Prognostic significance of mechanical biomarkers derived from pulse wave analysis for predicting long-term cardiovascular mortality in two population-based cohorts

Hao Min Cheng, Shao Yuan Chuang, Jiun Jr Wang, Yuan Ta Shih, Hsin Ning Wang, Chi Jung Huang, Jui Tzu Huang, Shih Hsien Sung, Edward G. Lakatta, Frank C P Yin, Pesus Chou, Chih Jung Yeh, Chyi Huey Bai, Wen Harn Pan, Chen Huan Chen

研究成果: 雜誌貢獻文章

12 引文 (Scopus)

摘要

Background Numerous mechanical biomarkers derived from pulse wave analysis (PWA) have been proposed to predict cardiovascular outcomes. However, whether these biomarkers carry independent prognostic value and clinical utility beyond traditional cardiovascular risk factors hasn't been systematically evaluated. We aimed to investigate the additive utility of PWA-derived biomarkers in two independent population-based cohorts. Methods PWA on central arterial pressure waveforms obtained from subjects without a prior history of cardiovascular diseases of two studies was conducted based on the wave transmission and reservoir-wave theory: firstly in the Kinmen study (1272 individuals, a median follow-up of 19.8 years); and then in the Cardiovascular Disease Risk Factors Two-Township Study (2221 individuals, median follow-up of 10 years). The incremental value of the biomarkers was evaluated by net reclassification index (NRI). Results In multivariate Cox analyses accounting for age, gender, body mass index, systolic blood pressure, fasting glucose, high-density- and low-density-lipoprotein cholesterol, and smoking, only systolic (SC) and diastolic rate constant (DC) of reservoir pressure could independently and consistently predict cardiovascular mortality in both cohorts and the combined cohort (SC: hazard ratio 1.18 [95% confidence interval 1.08-1.28, p <0.001; DC: 1.18 [1.09-1.28], p <0.001]. Risk prediction estimates in traditional risk prediction models were significantly more accurate when incorporating peak of reservoir pressure (NRI = 0.049, p = 0.0361), SC (NRI = 0.043, p = 0.0236) and DC (NRI = 0.054, p = 0.047). Conclusions Of all PWA-derived biomarkers, SC and DC were consistently identified as valuable parameters for incremental cardiovascular risk prediction in two large prospective cohorts.

原文英語
頁(從 - 到)388-395
頁數8
期刊International Journal of Cardiology
215
DOIs
出版狀態已發佈 - 七月 15 2016

指紋

Pulse Wave Analysis
Biomarkers
Mortality
Population
Cardiovascular Diseases
Blood Pressure
Pressure
LDL Cholesterol
Fasting
Arterial Pressure
Body Mass Index
Multivariate Analysis
Smoking
Confidence Intervals
Glucose

ASJC Scopus subject areas

  • Cardiology and Cardiovascular Medicine

引用此文

Prognostic significance of mechanical biomarkers derived from pulse wave analysis for predicting long-term cardiovascular mortality in two population-based cohorts. / Cheng, Hao Min; Chuang, Shao Yuan; Wang, Jiun Jr; Shih, Yuan Ta; Wang, Hsin Ning; Huang, Chi Jung; Huang, Jui Tzu; Sung, Shih Hsien; Lakatta, Edward G.; Yin, Frank C P; Chou, Pesus; Yeh, Chih Jung; Bai, Chyi Huey; Pan, Wen Harn; Chen, Chen Huan.

於: International Journal of Cardiology, 卷 215, 15.07.2016, p. 388-395.

