Evidence map›Paper›PMID 35979042›Full record

ArticleComputational and mathematical methods in medicine2022

Association between HBV Infection and the Prevalence of Coronary Artery Disease in the US Population.

Zun-Ping Ke, Miao Gong, Gang Zhao, Yue Geng, Kuan Cheng

Abstract read
In one paragraph

Article in Computational and mathematical methods in medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

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0cells of the map it votes in
5citing papers in PubMed
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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

5 citing papers in PubMed.

  1. Paradox of hepatitis B: Metabolic risk and cardiovascular protection in a national cohort.International journal of cardiology. Cardiovascular risk and prevention · 2026
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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Zun-Ping KeDepartment of Geriatrics, Shanghai Fifth People's Hospital, Fudan University, Shanghai, China.ORCID https://orcid.org/0000-0003-0274-5543
Miao GongDepartment of Geriatrics, Shanghai Fifth People's Hospital, Fudan University, Shanghai, China.
Gang ZhaoDepartment of Cardiology, Zhongshan Hospital, Fudan University, Shanghai Institute of Cardiovascular Diseases, Shanghai, China.
Yue GengDepartment of Geriatrics, Shanghai Fifth People's Hospital, Fudan University, Shanghai, China.
Kuan ChengDepartment of Cardiology, Zhongshan Hospital, Fudan University, Shanghai Institute of Cardiovascular Diseases, Shanghai, China.ORCID https://orcid.org/0000-0002-5492-7122

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Aims: This study aims to investigate the association between HBV infection and coronary artery disease (CAD) prevalence in the US population. A nomogram was proposed to predict CAD based on HBV infection. Methods: 25,749 individuals were collected from the 2001-2014 National Health and Nutrition Examination Survey. Participants with hepatitis B core antibody seropositivity were identified with HBV infection, including current and previous HBV infection status. We used adjusted logistic regression and performed sensitivity analysis to investigate the association between HBV infection and the prevalence of CAD. The effect size was evaluated by odds ratio (OR) with a 95% confidence interval (CI). Then, we created a nomogram to predict coronary artery disease. Additionally, we applied the Cox regression model to assess the association between HBV infection and all-cause mortality in those with baseline CAD. Results: 1790 (6.95%) individuals were with HBV infection. In the adjusted model, individuals with HBV showed a decreased CAD risk than those without (OR, 0.81; 95% CI, 0.67-0.98). Consistently, reduced risk in self-reported angina (OR, 0.72; 95% CI, 0.52-0.98) and coronary heart disease (OR, 0.76; 95% CI, 0.58-0.98) was observed in the hepatitis B core antibody seropositivity group. The subgroup analysis showed a consistent trend in the subgroups of age (<45 or ≥45), gender (male or female), hypertension (no or yes), and diabetes (no or yes). In the testing set, the proposed predictive model showed good performance with an area under the curve of 0.85 (95% CI, 0.83-0.86). There was no significant association between HBV infection and all-cause mortality in CAD patients (adjusted Conclusion: Our study suggests that HBV infection was associated with lower CAD risk. The proposed nomogram showed good performance in predicting CAD. However, no significant association was observed between HBV and all-cause mortality in CAD patients.

Indexed as

Coronary Artery DiseaseHepatitis BFemaleHepatitis B virusHumansMaleNutrition SurveysPrevalenceRisk Factors

Identifiers

PMID35979042
PMCPMC9377945

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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.