Hemodynamic Parameters and Diabetes Mellitus in Community-dwelling Middle-aged Adults and Elders: a Community-based Study

Overview

Journal Sci Rep

Specialty Science

Date 2024 May 26

PMID 38797773

Authors

Tzu-Wei Wu

Yih-Jer Wu

Chao-Liang Chou

Chun-Fang Cheng

Shu-Xin Lu

Li-Yu Wang

Affiliations

Soon will be listed here.

Abstract

Hemodynamic parameters have been correlated with stroke, hypertension, and arterial stenosis. While only a few small studies have examined the link between hemodynamics and diabetes mellitus (DM). This case-control study enrolled 417 DM patients and 3475 non-DM controls from a community-based cohort. Peak systolic velocity (PSV), end-diastolic velocity (EDV), blood flow velocity (MFV), pulsatility index (PI), and the resistance index (RI) of the common carotid arteries were measured by color Doppler ultrasonography. Generalized linear regression analyses showed that as compared to the non-DM controls, the age-sex-adjusted means of PSV, EDV, and MFV were - 3.28 cm/sec, - 1.94 cm/sec, and - 2.38 cm/sec, respectively, lower and the age-sex-adjusted means of RI and PI were 0.013 and 0.0061, respectively, higher for the DM cases (all p-values < 0.0005). As compared to the lowest quartiles, the multivariable-adjusted ORs of DM for the highest quartiles of PSV, EDV, MFV, RI, and PI were 0.59 (95% confidence interval [CI] 0.41-0.83), 0.45 (95% CI 0.31-0.66), 0.53 (95% CI 0.37-0.77), 1.61 (95% CI 1.15-2.25), and 1.58 (95% CI 1.12-2.23), respectively. More importantly, the additions of EDV significantly improved the predictabilities of the regression models on DM. As compared to the model contained conventional CVD risk factors alone, the area under the receiver operating curve (AUROC) increased by 1.00% (95% CI 0.29-1.73%; p = 0.0059) and 0.80% (95% CI 0.15-1.46%; p = 0.017) for models that added EDV in continuous and quartile scales, respectively. Additionally, the additions of PSV and MFV also significantly improved the predictabilities of the regression models (all 0.01 < p-value < 0.05). This study reveals a significant correlation between DM and altered hemodynamic parameters. Understanding this relationship could help identify individuals at higher risk of DM and facilitate targeted preventive strategies to reduce cardiovascular complications in DM patients.

Citing Articles

Development of Mathematical Model for Understanding Microcirculation in Diabetic Foot Ulcers Based on Ankle-Brachial Index.

Da Silva A, de Almeida Nunes G, Faria R, Rosa M, Da Costa L, de Faria N Bioengineering (Basel). 2025; 12(2).

PMID: 40001725 PMC: 11851477. DOI: 10.3390/bioengineering12020206.

References

Glagov S, Zarins C, Giddens D, Ku D . Hemodynamics and atherosclerosis. Insights and perspectives gained from studies of human arteries. Arch Pathol Lab Med. 1988; 112(10):1018-31. View

Summerhill V, Grechko A, Yet S, Sobenin I, Orekhov A . The Atherogenic Role of Circulating Modified Lipids in Atherosclerosis. Int J Mol Sci. 2019; 20(14). PMC: 6678182. DOI: 10.3390/ijms20143561. View

Wong N, Budoff M, Ferdinand K, Graham I, Michos E, Reddy T . Atherosclerotic cardiovascular disease risk assessment: An American Society for Preventive Cardiology clinical practice statement. Am J Prev Cardiol. 2022; 10:100335. PMC: 8943256. DOI: 10.1016/j.ajpc.2022.100335. View

Chuang S, Bai C, Cheng H, Chen J, Yeh W, Hsu P . Common carotid artery end-diastolic velocity is independently associated with future cardiovascular events. Eur J Prev Cardiol. 2015; 23(2):116-24. DOI: 10.1177/2047487315571888. View

Lau K, Pego P, Mazzucco S, Li L, Howard D, Kuker W . Age and sex-specific associations of carotid pulsatility with small vessel disease burden in transient ischemic attack and ischemic stroke. Int J Stroke. 2018; 13(8):832-839. PMC: 6424409. DOI: 10.1177/1747493018784448. View

