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Xu SD, Hao LL, Liu FF, Xu CZ. The effects of obstructive sleep apnea on blood pressure variability and load in patients with hypertension. Sleep Breath 2024; 28:1251-1260. [PMID: 38326691 DOI: 10.1007/s11325-024-03005-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2023] [Revised: 01/15/2024] [Accepted: 01/24/2024] [Indexed: 02/09/2024]
Abstract
BACKGROUND Hypertension frequently coexists with obstructive sleep apnea (OSA), and their interplay substantially impacts the prognosis of affected individuals. Investigating the influence of OSA on blood pressure variability (BPV) and blood pressure load (BPL) in hypertensive patients has become a focal point of clinical research. METHODS This cross-sectional study recruited hypertensive patients (n = 265) without discrimination and classified them into four groups based on their apnea-hypopnea index (AHI): control group (n = 40), AHI < 5; mild group (n = 74), 5 ≤ AHI ≤ 15; moderate group (n = 68), 15 < AHI ≤ 30; severe group (n = 83), AHI > 30. All participants underwent comprehensive assessments, including polysomnography (PSG) monitoring, 24-h ambulatory blood pressure (ABP) monitoring, cardiac Doppler ultrasound, and additional examinations when indicated. RESULTS BPV and BPL exhibited significant elevations in the moderate and severe OSA groups compared to the control and mild OSA groups (P < 0.05). Moreover, interventricular septum thickness and left ventricular end-diastolic volume (LVEDV) demonstrated higher values in the moderate and severe OSA groups (P < 0.05). Multiple stepwise regression analysis identified noteworthy risk factors for elevated BPV in hypertensive patients with OSA, including AHI, maximum apnea time, total times of oxygen reduction, and mean time of apnea. CONCLUSION Hypertensive patients with moderate to severe OSA exhibited substantially increased BPV and BPL. Moreover, BPV was correlated with AHI, maximum apnea time, total times of oxygen reduction, and mean time of apnea in hypertensive patients with OSA.
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Affiliation(s)
- Shao-Dong Xu
- Department of Cardiology, The Third Affiliated Hospital of Anhui Medical University, Hefei, 230001, Anhui Province, China.
| | - Ling-Li Hao
- Department of Sleep Monitoring Center, The Third Affiliated Hospital of Anhui Medical University, Hefei, 230001, Anhui Province, China
| | - Fei-Fei Liu
- Department of Sleep Monitoring Center, The Third Affiliated Hospital of Anhui Medical University, Hefei, 230001, Anhui Province, China
| | - Chuan-Zhi Xu
- Department of Electrocardiogram, The Third Affiliated Hospital of Anhui Medical University, Hefei, 230001, Anhui Province, China
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Guo X, Sun R, Cui X, Liu Y, Yang Y, Lin R, Yang H, Wu J, Xu J, Peng Y, Zheng X, Qin G, Chen J. Age-Specific Association Between Visit-to-Visit Blood Pressure Variability and Hearing Loss: A Population-Based Cohort Study. Innov Aging 2024; 8:igae047. [PMID: 38854854 PMCID: PMC11154138 DOI: 10.1093/geroni/igae047] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2023] [Indexed: 06/11/2024] Open
Abstract
Background and Objectives Hearing loss is common and undertreated, and the impact of blood pressure variability (BPV) on the development of hearing loss remains unclear. We aimed to examine the age-specific association between visit-to-visit BPV and hearing loss. Research Design and Methods This nationally representative cohort study included 3,939 adults over 50 years from the Health and Retirement Study in the United States. Variabilities of systolic blood pressure (SBP) and diastolic blood pressure (DBP) were assessed by standard deviation (SD), coefficient of variation, and variability independent of the mean (VIM), using SBP and DBP from 3 visits. Hearing loss was assessed by self-rated questions. Cox proportional risk models were used to evaluate age-specific associations (50-64, 65-79, and ≥80 years) between BPV and hearing loss. The generalized additive Cox models were further used to visualize the combined effect of age and BPV. Results During the follow-up up to 7.0 years, 700 participants developed hearing loss. Among people aged under 65 years, we observed a 36% increased risk of hearing loss with per-SD increment in VIM of SBP (hazard ratio [HR] per SD 1.36, 95% confidence interval [CI] 1.13-1.63) and a slightly significant association between VIM of DBP (HR per SD 1.21, 95% CI 1.01-1.45) and hearing loss. We did not observe significant associations among groups aged over 65 years (p > .05). The generalized additive Cox models also showed younger participants had stronger associations between BPV and hearing loss. Discussion and Implications Higher visit-to-visit variabilities of SBP were associated with an increased risk of hearing loss in middle-aged adults (50-65 years). Intervention in early BPV may help decrease hearing loss in adults aged over 50 years.
