Evidence mapPaperPMID 36926049Full record

ArticleFrontiers in cardiovascular medicine2023

Assessing the performance of genetic risk score for stratifying risk of post-sepsis cardiovascular complications.

Brian McElligott, Zhuqing Shi, Andrew S Rifkin, Jun Wei, S Lilly Zheng, Brian T Helfand, Jonathan S H Woo, Jianfeng Xu

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Article in Frontiers in cardiovascular medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited 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

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0 citing papers in PubMed, 0 citations in OpenAlex.

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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

8 authors at 2 institutions in 1 country.

Brian McElligottProgram for Personalized Cancer Care, NorthShore University HealthSystem, Evanston, IL, United States.
Zhuqing ShiProgram for Personalized Cancer Care, NorthShore University HealthSystem, Evanston, IL, United States.
Andrew S RifkinProgram for Personalized Cancer Care, NorthShore University HealthSystem, Evanston, IL, United States.
Jun WeiProgram for Personalized Cancer Care, NorthShore University HealthSystem, Evanston, IL, United States.
S Lilly ZhengProgram for Personalized Cancer Care, NorthShore University HealthSystem, Evanston, IL, United States.
Brian T HelfandProgram for Personalized Cancer Care, NorthShore University HealthSystem, Evanston, IL, United States.
Jonathan S H WooDepartment of Medicine, NorthShore University HealthSystem, Evanston, IL, United States.
Jianfeng XuProgram for Personalized Cancer Care, NorthShore University HealthSystem, Evanston, IL, United States.
NorthShore University HealthSystem · USUniversity of Chicago · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Patients with sepsis are at increased risk for cardiovascular complications, including myocardial infarction (MI), ischemic stroke (IS), and venous thromboembolism (VTE). Our objective is to assess whether genetic risk score (GRS) can differentiate risk for these complications. Methods: A population-based prospective cohort of 483,177 subjects, derived from the UK Biobank, was followed for diagnosis of sepsis and its complications (MI, IS, and VTE) after the study recruitment. GRS for each complication was calculated based on established risk-associated single nucleotide polymorphisms (SNPs). Time to incident MI, IS, and VTE was compared between subjects with or without sepsis and GRS risk groups using Kaplan-Meier log-rank test and Cox-regression analysis. Results: During an average of 12.6 years of follow-up, 10,757 (2.23%) developed sepsis. Patients with sepsis had an overall higher risk than non-sepsis subjects for each complication, but the risk differed by time after a sepsis diagnosis; exceedingly high in short-term (0-30 days), considerably high in mid-term (31 days to 2 years), and reduced in long-term (>2 years). Furthermore, in White subjects, GRS was a significant predictor of complications, independent of sepsis and other risk factors. For example, GRS Conclusion: Risk for post-sepsis cardiovascular complications differed considerably by time after a sepsis diagnosis and GRS. These findings, if confirmed in other ancestry-specific populations, may guide personalized management for preventing post-sepsis cardiovascular complications.

Indexed as

genetic risk scoreischemic strokemyocardial infarctionpolygenicsepsisvenous thromboembolism

Identifiers

PMID36926049
PMCPMC10011112
OpenAlexW4322630661

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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.