Diabetes, glycemic control and arterial stiffness: a real-world cohort study in the context of predictive, preventive, and personalized medicine

Cancan Cui; Te Zhang; Yitian Qi; Jiaqi Chu; Haikun Xu; Chen Sun; Zhenming Zhang; Xingang Wang; Siqi Yue; Xiaoping Kang; Ling Fang

doi:10.1007/s13167-023-00347-z

Diabetes, glycemic control and arterial stiffness: a real-world cohort study in the context of predictive, preventive, and personalized medicine

EPMA J. 2023 Nov 24;14(4):663-672. doi: 10.1007/s13167-023-00347-z. eCollection 2023 Dec.

Authors

Cancan Cui¹, Te Zhang¹, Yitian Qi¹, Jiaqi Chu², Haikun Xu¹, Chen Sun¹, Zhenming Zhang¹, Xingang Wang¹, Siqi Yue¹, Xiaoping Kang³, Ling Fang¹

Affiliations

¹ China-Japan Union Hospital of Jilin University, Jilin University, Changchun, China.
² School of Medical Imaging, Dalian Medical University, Dalian, China.
³ Beijing Xiaotangshan Hospital, Beijing, China.

PMID: 38094580
PMCID: PMC10713938 (available on 2024-12-01)
DOI: 10.1007/s13167-023-00347-z

Abstract

Background: Arterial stiffness is a major contributor to morbidity and mortality worldwide. Although several metabolic markers associated with arterial stiffness have been developed, there is limited data regarding whether glycemic control modifies the association between diabetes and arterial stiffness. For these reasons, identification of traits around diabetes will directly contribute to arterial stiffness and atherosclerosis management in the context of predictive, preventive, and personalized medicine (PPPM). Thus, this study aimed to explore the relationship of diabetes and glycemic control status with arterial stiffness in a real-world setting.

Methods: Data of participants from Beijing Xiaotangshan Examination Center (BXEC) with at least two surveys between 2008 and 2019 were used. Cumulative hazards were presented by inverse probability of treatment weighted (IPTW) Kaplan-Meier curves. Cox models were used to estimate the hazard ratio (HR) and 95% confidence interval (CI). Arterial stiffness was defined as brachial-ankle pulse wave velocity (baPWV) ≥1400 cm/s.

Results: Of 5837 participants, the mean baseline age was 46.5±9.3 years, including 3791 (64.9%) males. During a median follow-up of 4.0 years, 1928 (33.0%) cases of incident arterial stiffness were observed. People with diabetes at baseline had a 48.4% (HR: 1.484, 95% CI: 1.250-1.761) excessive risk of arterial stiffness. Adherence to good glycemic control attenuated the relationship between diabetes and arterial stiffness (HR: 1.264, 95% CI: 0.950-1.681); while uncontrolled diabetes was associated with the highest risk of arterial stiffness (HR: 1.629, 95% CI: 1.323-2.005). Results were consistent using IPTW algorithm and multiple imputed data.

Conclusion: Our study quantified that diabetes status is closely associated with an increased risk of arterial stiffness and supported that adherence to good glycemic control could attenuate the adverse effect of diabetes on arterial stiffness. Therefore, glucose monitoring and control is a cost-effective strategy for the predictive diagnostics, targeted prevention, patient stratification, and personalization of medical services in early vascular damages and arterial stiffness.

Supplementary information: The online version contains supplementary material available at 10.1007/s13167-023-00347-z.

Keywords: Arterial stiffness; Brachial-ankle pulse wave velocity (baPWV); Diabetes; Glycemic control; Predictive preventive personalized medicine (PPPM).

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