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Affiliation(s)
- Xinyue Guo
- Department of Biostatistics, National Health Commission Key Laboratory of Health Technology Assessment, Ministry of Education Key Laboratory of Public Health Safety, School of Public Health, Fudan University, Shanghai, China
| | - Renjian Sun
- Department of Health Management, Seventh People’s Hospital of Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Xiaorui Cui
- Department of Biostatistics, National Health Commission Key Laboratory of Health Technology Assessment, Ministry of Education Key Laboratory of Public Health Safety, School of Public Health, Fudan University, Shanghai, China
| | - Yahang Liu
- Department of Biostatistics, National Health Commission Key Laboratory of Health Technology Assessment, Ministry of Education Key Laboratory of Public Health Safety, School of Public Health, Fudan University, Shanghai, China
| | - Yating Yang
- Department of Biostatistics, National Health Commission Key Laboratory of Health Technology Assessment, Ministry of Education Key Laboratory of Public Health Safety, School of Public Health, Fudan University, Shanghai, China
| | - Ruilang Lin
- Department of Biostatistics, National Health Commission Key Laboratory of Health Technology Assessment, Ministry of Education Key Laboratory of Public Health Safety, School of Public Health, Fudan University, Shanghai, China
| | - Hui Yang
- Department of Biostatistics, National Health Commission Key Laboratory of Health Technology Assessment, Ministry of Education Key Laboratory of Public Health Safety, School of Public Health, Fudan University, Shanghai, China
| | - Jingyi Wu
- Department of Biostatistics, National Health Commission Key Laboratory of Health Technology Assessment, Ministry of Education Key Laboratory of Public Health Safety, School of Public Health, Fudan University, Shanghai, China
| | - Jiaqin Xu
- Department of Biostatistics, National Health Commission Key Laboratory of Health Technology Assessment, Ministry of Education Key Laboratory of Public Health Safety, School of Public Health, Fudan University, Shanghai, China
| | - Yuwei Peng
- Department of Biostatistics, National Health Commission Key Laboratory of Health Technology Assessment, Ministry of Education Key Laboratory of Public Health Safety, School of Public Health, Fudan University, Shanghai, China
| | - Xueying Zheng
- Department of Biostatistics, National Health Commission Key Laboratory of Health Technology Assessment, Ministry of Education Key Laboratory of Public Health Safety, School of Public Health, Fudan University, Shanghai, China
| | - Guoyou Qin
- Department of Biostatistics, National Health Commission Key Laboratory of Health Technology Assessment, Ministry of Education Key Laboratory of Public Health Safety, School of Public Health, Fudan University, Shanghai, China
- Shanghai Institute of Infectious Disease and Biosecurity, Fudan University, Shanghai, China
| | - Jiaohua Chen
- Department of Health Management, Seventh People’s Hospital of Shanghai University of Traditional Chinese Medicine, Shanghai, China
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Yang Y, Li D, Liu R, Hu Y, Chen S, Wu S, Tian Y. Brachial-ankle pulse wave velocity is a stronger predictor than blood pressure for atherosclerotic cardiovascular diseases and all-cause mortality: a cohort study. Hypertens Res 2023; 46:2100-2112. [PMID: 37237106 DOI: 10.1038/s41440-023-01313-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2022] [Revised: 04/23/2023] [Accepted: 04/28/2023] [Indexed: 05/28/2023]
Abstract
Whether brachial-ankle pulse wave velocity (baPWV) is a better predictive indicator than blood pressure (BP) for atherosclerotic cardiovascular diseases (ASCVD) events and all-cause mortality in the general population has not yet been established. The current study included 47,659 participants from the Kailuan cohort in China, who underwent the baPWV test and were free of ASCVD, atrial fibrillation, and cancer at baseline. The hazard ratios (HRs) of ASCVD and all-cause mortality were evaluated using the Cox proportional hazards model. The predictive ability of baPWV, systolic BP (SBP), and diastolic BP (DBP) for ASCVD and all-cause mortality was evaluated using the area under the curve (AUC) and concordance index (C-index). Within the median follow-up period of 3.27 and 3.32 person-years, 885 ASCVD events and 259 deaths occurred, respectively. The HRs of ASCVD and all-cause mortality increased with the increase of baPWV, SBP, and DBP. When baPWV, SBP, and DBP were analyzed as continuous variables, the adjusted HRs were 1.29 (95% CI, 1.22-1.37), 1.28 (95% CI, 1.20-1.37), and 1.26 (95% CI, 1.17-1.34) for each standard deviation increase, respectively. The AUC and C-index for baPWV in predicting ASCVD and all-cause mortality were 0.744 and 0.750, respectively, while those for SBP were 0.697 and 0.620, those for DBP were 0.666 and 0.585. The AUC and C-index of baPWV were higher than those of SBP and DBP (P < 0.001). Therefore, baPWV is an independent predictor of ASCVD and all-cause mortality in the general Chinese population, and its predictive ability is superior to that of BP. baPWV is a more ideal screening method for ASCVD in large-scale population.
