Evidence map›Paper›PMID 39347932›Full record

ArticleJournal of epidemiology and global health2024

Comparing Carotid Artery Velocities with Current ASCVD Risk Stratification: A Novel Approach to Simpler Risk Assessment.

Yueh-Chien Lu, Po-Ju Chen, Sheng-Nan Lu, Fu-Wen Liang, Hung-Yi Chuang

Abstract readComparative Study
In one paragraph

Article in Journal of epidemiology and global health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

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4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

5 authors.

Yueh-Chien LuDepartment of Occupational Medicine, Kaohsiung Chang Gung Memorial Hospital, Kaohsiung, Taiwan.ORCID 0000-0001-7582-1573
Po-Ju ChenDepartment of Occupational Medicine, Kaohsiung Chang Gung Memorial Hospital, Kaohsiung, Taiwan.ORCID 0000-0003-1204-3027
Sheng-Nan LuChang Gung University College of Medicine, Taoyuan, Taiwan.ORCID 0000-0002-5493-4752
Fu-Wen LiangDepartment of Public Health, College of Health Sciences, Kaohsiung Medical University, Kaohsiung, Taiwan.ORCID 0000-0002-3396-037X
Hung-Yi ChuangDepartment of Community Medicine, Kaohsiung Medical University Hospital, No.100, Shih-Chuan 1st Road, Sanmin, Kaohsiung, 80708, Taiwan. ericch@kmu.edu.tw.ORCID 0000-0002-8321-8720

Funding

Kaohsiung Medical University Chung-Ho Memorial Hospital KMUH112-2R79Kaohsiung Medical University Research Center KMU- TC113A01Ministry of Science and Technology, Taiwan 111-2314-B-037-038-MY2
6 · The paper itself

Abstract

purposeTo explore the potential of a novel approach to simplify risk assessment by comparing carotid artery velocities with current atherosclerotic cardiovascular disease (ASCVD) risk stratification method using nonlinear measurements.

methodsIn this prospective study conducted at a medical center in southern Taiwan from January 1, 2020, to December 31, 2021, 1636 participants aged 40-75 years without prior ASCVD events were enrolled. Carotid flow velocity was obtained through duplex ultrasonography. ASCVD risk was categorized into two groups according to the 2022 USPSTF guidelines for primary prevention. We analyzed associations between flow indices and ASCVD risk using logistic regression and generalized additive models (GAMs).

resultsThe end diastolic velocity (EDV) of common carotid artery (CCA) and the peak systolic velocity (PSV) of internal carotid artery (ICA) were inversely and nonlinearly associated with cardiovascular event risk. Multivariate logistic regression analysis with ROC curves revealed that the optimal speed for the EDV of CCA was approximately 23.75 cm/s, and the optimal PSV and EDV of ICA were approximately 81.75 cm/s and 26.75 cm/s, respectively. The GAMs showed U-shaped relationships between elevated ASCVD risk and blood flow velocity in the carotid arteries, with inflection points of approximately 82 cm/s in the PSV of ICA and near 25 cm/s in the EDV of CCA. Both methods revealed similar results.

conclusionsThe EDVs and PSVs of the CCA and ICA are associated with the development of cardiovascular events. Optimal velocity ranges were identified; however, further hemodynamic investigations are warranted.

Indexed as

Carotid ArteriesAdultAgedAtherosclerosisBlood Flow VelocityFemaleHumansMaleMiddle AgedProspective StudiesRisk AssessmentTaiwanUltrasonography, Doppler, DuplexAtherosclerotic cardiovascular disease riskCarotid artery velocityDuplex ultrasonographyGeneralized additive model

Identifiers

PMID39347932
PMCPMC11652626

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LicenceCC BY-NC-ND
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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.