研究成果: 雜誌貢獻文章

Cheng, HM, Chuang, SY, Wang, JJ, Shih, YT, Wang, HN, Huang, CJ, Huang, JT, Sung, SH, Lakatta, EG, Yin, FCP, Chou, P, Yeh, CJ, Bai, CH, Pan, WH & Chen, CH 2016, 'Prognostic significance of mechanical biomarkers derived from pulse wave analysis for predicting long-term cardiovascular mortality in two population-based cohorts', International Journal of Cardiology, 卷 215, 頁 388-395. https://doi.org/10.1016/j.ijcard.2016.04.070
Cheng, Hao Min ; Chuang, Shao Yuan ; Wang, Jiun Jr ; Shih, Yuan Ta ; Wang, Hsin Ning ; Huang, Chi Jung ; Huang, Jui Tzu ; Sung, Shih Hsien ; Lakatta, Edward G. ; Yin, Frank C P ; Chou, Pesus ; Yeh, Chih Jung ; Bai, Chyi Huey ; Pan, Wen Harn ; Chen, Chen Huan. / Prognostic significance of mechanical biomarkers derived from pulse wave analysis for predicting long-term cardiovascular mortality in two population-based cohorts. 於: International Journal of Cardiology. 2016 ; 卷 215. 頁 388-395.
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title = "Prognostic significance of mechanical biomarkers derived from pulse wave analysis for predicting long-term cardiovascular mortality in two population-based cohorts",
abstract = "Background Numerous mechanical biomarkers derived from pulse wave analysis (PWA) have been proposed to predict cardiovascular outcomes. However, whether these biomarkers carry independent prognostic value and clinical utility beyond traditional cardiovascular risk factors hasn't been systematically evaluated. We aimed to investigate the additive utility of PWA-derived biomarkers in two independent population-based cohorts. Methods PWA on central arterial pressure waveforms obtained from subjects without a prior history of cardiovascular diseases of two studies was conducted based on the wave transmission and reservoir-wave theory: firstly in the Kinmen study (1272 individuals, a median follow-up of 19.8 years); and then in the Cardiovascular Disease Risk Factors Two-Township Study (2221 individuals, median follow-up of 10 years). The incremental value of the biomarkers was evaluated by net reclassification index (NRI). Results In multivariate Cox analyses accounting for age, gender, body mass index, systolic blood pressure, fasting glucose, high-density- and low-density-lipoprotein cholesterol, and smoking, only systolic (SC) and diastolic rate constant (DC) of reservoir pressure could independently and consistently predict cardiovascular mortality in both cohorts and the combined cohort (SC: hazard ratio 1.18 [95{\%} confidence interval 1.08-1.28, p <0.001; DC: 1.18 [1.09-1.28], p <0.001]. Risk prediction estimates in traditional risk prediction models were significantly more accurate when incorporating peak of reservoir pressure (NRI = 0.049, p = 0.0361), SC (NRI = 0.043, p = 0.0236) and DC (NRI = 0.054, p = 0.047). Conclusions Of all PWA-derived biomarkers, SC and DC were consistently identified as valuable parameters for incremental cardiovascular risk prediction in two large prospective cohorts.",
keywords = "Epidemiology, Mortality, Pulse wave analysis, Reservoir pressure, Vascular aging, Wave reflection",
author = "Cheng, {Hao Min} and Chuang, {Shao Yuan} and Wang, {Jiun Jr} and Shih, {Yuan Ta} and Wang, {Hsin Ning} and Huang, {Chi Jung} and Huang, {Jui Tzu} and Sung, {Shih Hsien} and Lakatta, {Edward G.} and Yin, {Frank C P} and Pesus Chou and Yeh, {Chih Jung} and Bai, {Chyi Huey} and Pan, {Wen Harn} and Chen, {Chen Huan}",
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T1 - Prognostic significance of mechanical biomarkers derived from pulse wave analysis for predicting long-term cardiovascular mortality in two population-based cohorts

AU - Cheng, Hao Min

AU - Chuang, Shao Yuan

AU - Wang, Jiun Jr

AU - Shih, Yuan Ta

AU - Wang, Hsin Ning

AU - Huang, Chi Jung

AU - Huang, Jui Tzu

AU - Sung, Shih Hsien

AU - Lakatta, Edward G.

