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Fang SC, Wu YL, Tsai PS. Heart Rate Variability and Risk of All-Cause Death and Cardiovascular Events in Patients With Cardiovascular Disease: A Meta-Analysis of Cohort Studies. Biol Res Nurs 2019; 22:45-56. [PMID: 31558032 DOI: 10.1177/1099800419877442] [Citation(s) in RCA: 121] [Impact Index Per Article: 24.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/11/2023]
Abstract
Lower heart rate variability (HRV) is associated with a higher risk of cardiovascular events and mortality, although the extent of the association is uncertain. We performed a meta-analysis of cohort studies to elucidate the association between HRV and the risk of all-cause death or cardiovascular events in patients with cardiovascular disease (CVD) during a follow-up of at least 1 year. We searched four databases (PubMed, MEDLINE, Embase, and Cochrane Central Register of Controlled Trials) and extracted the adjusted hazard ratio (HR) from eligible studies. We included 28 cohort studies involving 3,094 participants in the meta-analysis. Results revealed that lower HRV was associated with a higher risk of all-cause death and cardiovascular events; the pooled HR was 2.27 (95% confidence interval [CI]: 1.72, 3.00) and 1.41 (95% CI: 1.16, 1.72), respectively. In subgroup analyses, the pooled HR of all-cause death was significant for patients with acute myocardial infarction (AMI) but not for those with heart failure. The pooled HR for cardiovascular events was significant for the subgroup of patients with AMI and acute coronary syndrome but not for those with coronary artery disease and heart failure. Additionally, both time and frequency domains of HRV were significantly associated with risk of all-cause death and cardiovascular events in patients with CVD.
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Affiliation(s)
- Su-Chen Fang
- School of Nursing, College of Nursing, Taipei Medical University, Taipei
| | - Yu-Lin Wu
- Department of Nursing, St. Mary's Junior College of Medicine, Nursing and Management, Yilan
| | - Pei-Shan Tsai
- School of Nursing, College of Nursing, Taipei Medical University, Taipei.,Department of Nursing and Research Center of Big Data and Meta-Analysis, Wan Fang Hospital, Taipei Medical University, Taipei.,Sleep Research Center, Taipei Medical University Hospital, Taipei
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Botsva N, Naishtetik I, Khimion L, Chernetchenko D. Predictors of aging based on the analysis of heart rate variability. PACING AND CLINICAL ELECTROPHYSIOLOGY: PACE 2017; 40:1269-1278. [PMID: 28983984 DOI: 10.1111/pace.13180] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/23/2017] [Revised: 07/31/2017] [Accepted: 08/14/2017] [Indexed: 12/11/2022]
Abstract
BACKGROUND The current significant progress in the use of heart rate variability in the solution of many diagnostic and therapeutic problems is determined by the availability of standardized methods of measurement and physiological interpretation of heart rate variability indices on the one hand and the high technological level of state-of-the-art electronic measuring equipment that is used for automatic registration and computer processing of cardio-signals. METHODS A retrospective analysis of anonymized cardio screening results of 22,433 adult residents of 565 settlements (cities and villages) across all 20 administrative districts of the Khmelnytskyi Region (Ukraine) was conducted to find a statistically significant connection between individual heart rate variability parameters and the age of people. RESULTS Primary statistical analysis and visualization showed a correlation between the selected heart rate variability parameters and the age and sex of the examined persons. The study found values of the predicted age slightly over estimation versus the actual age for very young test subjects and below estimation for elderly subjects. CONCLUSION The use of neural network computations and the modification of the algorithm through the construction of individual training samples for different age intervals, and the creation of individual ensembles of classification neural networks, therefore achieved a prediction of the age of examined persons based on the values of their time and frequency domain heart rate variability indices, with 87% accuracy for women and 85% accuracy for men in the 66-85 years age interval and at least 85% for age groups across the entire sample.
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Affiliation(s)
- Nataliia Botsva
- Oles Honchar Dnipropetrovsk National University, 20 Kazakova Str., Dnipro, 49010, Ukraine
| | - Iryna Naishtetik
- Academy of the Postgraduate Education named after P.L. Schupik, Dorogozhytska Str., Kyiv, 04112, Ukraine
| | - Ludmyla Khimion
- Academy of the Postgraduate Education named after P.L. Schupik, Dorogozhytska Str., Kyiv, 04112, Ukraine
| | - Dmitriy Chernetchenko
- Oles Honchar Dnipropetrovsk National University, 20 Kazakova Str., Dnipro, 49010, Ukraine
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Ouyang H, Tian J, Sun G, Zou Y, Liu Z, Li H, Zhao L, Shi B, Fan Y, Fan Y, Wang ZL, Li Z. Self-Powered Pulse Sensor for Antidiastole of Cardiovascular Disease. ADVANCED MATERIALS (DEERFIELD BEACH, FLA.) 2017; 29:1703456. [PMID: 28863247 DOI: 10.1002/adma.201703456] [Citation(s) in RCA: 154] [Impact Index Per Article: 22.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/20/2017] [Revised: 07/27/2017] [Indexed: 05/21/2023]
Abstract
Cardiovascular diseases are the leading cause of death globally; fortunately, 90% of cardiovascular diseases are preventable by long-term monitoring of physiological signals. Stable, ultralow power consumption, and high-sensitivity sensors are significant for miniaturized wearable physiological signal monitoring systems. Here, this study proposes a flexible self-powered ultrasensitive pulse sensor (SUPS) based on triboelectric active sensor with excellent output performance (1.52 V), high peak signal-noise ratio (45 dB), long-term performance (107 cycles), and low cost price. Attributed to the crucial features of acquiring easy-processed pulse waveform, which is consistent with second derivative of signal from conventional pulse sensor, SUPS can be integrated with a bluetooth chip to provide accurate, wireless, and real-time monitoring of pulse signals of cardiovascular system on a smart phone/PC. Antidiastole of coronary heart disease, atrial septal defect, and atrial fibrillation are made, and the arrhythmia (atrial fibrillation) is indicative diagnosed from health, by characteristic exponent analysis of pulse signals accessed from volunteer patients. This SUPS is expected to be applied in self-powered, wearable intelligent mobile diagnosis of cardiovascular disease in the future.
