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Fortune JD, Coppa NE, Haq KT, Patel H, Tereshchenko LG. Digitizing ECG image: A new method and open-source software code. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 2022; 221:106890. [PMID: 35598436 PMCID: PMC9286778 DOI: 10.1016/j.cmpb.2022.106890] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/24/2021] [Revised: 05/07/2022] [Accepted: 05/12/2022] [Indexed: 06/03/2023]
Abstract
BACKGROUND AND OBJECTIVE We aimed to develop and validate an open-source code ECG-digitizing tool and assess agreements of ECG measurements across three types of median beats, comprised of digitally recorded simultaneous and asynchronous ECG leads and digitized asynchronous ECG leads. METHODS We used the data of clinical studies participants (n = 230; mean age 30±15 y; 25% female; 52% had the cardiovascular disease) with available both digitally recorded and printed on paper and then scanned ECGs, split into development (n = 150) and validation (n = 80) datasets. The agreement between ECG and VCG measurements on the digitally recorded time-coherent median beat, representative asynchronous digitized, and digitally recorded beats was assessed by Bland-Altman analysis. RESULTS The sample-per-sample comparison of digitally recorded and digitized signals showed a very high correlation (0.977), a small mean difference (9.3 µV), and root mean squared error (25.9 µV). Agreement between digitally recorded and digitized representative beat was high [area spatial ventricular gradient (SVG) elevation bias 2.5(95% limits of agreement [LOA] -7.9-13.0)°; precision 96.8%; inter-class correlation [ICC] 0.988; Lin's concordance coefficient ρc 0.97(95% confidence interval [CI] 0.95-0.98)]. Agreement between digitally recorded asynchronous and time-coherent median beats was moderate for area-based VCG metrics (spatial QRS-T angle bias 1.4(95%LOA -33.2-30.3)°; precision 94.8%; ICC 0.95; Lin's concordance coefficient ρc 0.90(95%CI 0.82-0.95)]. CONCLUSIONS We developed and validated an open-source software tool for paper-ECG digitization. Asynchronous ECG leads are the primary source of disagreement in measurements on digitally recorded and digitized ECGs.
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Affiliation(s)
| | | | - Kazi T Haq
- Oregon Health and Science University, Knight Cardiovascular Institute, Portland, OR, United States
| | - Hetal Patel
- Oregon Health and Science University, Knight Cardiovascular Institute, Portland, OR, United States; Chicago Medical School at Rosalind Franklin University, IL, United States
| | - Larisa G Tereshchenko
- Oregon Health and Science University, Knight Cardiovascular Institute, Portland, OR, United States; Department of Quantitative Health Sciences, Cleveland Clinic Lerner Research Institute, Larisa Tereshchenko, 9500 Euclid Ave, JJN3-01. , Cleveland, OH 44195, United States.
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Hurley NC, Spatz ES, Krumholz HM, Jafari R, Mortazavi BJ. A Survey of Challenges and Opportunities in Sensing and Analytics for Risk Factors of Cardiovascular Disorders. ACM TRANSACTIONS ON COMPUTING FOR HEALTHCARE 2021; 2:9. [PMID: 34337602 PMCID: PMC8320445 DOI: 10.1145/3417958] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/01/2019] [Accepted: 08/01/2020] [Indexed: 10/22/2022]
Abstract
Cardiovascular disorders cause nearly one in three deaths in the United States. Short- and long-term care for these disorders is often determined in short-term settings. However, these decisions are made with minimal longitudinal and long-term data. To overcome this bias towards data from acute care settings, improved longitudinal monitoring for cardiovascular patients is needed. Longitudinal monitoring provides a more comprehensive picture of patient health, allowing for informed decision making. This work surveys sensing and machine learning in the field of remote health monitoring for cardiovascular disorders. We highlight three needs in the design of new smart health technologies: (1) need for sensing technologies that track longitudinal trends of the cardiovascular disorder despite infrequent, noisy, or missing data measurements; (2) need for new analytic techniques designed in a longitudinal, continual fashion to aid in the development of new risk prediction techniques and in tracking disease progression; and (3) need for personalized and interpretable machine learning techniques, allowing for advancements in clinical decision making. We highlight these needs based upon the current state of the art in smart health technologies and analytics. We then discuss opportunities in addressing these needs for development of smart health technologies for the field of cardiovascular disorders and care.
