Peripheral Arterial Stiffness Increases the Risk of Progression of Renal Disease in Type 2 Diabetic Patients

Lim, Tae Hoon; Chung, Seung Min; Lee, Dong Sung; Choi, Se Ra; Moon, Jun Sung; Yoon, Ji Sung; Won, Kyu Chang; Lee, Hyoung Woo

doi:10.3389/fmed.2020.588967

Cited by 5 publications

(6 citation statements)

References 32 publications

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“…We found that the cumulative incidence of new-onset renal damage and isolated proteinuria in the normal arterial stiffness group, borderline atherosclerosis group, and arteriosclerosis group increased gradually, from 6.71% and 4.79% in the normal group to 15.84% and 11.31% in the atherosclerosis group, respectively. Similar to our follow-up time and age, Lim et al [8] also found a higher cumulative incidence of new renal damage in the Model 2 was further adjusted for smoking status (never smoker, past or current smoker), drinking status (never drink, past or current drink), salt status (light and common salt, heavy salt), physical activity (low or moderate, high), educational level (primary or middle, college); Model 3 was further adjusted for MAP (mmHg), FBG (mmol/L), TC (mmol/L), body mass index (kg/m 2 ), uric acid (umol/L), CRP (mg/L), eGFR (mL/min/1.73 m 2 ), the duration of diabetes (year), using antihypertensive drugs (no, yes), using hypoglycemic drugs (no, yes), using hypolipemic drugs (no, yes).…”

Section: Discussionsupporting

confidence: 89%

“…In addition, a study [7] of 461 Japanese DM patients revealed that cf-PWV had an independent association with a faster decline in kidney function. In contrast, a study [8] of 186 South Korea DM patients, showed a negative correlation between PWV and annual change in eGFR, whereas no signifificant risk was observed for the decline in eGFR among individuals with a BaPWV of ≥1,800 cm/s (HR 2.76, 95% CI 0.15-52.07). However, such results should be interpreted with caution because of small sample size.…”

Section: Endocrine Journal Advance Publicationmentioning

confidence: 82%

“…A study [7] has shown that atherosclerosis may contribute to the occurrence of proteinuria and decreased eGFR in diabetic patients. However, studies [8,9] have shown that arteriosclerosis is only associated with new-onset proteinuria and not significantly associated with eGFR decline. The past studies were hospital based and enrolled a relatively small number of patients.…”

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confidence: 99%

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The effect of arteriosclerosis on new-onset renal damage in diabetic patients

Gao

Liu

et al. 2023

Endocr J

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The aim of this study was to investigate the effect of arteriosclerosis on new-onset renal damage in a Chinese community population with diabetes. Patients with diabetes who had attended at least one physical examination after the Brachial-ankle pulse wave velocity (BaPWV) test from 2010 to 2018 were selected as subjects. A total of 4,462 patients were included in the study cohort. BaPWV levels <1,400 cm/s, 1,400-1,799 cm/s, and ≥1,800 cm/s were applied to divide the subjects into a normal arterial stiffness group, borderline atherosclerosis group and atherosclerosis group. Renal damage was defined by isolated proteinuria, isolated eGFR <60 mL/min/1.73 m 2 , proteinuria and eGFR <60 mL/min/1.73 m 2 . A Cox proportional risk model was used to analyze the effect of different groups on new-onset renal damage. After a median followup of 2.85 (1.88-4.90) years, Cox proportional risk models showed that after adjusting for risk factors, compared with the normal group, the HR and 95% CI of the risk of new-onset renal damage were 1.29 (95% CI: 0.95-1.76) and 1.59 (95% CI: 1.14-2.22) in the borderline atherosclerosis group and the atherosclerosis group, respectively. Atherosclerosis is a risk factor for new-onset renal damage, especially new-onset proteinuria, in diabetic patients.

