Physiological Diagnostic Criteria for Vascular Failure

Tanaka, Atsushi; Tomiyama, Hirofumi; Maruhashi, Tatsuya; Matsuzawa, Yasushi; Miyoshi, Toru; Kabutoya, Tomoyuki; Kario, Kazuomi; Sugiyama, Seigo; Munakata, Masanori; Ito, Hiroshi; Ueda, Shinichiro; Vlachopoulos, Charalambos; Higashi, Yukihito; Inoue, Teruo; Node, Koichi

doi:10.1161/hypertensionaha.118.11554

Cited by 199 publications

(172 citation statements)

References 136 publications

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“…The cardio‐ankle vascular index (CAVI) is an indicator of arterial stiffness and has been associated with cardiovascular risk factors and cardiovascular disease . CAVI is one of the vascular measures of the systemic hemodynamic atherothrombotic syndrome (SHATS), which is characterized by a vicious cycle of BP variability and vascular disease contributing to cardiovascular events .…”

Section: Introductionmentioning

confidence: 99%

Highly precise risk prediction model for new‐onset hypertension using artificial intelligence techniques

Kanegae

Suzuki

Fukatani

et al. 2019

J of Clinical Hypertension

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It has been estimated that hypertension is the cause of approximately 13% of all deaths worldwide each year. 1 In light of the world's population growth and aging demographic, hypertension is a global burden, along with other cardiovascular and age-related diseases. 2,3 Early intervention with lifestyle modifications and treatment of "prehypertension" may reduce the incidence and long-term consequences of clinical hypertension. [4][5][6][7] Recent guidelines lowered the recommended thresholds for diagnosing hypertension or abnormal "elevated blood pressure (BP)" and the BP goal during antihypertensive therapy. 8-10 Therefore, the ability to predict an individual's risk of developing hypertension would be helpful for clinicians. They could then plan and prescribe personalized lifestyle modifications or make therapeutic decisions designed to prevent or postpone the development of hypertension. There are several models available to predict the risk of new-onset hypertension; these have been developed in Western and Asian countries using traditional statistical methods (eg, Cox regression or logistic regression). 11,12 Arterial stiffness is increasingly being recognized as making an important contribution to increases in systolic BP (SBP) and the development of hypertension in general populations, independent of traditional hypertension risk factors. [13][14][15][16] In addition, arterial AbstractHypertension is a significant public health issue. The ability to predict the risk of developing hypertension could contribute to disease prevention strategies. This study used machine learning techniques to develop and validate a new risk prediction model for new-onset hypertension. In Japan, Industrial Safety and Health Law requires employers to provide annual health checkups to their employees. We used 2005-2016 health checkup data from 18 258 individuals, at the time of hypertension diagnosis [Year (0)] and in the two previous annual visits [Year (−1) and Year (−2)].Data were entered into models based on machine learning methods (XGBoost and ensemble) or traditional statistical methods (logistic regression). Data were randomly split into a derivation set (75%, n = 13 694) used for model construction and development, and a validation set (25%, n = 4564) used to test performance of the derived models. The best predictor in the XGBoost model was systolic blood pressure during cardio-ankle vascular index measurement at Year (−1). Area under the receiver operator characteristic curve values in the validation cohort were 0.877, 0.881, and 0.859 for the XGBoost, ensemble, and logistic regression models, respectively. We have developed a highly precise prediction model for future hypertension using machine learning methods in a general normotensive population. This could be used to identify at-risk individuals and facilitate earlier non-pharmacological intervention to prevent the future development of hypertension.

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Section: Introductionmentioning

confidence: 99%

Highly precise risk prediction model for new‐onset hypertension using artificial intelligence techniques

Kanegae

Suzuki

Fukatani

et al. 2019

J of Clinical Hypertension

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“…We and other investigators also reported that a postprandial increase of serum TG and remnant-like particles-cholesterol (RLP-C) causes endothelial dysfunction assessed by brachial artery flowmediated dilatation (FMD) [5,6,12,13]. FMD has been shown to be impaired in patients with traditional coronary risk factors, including hypertension, dyslipidemia, diabetes mellitus, and smoking, and it has been considered to be a cause of atherosclerosis [14]. Statins improve endothelial function as assessed by FMD [15,16].…”

Section: Introductionmentioning

confidence: 92%

Combination Therapy with Pemafibrate (K-877) and Pitavastatin Improves Vascular Endothelial Dysfunction in Dahl/Salt-sensitive Rats Fed a High-salt and High-fat Diet

