Evidence mapPaperPMID 38664682Full record

ArticleBMC public health2024

The dynamic risk factors of cardiovascular disease among people living with HIV: a real-world data study.

Ziang Liu, Jiajia Zhang, Xueying Yang, Haoyuan Gao, Shujie Chen, Sharon Weissman, Bankole Olatosi, Xiaoming Li

Open access · goldAbstract read
In one paragraph

Article in BMC public health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 1 pooled it
8.3field-weighted citation impact, top 2% of its field
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

7 citing papers in PubMed, 1 synthesis or guideline pooled it, 12 citations in OpenAlex.

  1. Pooled it
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  3. Article
  4. Article
  5. Article
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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

8 authors at 1 institution in 1 country.

Ziang LiuDepartment of Epidemiology and Biostatistics, Arnold School of Public Health, University of South Carolina, 915 Greene Street, Columbia, SC, 29208, USA. ziangl@email.sc.edu.
Jiajia ZhangDepartment of Epidemiology and Biostatistics, Arnold School of Public Health, University of South Carolina, 915 Greene Street, Columbia, SC, 29208, USA.
Xueying YangArnold School of Public Health, South Carolina SmartState Center for Healthcare Quality, University of South Carolina, Columbia, SC, 29208, USA.
Haoyuan GaoDepartment of Epidemiology and Biostatistics, Arnold School of Public Health, University of South Carolina, 915 Greene Street, Columbia, SC, 29208, USA.
Shujie ChenDepartment of Epidemiology and Biostatistics, Arnold School of Public Health, University of South Carolina, 915 Greene Street, Columbia, SC, 29208, USA.
Sharon WeissmanArnold School of Public Health, South Carolina SmartState Center for Healthcare Quality, University of South Carolina, Columbia, SC, 29208, USA.
Bankole OlatosiArnold School of Public Health, South Carolina SmartState Center for Healthcare Quality, University of South Carolina, Columbia, SC, 29208, USA.
Xiaoming LiArnold School of Public Health, South Carolina SmartState Center for Healthcare Quality, University of South Carolina, Columbia, SC, 29208, USA.
University of South Carolina · US

Funding

Patterns and predictors of viral suppression: A Big Data approachR01AI164947 · UNIVERSITY OF SOUTH CAROLINA AT COLUMBIA · 2025 to 2025
$710k
National Institute of Allergy and Infectious Diseases of the National Institutes of Health R01AI127203-4S1National Institute of Allergy and Infectious Diseases of the National Institutes of Health R01AI164947-03S2National Institute of Allergy and Infectious Diseases of the National Institutes of Health R21AI170159-01A1
6 · The paper itself

Abstract

backgroundThis study aims to investigate the incidence and dynamic risk factors for cardiovascular diseases (CVD) among people living with HIV (PLWH).

methodsIn this population-based statewide cohort study, we utilized integrated electronic health records data to identify adult (age ≥ 18) who were diagnosed with HIV between 2006 and 2019 and were CVD event-free at the HIV diagnosis in South Carolina. The associations of HIV-related factors and traditional risk factors with the CVD incidence were investigated during the overall study period, and by different follow-up periods (i.e., 0-5yrs, 6-10yrs 11-15yrs) using multivariable logistic regression models.

resultsAmong 9,082 eligible participants, the incidence of CVD was 18.64 cases per 1000 person-years. Overall, conventional risk factors, such as tobacco use, hypertension, obesity, chronic kidney disease (CKD), were persistently associated with the outcome across all three groups. While HIV-related factors, such as recent CD4 count (e.g., > 350 vs. <200 cells/mm

conclusionsMaintaining an optimal viral suppression might prevent CVD incidence in the short term, whereas restoring immune recovery may be beneficial for reducing CVD risk regardless of the duration of HIV diagnosis. Our findings suggest the necessity of conducting more targeted interventions during different periods of HIV infection.

Indexed as

Cardiovascular DiseasesHIV InfectionsAdultCohort StudiesElectronic Health RecordsFemaleHumansIncidenceMaleMiddle AgedRisk FactorsSouth CarolinaYoung AdultCardiovascular DiseaseCD4 countChronic diseaseHIVSouth CarolinaViral load

Identifiers

PMID38664682
PMCPMC11044498
OpenAlexW4395455586

What Socratic holds

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LicenceCC BY
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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.