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Affiliation(s)
- Yingping Yang
- Ministry of Education Key Laboratory of Environment and Health, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, No.13 Hangkong Road, Wuhan, 430030, China
- Department of Maternal and Child Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, No.13 Hangkong Road, Wuhan, 430030, China
| | - Dankang Li
- Ministry of Education Key Laboratory of Environment and Health, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, No.13 Hangkong Road, Wuhan, 430030, China
- Department of Maternal and Child Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, No.13 Hangkong Road, Wuhan, 430030, China
| | - Run Liu
- Ministry of Education Key Laboratory of Environment and Health, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, No.13 Hangkong Road, Wuhan, 430030, China
- Department of Maternal and Child Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, No.13 Hangkong Road, Wuhan, 430030, China
| | - Yonghua Hu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, No.38 Xueyuan Road, Beijing, 100191, China
| | - Shuohua Chen
- Department of Cardiology, Kailuan Hospital, North China University of Science and Technology, No.57 Xinhua East Road, Tangshan City, 063001, China
| | - Shouling Wu
- Department of Cardiology, Kailuan Hospital, North China University of Science and Technology, No.57 Xinhua East Road, Tangshan City, 063001, China.
| | - Yaohua Tian
- Ministry of Education Key Laboratory of Environment and Health, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, No.13 Hangkong Road, Wuhan, 430030, China.
- Department of Maternal and Child Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, No.13 Hangkong Road, Wuhan, 430030, China.
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Gruenewald T, Seeman TE, Choo TH, Scodes J, Snyder C, Pavlicova M, Weinstein M, Schwartz JE, Mukkamala R, Sloan RP. Cardiovascular variability, sociodemographics, and biomarkers of disease: the MIDUS study. Front Physiol 2023; 14:1234427. [PMID: 37693005 PMCID: PMC10484414 DOI: 10.3389/fphys.2023.1234427] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2023] [Accepted: 08/09/2023] [Indexed: 09/12/2023] Open
Abstract
Introduction: Like heart rate, blood pressure (BP) is not steady but varies over intervals as long as months to as short as consecutive cardiac cycles. This blood pressure variability (BPV) consists of regularly occurring oscillations as well as less well-organized changes and typically is computed as the standard deviation of multiple clinic visit-to-visit (VVV-BP) measures or from 24-h ambulatory BP recordings (ABPV). BP also varies on a beat-to-beat basis, quantified by methods that parse variation into discrete bins, e.g., low frequency (0.04-0.15 Hz, LF). However, beat-to-beat BPV requires continuous recordings that are not easily acquired. As a result, we know little about the relationship between LF-BPV and basic sociodemographic characteristics such as age, sex, and race and clinical conditions. Methods: We computed LF-BPV during an 11-min resting period in 2,118 participants in the Midlife in the US (MIDUS) study. Results: LF-BPV was negatively associated with age, greater in men than women, and unrelated to race or socioeconomic status. It was greater in participants with hypertension but unrelated to hyperlipidemia, hypertriglyceridemia, diabetes, elevated CRP, or obesity. LF-diastolic BPV (DBPV), but not-systolic BPV (SBPV), was negatively correlated with IL-6 and s-ICAM and positively correlated with urinary epinephrine and cortisol. Finally, LF-DBPV was negatively associated with mortality, an effect was rendered nonsignificant by adjustment by age but not other sociodemographic characteristics. Discussion: These findings, the first from a large, national sample, suggest that LF-BPV differs significantly from VVV-BP and ABPV. Confirming its relationship to sociodemographic risk factors and clinical outcomes requires further study with large and representative samples.
