of Korea NRF-2022R1A2B5B02001602
6 · The paper itself

Abstract

backgroundDysregulation of lipid metabolism is implicated in the pathogenesis of idiopathic pulmonary fibrosis (IPF). However, the association between the blood lipid profiles and the prognosis of IPF is not well defined. We aimed to identify the impacts of lipid profiles on prognosis in patients with IPF.

methodsClinical data of 371 patients with IPF (145 and 226 in the derivation and validation cohorts, respectively), including serum lipid profiles (total cholesterol, triglyceride, high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, apolipoprotein A-I [Apo A-I], and apolipoprotein B), were retrospectively collected. The association with mortality was analyzed using the Cox proportional hazard model.

resultsIn the derivation cohort, the mean age was 67.5 years, 86.2% were men, and 30.3% died during the follow-up (median: 18.0 months). Non-survivors showed lower lung function and greater gender-age-physiology scores than survivors. Among the serum lipid profiles, the levels of triglyceride and Apo A-I were significantly lower in non-survivors than in survivors. In the multivariate Cox analysis, low Apo A-I levels (< 140 mg/dL) were independently associated with the risk of mortality (hazard ratio 3.910, 95% confidence interval 1.170-13.069; P = 0.027), when adjusted for smoking history, body mass index, GAP score, and antifibrotic agent use. In both derivation and validation cohorts, patients with low Apo A-I levels (< 140 mg/dL) had worse survival (median survival: [derivation] 34.0 months vs. not reached, P = 0.003; [validation] 40.0 vs. 53.0 months, P = 0.027) than those with high Apo A-I levels in the Kaplan-Meier survival analysis.

conclusionsOur results indicate that low serum Apo A-1 levels are an independent predictor of mortality in patients with IPF, suggesting the utility of serum Apo A-I as a prognostic biomarker in IPF.

Indexed as

BiomarkersIdiopathic Pulmonary FibrosisLipidsAgedApolipoprotein A-ICohort StudiesFemaleFollow-Up StudiesHumansMaleMiddle AgedPrognosisRetrospective StudiesApolipoprotein A-IBiomarkersLipidsApolipoprotein A-IGAP scoreIdiopathic pulmonary fibrosisMortality

Identifiers

PMID39026259
PMCPMC11264581

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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.