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Vavrinsky E, Subjak J, Donoval M, Wagner A, Zavodnik T, Svobodova H. Application of Modern Multi-Sensor Holter in Diagnosis and Treatment. SENSORS (BASEL, SWITZERLAND) 2020; 20:E2663. [PMID: 32392697 PMCID: PMC7273207 DOI: 10.3390/s20092663] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/31/2020] [Revised: 05/04/2020] [Accepted: 05/04/2020] [Indexed: 12/11/2022]
Abstract
Modern Holter devices are very trendy tools used in medicine, research, or sport. They monitor a variety of human physiological or pathophysiological signals. Nowadays, Holter devices have been developing very fast. New innovative products come to the market every day. They have become smaller, smarter, cheaper, have ultra-low power consumption, do not limit everyday life, and allow comfortable measurements of humans to be accomplished in a familiar and natural environment, without extreme fear from doctors. People can be informed about their health and 24/7 monitoring can sometimes easily detect specific diseases, which are normally passed during routine ambulance operation. However, there is a problem with the reliability, quality, and quantity of the collected data. In normal life, there may be a loss of signal recording, abnormal growth of artifacts, etc. At this point, there is a need for multiple sensors capturing single variables in parallel by different sensing methods to complement these methods and diminish the level of artifacts. We can also sense multiple different signals that are complementary and give us a coherent picture. In this article, we describe actual interesting multi-sensor principles on the grounds of our own long-year experiences and many experiments.
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Affiliation(s)
- Erik Vavrinsky
- Institute of Electronics and Photonics, Faculty of Electrical Engineering and Information Technology, Slovak University of Technology, Ilkovicova 3, 81219 Bratislava, Slovakia; (J.S.); (M.D.); (T.Z.)
- Institute of Medical Physics, Biophysics, Informatics and Telemedicine, Faculty of Medicine, Comenius University, Sasinkova 2, 81272 Bratislava, Slovakia
| | - Jan Subjak
- Institute of Electronics and Photonics, Faculty of Electrical Engineering and Information Technology, Slovak University of Technology, Ilkovicova 3, 81219 Bratislava, Slovakia; (J.S.); (M.D.); (T.Z.)
| | - Martin Donoval
- Institute of Electronics and Photonics, Faculty of Electrical Engineering and Information Technology, Slovak University of Technology, Ilkovicova 3, 81219 Bratislava, Slovakia; (J.S.); (M.D.); (T.Z.)
| | - Alexandra Wagner
- Department of Simulation and Virtual Medical Education, Faculty of Medicine, Comenius University, Sasinkova 4, 81272 Bratislava, Slovakia; (A.W.); (H.S.)
| | - Tomas Zavodnik
- Institute of Electronics and Photonics, Faculty of Electrical Engineering and Information Technology, Slovak University of Technology, Ilkovicova 3, 81219 Bratislava, Slovakia; (J.S.); (M.D.); (T.Z.)
| | - Helena Svobodova
- Department of Simulation and Virtual Medical Education, Faculty of Medicine, Comenius University, Sasinkova 4, 81272 Bratislava, Slovakia; (A.W.); (H.S.)
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Soroudi A, Hernández N, Berglin L, Nierstrasz V. Electrode placement in electrocardiography smart garments: A review. J Electrocardiol 2019; 57:27-30. [PMID: 31473476 DOI: 10.1016/j.jelectrocard.2019.08.015] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2019] [Revised: 08/09/2019] [Accepted: 08/21/2019] [Indexed: 12/15/2022]
Abstract
Wearable Electrocardiography (ECG) sensing textiles have been widely used due to their high flexibility, comfort, reusability and the possibility to be used for home-based and real-time measurements. Textile electrodes are dry and non-adhesive, therefor unlike conventional gel electrodes, they don't cause skin irritation and are more user-friendly especially for long-term and continuous monitoring outside the hospital. However, the challenge with textile electrodes is that the quality and reliability of recorded ECG signals by smart garments are more sensitive to different factors such as electrode placement, skin humidity, user activities and contact pressure. This review will particularly focus on the research findings regarding the influence of electrode placement on the quality of biosignal sensing, and will introduce the methods used by researchers to measure the optimal positions of the electrodes in wearable ECG garments. The review will help the designers to take into account different parameters, which affect the data quality, reliability and comfort, when selecting the electrode placement in a wearable ECG garment.