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Affiliation(s)
- Han Ouyang
- Beijing Institute of Nanoenergy and Nanosystems, Chinese Academy of Sciences, Beijing, 100083, China
- CAS Center for Excellence in Nanoscience, National Center for Nanoscience and Technology (NCNST), Beijing, 100190, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Jingjing Tian
- Beijing Institute of Nanoenergy and Nanosystems, Chinese Academy of Sciences, Beijing, 100083, China
- CAS Center for Excellence in Nanoscience, National Center for Nanoscience and Technology (NCNST), Beijing, 100190, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Guanglong Sun
- Department of Cardiac Surgery, Beijing Anzhen Hospital, Capital Medical University, Beijing Institute of Heart Lung and Blood Vessel Disease, Beijing, 100029, China
| | - Yang Zou
- Beijing Institute of Nanoenergy and Nanosystems, Chinese Academy of Sciences, Beijing, 100083, China
- CAS Center for Excellence in Nanoscience, National Center for Nanoscience and Technology (NCNST), Beijing, 100190, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Zhuo Liu
- Beijing Institute of Nanoenergy and Nanosystems, Chinese Academy of Sciences, Beijing, 100083, China
- School of Biological Science and Medical Engineering, Beihang University, Beijing, 100191, China
| | - Hu Li
- Beijing Institute of Nanoenergy and Nanosystems, Chinese Academy of Sciences, Beijing, 100083, China
- School of Biological Science and Medical Engineering, Beihang University, Beijing, 100191, China
| | - Luming Zhao
- Beijing Institute of Nanoenergy and Nanosystems, Chinese Academy of Sciences, Beijing, 100083, China
- CAS Center for Excellence in Nanoscience, National Center for Nanoscience and Technology (NCNST), Beijing, 100190, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Bojing Shi
- Beijing Institute of Nanoenergy and Nanosystems, Chinese Academy of Sciences, Beijing, 100083, China
- CAS Center for Excellence in Nanoscience, National Center for Nanoscience and Technology (NCNST), Beijing, 100190, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Yubo Fan
- School of Biological Science and Medical Engineering, Beihang University, Beijing, 100191, China
| | - Yifan Fan
- Department of Cardiology, Beijing Chaoyang Hospital, Capital Medical University, Beijing Key Laboratory of Hypertension, Beijing, 100020, China
| | - Zhong Lin Wang
- Beijing Institute of Nanoenergy and Nanosystems, Chinese Academy of Sciences, Beijing, 100083, China
- CAS Center for Excellence in Nanoscience, National Center for Nanoscience and Technology (NCNST), Beijing, 100190, China
- School of Materials Science and Engineering, Georgia Institute of Technology, Atlanta, GA, 30332-0245, USA
| | - Zhou Li
- Beijing Institute of Nanoenergy and Nanosystems, Chinese Academy of Sciences, Beijing, 100083, China
- CAS Center for Excellence in Nanoscience, National Center for Nanoscience and Technology (NCNST), Beijing, 100190, China
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Silva RMFLD, Silva CAB, Greco OJ, Moreira MDCV. Spectral analysis related to bare-metal and drug-eluting coronary stent implantation. Arq Bras Cardiol 2014; 103:138-45. [PMID: 25029473 PMCID: PMC4150665 DOI: 10.5935/abc.20140094] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2013] [Accepted: 04/30/2014] [Indexed: 11/20/2022] Open
Abstract
BACKGROUND The autonomic nervous system plays a central role in cardiovascular regulation; sympathetic activation occurs during myocardial ischemia. OBJECTIVE To assess the spectral analysis of heart rate variability during stent implantation, comparing the types of stent. METHODS This study assessed 61 patients (mean age, 64.0 years; 35 men) with ischemic heart disease and indication for stenting. Stent implantation was performed under Holter monitoring to record the spectral analysis of heart rate variability (Fourier transform), measuring the low-frequency (LF) and high-frequency (HF) components, and the LF/HF ratio before and during the procedure. RESULTS Bare-metal stent was implanted in 34 patients, while the others received drug-eluting stents. The right coronary artery was approached in 21 patients, the left anterior descending, in 28, and the circumflex, in 9. As compared with the pre-stenting period, all patients showed an increase in LF and HF during stent implantation (658 versus 185 ms2, p = 0.00; 322 versus 121, p = 0.00, respectively), with no change in LF/HF. During stent implantation, LF was 864 ms2 in patients with bare-metal stents, and 398 ms2 in those with drug-eluting stents (p = 0.00). The spectral analysis of heart rate variability showed no association with diabetes mellitus, family history, clinical presentation, beta-blockers, age, and vessel or its segment. CONCLUSIONS Stent implantation resulted in concomitant sympathetic and vagal activations. Diabetes mellitus, use of beta-blockers, and the vessel approached showed no influence on the spectral analysis of heart rate variability. Sympathetic activation was lower during the implantation of drug-eluting stents.
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