Asil T, Uzunca I, Utku U, Berberoglu U . Monitoring of increased intracranial pressure resulting from cerebral edema with transcranial Doppler sonography in patients with middle cerebral artery infarction. J Ultrasound Med. 2003; 22(10):1049-53. DOI: 10.7863/jum.2003.22.10.1049. View

Vigen T, Ihle-Hansen H, Lyngbakken M, Berge T, Thommessen B, Ihle-Hansen H . Carotid Atherosclerosis is Associated with Middle Cerebral Artery Pulsatility Index. J Neuroimaging. 2020; 30(2):233-239. DOI: 10.1111/jon.12684. View

Bytyci I, Shenouda R, Wester P, Henein M . Carotid Atherosclerosis in Predicting Coronary Artery Disease: A Systematic Review and Meta-Analysis. Arterioscler Thromb Vasc Biol. 2021; 41(4):e224-e237. DOI: 10.1161/ATVBAHA.120.315747. View

Robinson J, Fox K, Bullano M, Grandy S . Atherosclerosis profile and incidence of cardiovascular events: a population-based survey. BMC Cardiovasc Disord. 2009; 9:46. PMC: 2753582. DOI: 10.1186/1471-2261-9-46. View

10.

Galis Z, Sukhova G, Lark M, Libby P . Increased expression of matrix metalloproteinases and matrix degrading activity in vulnerable regions of human atherosclerotic plaques. J Clin Invest. 1994; 94(6):2493-503. PMC: 330083. DOI: 10.1172/JCI117619. View

11.

Chuang S, Cheng H, Bai C, Yeh W, Chen J, Pan W . Blood Pressure, Carotid Flow Pulsatility, and the Risk of Stroke: A Community-Based Study. Stroke. 2016; 47(9):2262-8. DOI: 10.1161/STROKEAHA.116.013207. View

12.

Soyoye D, Dawha S, Ayoola O, Ibitoye B, Ikem R, Adedeji T . Relationship between Renal Doppler Indices and Biochemical indices of Renal Function in Type 2 Diabetes Mellitus. West Afr J Med. 2018; 35(3):189-194. View

13.

Vasdev S, Gill V, Singal P . Role of advanced glycation end products in hypertension and atherosclerosis: therapeutic implications. Cell Biochem Biophys. 2007; 49(1):48-63. DOI: 10.1007/s12013-007-0039-0. View

14.

Park J, Cho M, Lee K, Kim C, Kim H, Nam J . Cerebral arterial pulsatility and insulin resistance in type 2 diabetic patients. Diabetes Res Clin Pract. 2007; 79(2):237-42. DOI: 10.1016/j.diabres.2007.08.029. View

15.

George P, Pourcelot L, Fourcade C, Guillaud C, Descotes J . [The Doppler effect and measurement of the blood flow]. C R Acad Hebd Seances Acad Sci D. 1965; 261(1):253-6. View

16.

Du X, Edelstein D, Obici S, Higham N, Zou M, Brownlee M . Insulin resistance reduces arterial prostacyclin synthase and eNOS activities by increasing endothelial fatty acid oxidation. J Clin Invest. 2006; 116(4):1071-80. PMC: 1395482. DOI: 10.1172/JCI23354. View

17.

Chuang S, Bai C, Chen J, Yeh W, Chen H, Chiu H . Common carotid end-diastolic velocity and intima-media thickness jointly predict ischemic stroke in Taiwan. Stroke. 2011; 42(5):1338-44. DOI: 10.1161/STROKEAHA.110.605477. View

18.

Climie R, Picone D, Blackwood S, Keel S, Qasem A, Rattigan S . Pulsatile interaction between the macro-vasculature and micro-vasculature: proof-of-concept among patients with type 2 diabetes. Eur J Appl Physiol. 2018; 118(11):2455-2463. DOI: 10.1007/s00421-018-3972-2. View

19.

Mozaffarian D, Benjamin E, Go A, Arnett D, Blaha M, Cushman M . Executive Summary: Heart Disease and Stroke Statistics--2016 Update: A Report From the American Heart Association. Circulation. 2016; 133(4):447-54. DOI: 10.1161/CIR.0000000000000366. View

20.

Li Y, Ueng K, Jeng J, Charng M, Lin T, Chien K . 2017 Taiwan lipid guidelines for high risk patients. J Formos Med Assoc. 2017; 116(4):217-248. DOI: 10.1016/j.jfma.2016.11.013. View