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Affiliation(s)
- Azadeh Soroudi
- Textile Materials Technology, Department of Textile Technology, Faculty of Textiles, Engineering and Business, University of Boras, 501 90 Boras, Sweden.
| | - Niina Hernández
- Textile Materials Technology, Department of Textile Technology, Faculty of Textiles, Engineering and Business, University of Boras, 501 90 Boras, Sweden
| | - Lena Berglin
- Textile Materials Technology, Department of Textile Technology, Faculty of Textiles, Engineering and Business, University of Boras, 501 90 Boras, Sweden
| | - Vincent Nierstrasz
- Textile Materials Technology, Department of Textile Technology, Faculty of Textiles, Engineering and Business, University of Boras, 501 90 Boras, Sweden
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Seshadri DR, Li RT, Voos JE, Rowbottom JR, Alfes CM, Zorman CA, Drummond CK. Wearable sensors for monitoring the internal and external workload of the athlete. NPJ Digit Med 2019; 2:71. [PMID: 31372506 PMCID: PMC6662809 DOI: 10.1038/s41746-019-0149-2] [Citation(s) in RCA: 80] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2018] [Accepted: 07/08/2019] [Indexed: 11/29/2022] Open
Abstract
The convergence of semiconductor technology, physiology, and predictive health analytics from wearable devices has advanced its clinical and translational utility for sports. The detection and subsequent application of metrics pertinent to and indicative of the physical performance, physiological status, biochemical composition, and mental alertness of the athlete has been shown to reduce the risk of injuries and improve performance and has enabled the development of athlete-centered protocols and treatment plans by team physicians and trainers. Our discussions in this review include commercially available devices, as well as those described in scientific literature to provide an understanding of wearable sensors for sports medicine. The primary objective of this paper is to provide a comprehensive review of the applications of wearable technology for assessing the biomechanical and physiological parameters of the athlete. A secondary objective of this paper is to identify collaborative research opportunities among academic research groups, sports medicine health clinics, and sports team performance programs to further the utility of this technology to assist in the return-to-play for athletes across various sporting domains. A companion paper discusses the use of wearables to monitor the biochemical profile and mental acuity of the athlete.
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Affiliation(s)
- Dhruv R. Seshadri
- Department of Biomedical Engineering, Case Western Reserve University, 10900 Euclid Avenue, Cleveland, OH 44106 USA
| | - Ryan T. Li
- Department of Orthopaedic Surgery, University Hospitals Cleveland Medical Center, Cleveland, OH 44106 USA
| | - James E. Voos
- University Hospitals Sports Medicine Institute, Cleveland, OH 44106 USA
| | - James R. Rowbottom
- Department of Cardiothoracic Anesthesiology, The Cleveland Clinic, 9500 Euclid Avenue, Cleveland, OH 44195 USA
| | - Celeste M. Alfes
- Frances Payne Bolton School of Nursing, Case Western Reserve University, 9501 Euclid Avenue, Cleveland, OH 44106 USA
| | - Christian A. Zorman
- Department of Electrical Engineering and Computer Science, Case Western Reserve University, 10900 Euclid Avenue, Cleveland, OH 44106 USA
| | - Colin K. Drummond
- Department of Biomedical Engineering, Case Western Reserve University, 10900 Euclid Avenue, Cleveland, OH 44106 USA
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Sen-Gupta E, Wright DE, Caccese JW, Wright Jr. JA, Jortberg E, Bhatkar V, Ceruolo M, Ghaffari R, Clason DL, Maynard JP, Combs AH. A Pivotal Study to Validate the Performance of a Novel Wearable Sensor and System for Biometric Monitoring in Clinical and Remote Environments. Digit Biomark 2019; 3:1-13. [PMID: 32095764 PMCID: PMC7015390 DOI: 10.1159/000493642] [Citation(s) in RCA: 22] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2018] [Accepted: 09/11/2018] [Indexed: 12/30/2022] Open
Abstract