Yoshida

Nakamura

Miyoshi

et al. 2020

Preprint

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Background Statins suppress the progression of atherosclerosis by reducing low-density lipoprotein (LDL) cholesterol levels. Pemafibrate (K-877), a novel selective peroxisome proliferator-activated receptor α modulator, is expected to reduce residual risk factors including high triglycerides (TGs) and low high-density lipoprotein (HDL) cholesterol during statin treatment. However, it is not known if statin therapy with add-on pemafibrate improves the progression of atherosclerosis. The aim of this study was to assess the effect of combination therapy with pitavastatin and pemafibrate on lipid profiles and endothelial dysfunction in hypertension and hyperlipidemia model rats. Methods Seven-week-old male Dahl salt-sensitive (DS) rats were divided into the following five treatment groups (normal diet (ND) plus vehicle, high-salt and high-fat diet (HD) plus vehicle, HD plus pitavastatin (0.3 mg/kg), HD plus pemafibrate (K-877) (0.5 mg/kg), and HD plus combination of pitavastatin and pemafibrate) and treated for 12 weeks. At 19 weeks, endothelium-dependent relaxation of the thoracic aorta in response to acetylcholine was evaluated. Results After feeding for 12 weeks, systolic blood pressure and plasma levels of total cholesterol were significantly higher in the HD-vehicle group compared with the ND-vehicle group. Combination therapy with pitavastatin and pemafibrate significantly reduced systolic blood pressure, TG levels, including total, chylomicron (CM), very LDL (VLDL), HDL-TG, and cholesterol levels, including total, CM, VLDL, and LDL-cholesterol, compared with vehicle treatment. Acetylcholine caused concentration-dependent relaxation of thoracic aorta rings that were pre-contracted with phenylephrine in all rats. Relaxation rates in the HD-vehicle group were significantly lower compared with the ND-vehicle group. Relaxation rates in the HD-combination of pitavastatin and pemafibrate group significantly increased compared with the HD-vehicle group, although neither medication alone ameliorated relaxation rates significantly. Western blotting experiments showed increased phosphorylated endothelial nitric oxide synthase protein expression in aortas from rats in the HD-combination group compared with the HD-vehicle group. However, the expression levels did not respond significantly to either medication alone. Conclusions Combination therapy with pitavastatin and pemafibrate improved lipid profiles and endothelial dysfunction in hypertension and hyperlipidemia model rats. Pemafibrate as an add-on strategy to statins may be useful for preventing atherosclerosis progression.

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“…Via mail potential participants were informed about the study, it's goals and the confidentiality of any provided information. Based on the two samplings with a total of 6,377 randomly selected invitees, the overall response rate was 33 triglycerides were higher, LDL-c was measured by the homogeneous technique for direct measuring (Sekisui Medical, Japan). BP was measured, using an automated office measurement device (BpTRU, model BPM 200; Bp TRU Medical Devices Ltd., Canada).…”

Section: Sampling and Recruitmentmentioning

confidence: 99%

“…Where PWV is pulse wave velocity, ρ is blood density, Ps and Pd are systolic and diastolic BP values in mmHg [4]. High CAVI group was defined as those subjects with ≥ 9 points and normal as those with CAVI <9, based on the presence of advanced arteriosclerosis [4][5][6][30][31][32][33][34]. Levels of carbon monoxide in the expired breath < 10 ppm were compatible with the definition of a non-smoker.…”

Section: Definition Of Variablesmentioning

confidence: 99%

Associations between high triglycerides and arterial stiffness in a population-based sample: Results from the Kardiovize 2030 study

Pavlovska

Kunzová

Jakubík

et al. 2020

Preprint

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Background : The term arterial stiffness (ArSt) describes structural changes in arterial wall related to the loss of elasticity and is known as an independent predictor of cardiovascular diseases (CVD). The evidence relating to ArSt and triglycerides (TG) shows contradictory results. This paper means to survey the association between high TG and ArSt, utilizing the cardio-ankle vascular index (CAVI). Methods : Subjects aged between 25 and 64 years from a random population-based sample were evaluated between 2013-2016. Data from questionnaires, blood pressure, anthropometric measures, and blood samples were collected and analyzed. CAVI was measured using VaSera VS-1500N devise. Subjects with a history of CVD or chronic renal disease were excluded. Results : 1934 participants, 44.7 % of males, were included. The median age was 48 (Interquartile Range [IQR] 19) years, TG levels were 1.05 (0.793) mmol/L, and CAVI 7.24 (1.43) points. Prevalence of high CAVI was 10.0 % (14.5 % in males and 6.4 % in females; P < 0.001) and prevalence of hypertriglyceridemia was 20.2 % (29.2 % in males and 13 % in females; P <0.001). Correlation between TG and CAVI was 0.136 ( P <0.001). High CAVI values were more prevalent among participants with metabolic syndrome (MetS), high blood pressure, dysglycemia, abdominal obesity, high LDL-cholesterol, and high total cholesterol. Using binary regression analysis, high TG were associated with high CAVI, even after adjustment for other MetS components, age, gender, smoking status, LDL-c, and statin treatment (β=0.474, OR= 1.607, 95 % CI = 1.063-2.429, P =0.024). Conclusion : TG levels were correlated with ArSt, measured as CAVI. High TG was associated with high CAVI independent of multiple cardiometabolic risk factors. Awareness of the risks and targeted treatment of hypertriglyceridemia could further benefit in reducing the prevalence of CVD and events.

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Physiological Diagnostic Criteria for Vascular Failure

Cited by 199 publications

References 136 publications

Highly precise risk prediction model for new‐onset hypertension using artificial intelligence techniques

Highly precise risk prediction model for new‐onset hypertension using artificial intelligence techniques

Combination Therapy with Pemafibrate (K-877) and Pitavastatin Improves Vascular Endothelial Dysfunction in Dahl/Salt-sensitive Rats Fed a High-salt and High-fat Diet

Associations between high triglycerides and arterial stiffness in a population-based sample: Results from the Kardiovize 2030 study

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Physiological Diagnostic Criteria for Vascular Failure

Cited by 199 publications

References 136 publications

Highly precise risk prediction model for new‐onset hypertension using artificial intelligence techniques

Highly precise risk prediction model for new‐onset hypertension using artificial intelligence techniques

Combination Therapy with Pemafibrate (K-877) and Pitavastatin Improves Vascular Endothelial Dysfunction in Dahl/Salt-sensitive Rats Fed a High-salt and High-fat Diet​

Associations between high triglycerides and arterial stiffness in a population-based sample: Results from the Kardiovize 2030 study

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Combination Therapy with Pemafibrate (K-877) and Pitavastatin Improves Vascular Endothelial Dysfunction in Dahl/Salt-sensitive Rats Fed a High-salt and High-fat Diet