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Section: Discussionsupporting

confidence: 89%

Section: Endocrine Journal Advance Publicationmentioning

confidence: 82%

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confidence: 99%

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The effect of arteriosclerosis on new-onset renal damage in diabetic patients

Gao

Liu

et al. 2023

Endocr J

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“…The correlation between these three features is analyzed to find the risk of diabetes patients with increased arterial stiffness. Lim et al, [13] studied the increased arterial stiffness leading to renal diseases in Type 2 diabetes mellitus using baPWV. Based on the EMPA-REG-Outcome trial, the increased risk of arterial stiffness is defined as baPWV>=1800 cm/s.…”

Section: Review Of Literaturementioning

confidence: 99%

Prediction of Arterial Stiffness Risk in Diabetes Patients through Pulse Wave Velocity and Deep Learning Techniques

Priya¹,

Thilagamani²

2022

ITC

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Diabetes and arterial stiffness are the primary health concerns related to each other. The understanding of both factors provides efficient disease prevention and avoidance. For the development of cardiovascular disease, arterial stiffness and Diabetes are pathological process considerations. The existing researchers reported the association of these two factors and the complications of arterial stiffness with Diabetes are still in research. Arterial stiffness is measured through pulse wave velocity (PWV), which influences cardiovascular disease in diabetic patients. Moreover, this study developed a medical prediction model for arterial stiffness through the machine and deep learning models to predict the patients who are high-risk factors. Brachial–ankle pulse wave velocity (baPWV) and fasting blood glucose (FBG) are the consideration of baseline. Gaussian-Least absolute shrinkage and selection operator (LASSO) with whale optimization is proposed for feature selection. Initially, key features are extracted from the wave measurement using LASSO, and Principal component analysis (PCA) has been used to remove the outliers. Second, Gaussian regression chooses the PWV-based relevant features from the LASSO identified features. The parts are the critical points to increasing the accuracy of the prediction model. Hence, the selected features are further improved with an evolutionary algorithm called the cat optimization approach. Third, the prediction model is constructed using three machine and deep learning algorithms such as a Support vector machine (SVM), a convolution neural network (CNN), and Gated Recurrent Unit (GRU). The performance of these methods is compared through the area under the receiver operating characteristic curve metric in the dataset. The model with the best performance was selected and validated in an independent discovery dataset (n = 912) from the Dryad Digital Repository (https://doi.org/10.5061/dryad.m484p). From the experimental evaluation, LSTM performs better than other algorithms in classifying arterial stiffness with the AUROC of 0.985 and AUPRC of 0.976.

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“…Pulse Wave Velocity (PWV), the propagation velocity of blood waves/pulses via the circulatory system, is a strong indicator of arterial stiffness [8][9][10][11] and can be used for the prediction of cardiovascular events [12]. The magnitude of PWV highly depends on the property of the blood vessels, e.g., blood vessel elasticity and wall thickness [13].…”

Section: Introductionmentioning

confidence: 99%

Simultaneous Measurement of Local Pulse Wave Velocities in Radial Arteries Using a Soft Sensor Based on the Fiber Bragg Grating Technique

Wang,

Zhang

et al. 2024

Micromachines

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Arterial stiffness has been proved to be an important parameter in the evaluation of cardiovascular diseases, and Pulse Wave Velocity (PWV) is a strong indicator of arterial stiffness. Compared to regional PWV (PWV among different arteries), local PWV (PWV within a single artery) outstands in providing higher precision in indicating arterial properties, as regional PWVs are highly affected by multiple parameters, e.g., variations in blood vessel lengths due to individual differences, and multiple reflection effects on the pulse waveform. However, local PWV is less-developed due to its high dependency on the temporal resolution in synchronized signals with usually low signal-to-noise ratios. This paper presents a method for the noninvasive simultaneous measurement of two local PWVs in both left and right radial arteries based on the Fiber Bragg Grating (FBG) technique via correlation analysis of the pulse pairs at the fossa cubitalis and at the wrist. Based on the measurements of five male volunteers at the ages of 19 to 21 years old, the average left radial PWV ranged from 9.44 m/s to 12.35 m/s and the average right radial PWV ranged from 11.50 m/s to 14.83 m/s. What is worth mentioning is that a stable difference between the left and right radial PWVs was observed for each volunteer, ranging from 2.27 m/s to 3.04 m/s. This method enables the dynamic analysis of local PWVs and analysis of their features among different arteries, which will benefit the diagnosis of early-stage arterial stiffening and may bring more insights into the diagnosis of cardiovascular diseases.

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Peripheral Arterial Stiffness Increases the Risk of Progression of Renal Disease in Type 2 Diabetic Patients

Cited by 5 publications

References 32 publications

The effect of arteriosclerosis on new-onset renal damage in diabetic patients

The effect of arteriosclerosis on new-onset renal damage in diabetic patients

Prediction of Arterial Stiffness Risk in Diabetes Patients through Pulse Wave Velocity and Deep Learning Techniques

Simultaneous Measurement of Local Pulse Wave Velocities in Radial Arteries Using a Soft Sensor Based on the Fiber Bragg Grating Technique

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