BACKGROUND Increasingly, drug and device clinical trials are tracking activity levels and other quality of life indices as endpoints for therapeutic efficacy. Trials have traditionally required intermittent subject visits to the clinic that are artificial, activity-intensive, and infrequent, making trend and event detection between visits difficult. Thus, there is an unmet need for wearable sensors that produce clinical quality and medical grade physiological data from subjects in the home. The current study was designed to validate the BioStamp nPoint® system (MC10 Inc., Lexington, MA, USA), a new technology designed to meet this need. OBJECTIVE To evaluate the accuracy, performance, and ease of use of an end-to-end system called the BioStamp nPoint. The system consists of an investigator portal for design of trials and data review, conformal, low-profile, wearable biosensors that adhere to the skin, a companion technology for wireless data transfer to a proprietary cloud, and algorithms for analyzing physiological, biometric, and contextual data for clinical research. METHODS A prospective, nonrandomized clinical trial was conducted on 30 healthy adult volunteers over the course of two continuous days and nights. Supervised and unsupervised study activities enabled performance validation in clinical and remote (simulated "at home") environments. System outputs for heart rate (HR), heart rate variability (HRV) (including root mean square of successive differences [RMSSD] and low frequency/high frequency ratio), activity classification during prescribed activities (lying, sitting, standing, walking, stationary biking, and sleep), step count during walking, posture characterization, and sleep metrics including onset/wake times, sleep duration, and respiration rate (RR) during sleep were evaluated. Outputs were compared to FDA-cleared comparator devices for HR, HRV, and RR and to ground truth investigator observations for activity and posture classifications, step count, and sleep events. RESULTS Thirty participants (77% male, 23% female; mean age 35.9 ± 10.1 years; mean BMI 28.1 ± 3.6) were enrolled in the study. The BioStamp nPoint system accurately measured HR and HRV (correlations: HR = 0.957, HRV RMSSD = 0.965, HRV ratio = 0.861) when compared to ActiheartTM. The system accurately monitored RR (mean absolute error [MAE] = 1.3 breaths/min) during sleep when compared to a Capnostream35TM end-tidal CO2 monitor. When compared with investigator observations, the system correctly classified activities and posture (agreement = 98.7 and 92.9%, respectively), step count (MAE = 14.7, < 3% of actual steps during a 6-min walk), and sleep events (MAE: sleep onset = 6.8 min, wake = 11.5 min, sleep duration = 13.7 min) with high accuracy. Participants indicated "good" to "excellent" usability (average System Usability Scale score of 81.3) and preferred the BioStamp nPoint system over both the Actiheart (86%) and Capnostream (97%) devices. CONCLUSIONS The present study validated the BioStamp nPoint system's performance and ease of use compared to FDA-cleared comparator devices in both the clinic and remote (home) environments.
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Patchable micro/nanodevices interacting with skin. Biosens Bioelectron 2018; 122:189-204. [DOI: 10.1016/j.bios.2018.09.035] [Citation(s) in RCA: 40] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2018] [Revised: 09/09/2018] [Accepted: 09/10/2018] [Indexed: 12/20/2022]
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Thomas JA, A Perez-Alday E, Junell A, Newton K, Hamilton C, Li-Pershing Y, German D, Bender A, Tereshchenko LG. Vectorcardiogram in athletes: The Sun Valley Ski Study. Ann Noninvasive Electrocardiol 2018; 24:e12614. [PMID: 30403442 DOI: 10.1111/anec.12614] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/13/2018] [Revised: 09/05/2018] [Accepted: 10/12/2018] [Indexed: 12/16/2022] Open
Abstract
