ArticleScientific reports2024
Hemodynamic parameters and diabetes mellitus in community-dwelling middle-aged adults and elders: a community-based study.
Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Low Carotid Mean Flow Velocity: A Noninvasive Marker for Coronary Heart Disease-A Community-Based Study.Diagnostics (Basel, Switzerland) · 2025Article
- Carotid Resistance and Pulsatility: Non-Invasive Markers for Diabetes Mellitus-Related Vascular Diseases.Journal of clinical medicine · 2025Article
- Development of Mathematical Model for Understanding Microcirculation in Diabetic Foot Ulcers Based on Ankle-Brachial Index.Bioengineering (Basel, Switzerland) · 2025Article
- The ProCVT smart-sheet as a new screening tool for cardiovascular autonomic neuropathy: a feasibility study.Frontiers in endocrinology · 2025Article
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Authors and funding
6 authors.
Funding
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.
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