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Affiliation(s)
- Tara Gruenewald
- Department of Psychology, Chapman University, Orange, CA, United States
| | - Teresa E. Seeman
- David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, United States
| | - Tse-Hwei Choo
- Mental Health Data Science Division, New York State Psychiatric Institute, New York, NY, United States
| | - Jennifer Scodes
- Mental Health Data Science Division, New York State Psychiatric Institute, New York, NY, United States
| | - Clayton Snyder
- Mental Health Data Science Division, New York State Psychiatric Institute, New York, NY, United States
| | - Martina Pavlicova
- Department of Biostatistics, Mailman School of Public Health, Columbia University Irving Medical Center, New York, NY, United States
| | | | - Joseph E. Schwartz
- Renaissance School of Medicine, Stony Brook University, New York, NY, United States
- Department of Medicine, Columbia University Irving Medical Center, New York, NY, United States
| | - Ramakrishna Mukkamala
- Swanson School of Engineering, University of Pittsburgh, Pittsburgh, PA, United States
| | - Richard P. Sloan
- Division of Behavioral Medicine, Department of Psychiatry, Columbia University Irving Medical Center, New York, NY, United States
- New York State Psychiatric Institute, New York, NY, United States
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Park MJ, Choi KM. Association between Variability of Metabolic Risk Factors and Cardiometabolic Outcomes. Diabetes Metab J 2022; 46:49-62. [PMID: 35135078 PMCID: PMC8831817 DOI: 10.4093/dmj.2021.0316] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/10/2021] [Accepted: 12/07/2021] [Indexed: 11/10/2022] Open
Abstract
Despite strenuous efforts to reduce cardiovascular disease (CVD) risk by improving cardiometabolic risk factors, such as glucose and cholesterol levels, and blood pressure, there is still residual risk even in patients reaching treatment targets. Recently, researchers have begun to focus on the variability of metabolic variables to remove residual risks. Several clinical trials and cohort studies have reported a relationship between the variability of metabolic parameters and CVDs. Herein, we review the literature regarding the effect of metabolic factor variability and CVD risk, and describe possible mechanisms and potential treatment perspectives for reducing cardiometabolic risk factor variability.
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Affiliation(s)
- Min Jeong Park
- Division of Endocrinology & Metabolism, Department of Internal Medicine, Korea University College of Medicine, Seoul, Korea
| | - Kyung Mook Choi
- Division of Endocrinology & Metabolism, Department of Internal Medicine, Korea University College of Medicine, Seoul, Korea
- Corresponding author: Kyung Mook Choi https://orcid.org/0000-0001-6175-0225 Division of Endocrinology & Metabolism, Department of Internal Medicine, Korea University Guro Hospital, Korea University College of Medicine, 148 Gurodong-ro, Guro-gu, Seoul 08308, Korea E-mail:
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Schiffrin EL. From the Editor-in-Chief: Issue at a Glance. Am J Hypertens 2021; 34:1245-1246. [PMID: 34864846 DOI: 10.1093/ajh/hpab158] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Affiliation(s)
- Ernesto L Schiffrin
- Lady Davis Institute for Medical Research, and Department of Medicine, Sir Mortimer B. Davis, Jewish General Hospital, McGill University, 3755 Côte-Ste-Catherine Rd., Montreal, Quebec, Canada H3T 1E2
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Grossman E. The Importance of Blood Pressure Variability. Am J Hypertens 2021; 34:1259-1260. [PMID: 34379103 DOI: 10.1093/ajh/hpab127] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2021] [Accepted: 08/09/2021] [Indexed: 11/13/2022] Open
Affiliation(s)
- Ehud Grossman
- Internal Medicine Wing, The Chaim Sheba Medical Center, Tel-Hashomer, Israel
- Sackler Faculty of Medicine, Tel Aviv University, Tel-Aviv, Israel
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