Evidence map›Paper›PMID 39619739›Full record

ArticleTobacco induced diseases2024

Total serum bilirubin levels as mediators of anti-atherosclerosis mechanisms with consideration of smoking status.

Shigemasa Tani, Kazuhiro Imatake, Yasuyuki Suzuki, Tsukasa Yagi, Atsuhiko Takahashi

Abstract read
In one paragraph

Article in Tobacco induced diseases, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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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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

1 citing paper 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

5 authors.

Shigemasa TaniDepartment of Health Planning Center, Nihon University Hospital, Tokyo, Japan.
Kazuhiro ImatakeDepartment of Health Planning Center, Nihon University Hospital, Tokyo, Japan.
Yasuyuki SuzukiDepartment of Health Planning Center, Nihon University Hospital, Tokyo, Japan.
Tsukasa YagiDepartment of Cardiology, Nihon University Hospital, Tokyo, Japan.
Atsuhiko TakahashiDepartment of Health Planning Center, Nihon University Hospital, Tokyo, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionCigarette smoking is a significant risk factor for atherosclerotic cardiovascular diseases (ASCVDs). Mildly elevated total serum bilirubin (TSB) levels can exert anti-atherosclerotic effects and may regulate inflammation. We explore the relationship between TSB levels, smoking, and inflammation.

methodsThis cross-sectional study evaluated health screening participants with no history of ASCVD between 1 April 2019 and 31 March 2020. TSB was compared between non-smokers and smokers using the Kruskal-Wallis test, and the influencing factors of TSB levels were identified using multivariable logistic regression with TSB levels above the 75th percentile set as the dependent variable. Mediation analysis was performed to determine whether TSB levels mediated the association between smoking and inflammation.

resultsA total of 8337 participants (mean age: 46.6 ± 13.0 years; 58.9% men) were included. TSB levels were significantly lower in smokers (n=1353) than in non-smokers (n=6984) [median (IQR): 0.72 (0.56-0.92) vs 0.76 (0.60-0.97) mg/dL, p<0.0001]. Multivariable logistic regression analysis demonstrated that smoking was an independent determinant of lower TSB levels (adjusted odds ratio, AOR=0.81; 95% CI: 0.70-0.93, p=0.003). Leukocyte counts and C-reactive protein levels significantly decreased as TSB levels increased (p<0.0001). Moreover, the relationship between the duration of smoking cessation and TSB levels showed a positive correlation. Mediation analysis indicated that cigarette smoking had significant indirect effects on higher leukocyte counts and higher CRP levels (coefficient=0.014; 95% CI: 0.008-0.021; and coefficient=0.002; 95% CI: 0.001-0.003, respectively].

conclusionsLower TSB levels related to a smoking habit may be associated with higher inflammation, thereby increasing the ASCVD risk. TSB may regulate inflammation and exert antioxidant effects. Furthermore, smoking cessation may lead to higher TSB levels and lower inflammation.

Indexed as

atherosclerosisbilirubincardiovascular diseaseinflammationsmoking

Identifiers

PMID39619739
PMCPMC11607641

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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.