AU - Yin, Frank C P

AU - Chou, Pesus

AU - Yeh, Chih Jung

AU - Bai, Chyi Huey

AU - Pan, Wen Harn

AU - Chen, Chen Huan

PY - 2016/7/15

Y1 - 2016/7/15

N2 - Background Numerous mechanical biomarkers derived from pulse wave analysis (PWA) have been proposed to predict cardiovascular outcomes. However, whether these biomarkers carry independent prognostic value and clinical utility beyond traditional cardiovascular risk factors hasn't been systematically evaluated. We aimed to investigate the additive utility of PWA-derived biomarkers in two independent population-based cohorts. Methods PWA on central arterial pressure waveforms obtained from subjects without a prior history of cardiovascular diseases of two studies was conducted based on the wave transmission and reservoir-wave theory: firstly in the Kinmen study (1272 individuals, a median follow-up of 19.8 years); and then in the Cardiovascular Disease Risk Factors Two-Township Study (2221 individuals, median follow-up of 10 years). The incremental value of the biomarkers was evaluated by net reclassification index (NRI). Results In multivariate Cox analyses accounting for age, gender, body mass index, systolic blood pressure, fasting glucose, high-density- and low-density-lipoprotein cholesterol, and smoking, only systolic (SC) and diastolic rate constant (DC) of reservoir pressure could independently and consistently predict cardiovascular mortality in both cohorts and the combined cohort (SC: hazard ratio 1.18 [95% confidence interval 1.08-1.28, p <0.001; DC: 1.18 [1.09-1.28], p <0.001]. Risk prediction estimates in traditional risk prediction models were significantly more accurate when incorporating peak of reservoir pressure (NRI = 0.049, p = 0.0361), SC (NRI = 0.043, p = 0.0236) and DC (NRI = 0.054, p = 0.047). Conclusions Of all PWA-derived biomarkers, SC and DC were consistently identified as valuable parameters for incremental cardiovascular risk prediction in two large prospective cohorts.

AB - Background Numerous mechanical biomarkers derived from pulse wave analysis (PWA) have been proposed to predict cardiovascular outcomes. However, whether these biomarkers carry independent prognostic value and clinical utility beyond traditional cardiovascular risk factors hasn't been systematically evaluated. We aimed to investigate the additive utility of PWA-derived biomarkers in two independent population-based cohorts. Methods PWA on central arterial pressure waveforms obtained from subjects without a prior history of cardiovascular diseases of two studies was conducted based on the wave transmission and reservoir-wave theory: firstly in the Kinmen study (1272 individuals, a median follow-up of 19.8 years); and then in the Cardiovascular Disease Risk Factors Two-Township Study (2221 individuals, median follow-up of 10 years). The incremental value of the biomarkers was evaluated by net reclassification index (NRI). Results In multivariate Cox analyses accounting for age, gender, body mass index, systolic blood pressure, fasting glucose, high-density- and low-density-lipoprotein cholesterol, and smoking, only systolic (SC) and diastolic rate constant (DC) of reservoir pressure could independently and consistently predict cardiovascular mortality in both cohorts and the combined cohort (SC: hazard ratio 1.18 [95% confidence interval 1.08-1.28, p <0.001; DC: 1.18 [1.09-1.28], p <0.001]. Risk prediction estimates in traditional risk prediction models were significantly more accurate when incorporating peak of reservoir pressure (NRI = 0.049, p = 0.0361), SC (NRI = 0.043, p = 0.0236) and DC (NRI = 0.054, p = 0.047). Conclusions Of all PWA-derived biomarkers, SC and DC were consistently identified as valuable parameters for incremental cardiovascular risk prediction in two large prospective cohorts.

KW - Epidemiology

KW - Mortality

KW - Pulse wave analysis

KW - Reservoir pressure

KW - Vascular aging

KW - Wave reflection

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