BACKGROUND Global electrical heterogeneity (GEH) is associated with sudden cardiac death (SCD) in adults of 45 years and above. However, GEH has not been previously measured in young athletes. The goal of this study was to establish a reference for vectorcardiograpic (VCG) metrics in male and female athletes. METHODS Skiers (n = 140; mean age 19.2 ± 3.5 years; 66% male, 94% white; 53% professional athletes) were enrolled in a prospective cohort. Resting 12-lead ECGs were interpreted per the International ECG criteria. Associations of age, sex, and athletic performance with GEH were studied. RESULTS In age and training level-adjusted analyses, male sex was associated with a larger T vector [T peak magnitude +186 (95% CI 106-266) µV] and a wider spatial QRS-T angle [+28.2 (17.3-39.2)°] as compared to women. Spatial QRS-T angle in the ECG left ventricular hypertrophy (LVH) voltage group (n = 21; 15%) and normal ECG group did not differ (67.7 ± 25.0 vs. 66.8 ± 28.2; p = 0.914), suggesting that ECG LVH voltage in athletes reflects physiological remodeling. In contrast, skiers with right ventricular hypertrophy (RVH) voltage (n = 26, 18.6%) had wider QRS-T angle (92.7 ± 29.6 vs. 66.8 ± 28.2°; p = 0.001), larger SAI QRST (194.9 ± 30.2 vs. 157.8 ± 42.6 mV × ms; p < 0.0001), but similar peak SVG vector magnitude (1976 ± 548 vs. 1939 ± 395 µV; p = 0.775) as compared to the normal ECG group. Better athletic performance was associated with the narrower QRS-T angle. Each 10% worsening in an athlete's Federation Internationale de' Ski downhill ranking percentile was associated with an increase in spatial QRS-T angle by 2.1 (95% CI 0.3-3.9) degrees (p = 0.013). CONCLUSION Vectorcardiograpic adds nuances to ECG phenomena in athletes.
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Affiliation(s)
- Jason A Thomas
- Knight Cardiovascular Institute, Oregon Health & Science University, Portland, Oregon.,Department of Biomedical Informatics and Medical Education, University of Washington, Seattle, Washington
| | - Erick A Perez-Alday
- Knight Cardiovascular Institute, Oregon Health & Science University, Portland, Oregon
| | - Allison Junell
- School of Medicine, Oregon Health and Science University, Portland, Oregon
| | - Kelley Newton
- School of Medicine, Oregon Health and Science University, Portland, Oregon
| | - Christopher Hamilton
- Knight Cardiovascular Institute, Oregon Health & Science University, Portland, Oregon
| | - Yin Li-Pershing
- Knight Cardiovascular Institute, Oregon Health & Science University, Portland, Oregon
| | - David German
- Knight Cardiovascular Institute, Oregon Health & Science University, Portland, Oregon
| | - Aron Bender
- Knight Cardiovascular Institute, Oregon Health & Science University, Portland, Oregon
| | - Larisa G Tereshchenko
- Knight Cardiovascular Institute, Oregon Health & Science University, Portland, Oregon.,Johns Hopkins University School of Medicine, Baltimore, Maryland
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Perez-Alday EA, Hamilton C, Li-Pershing A, Monroy-Trujillo JM, Estrella M, Sozio SM, Jaar B, Parekh R, Tereshchenko L. The Reproducibility of Global Electrical Heterogeneity ECG Measurements. COMPUTING IN CARDIOLOGY 2018; 45:10.22489/cinc.2018.162. [PMID: 32296724 PMCID: PMC7158900 DOI: 10.22489/cinc.2018.162] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2023]
Abstract
BACKGROUND Global electrical heterogeneity (GEH) is a useful predictor of adverse clinical outcomes. However, reproducibility of GEH measurements on 10-second routine clinical ECG is unknown. METHODS Data of the prospective cohort study of incident hemodialysis patients (n=253; mean age 54.6±13.5y; 56% male; 79% African American) were analysed. Two random 10-second segments of 5-minute ECG recording in sinus rhythm were compared. GEH was measured as spatial QRS-T angle, spatial ventricular gradient (SVG) magnitude and direction (azimuth and elevation), and a scalar value of SVG measured by (1) sum absolute QRST integral (SAI QRST), and (2) QT integral on vector magnitude signal (iVMQT). Bland-Altman analysis was used to calculate agreement. RESULTS For all studied vectorcardiographic metrics, agreement was substantial (Lin's concordance coefficient >0.98), and precision was perfect (>99.99%). 95% limits of agreement were ±14° for spatial QRS-T angle, ±13° for SVG azimuth, ±4° for SVG elevation, ±14 mV*ms for SVG magnitude, and ±17 mV*ms for SAI QRST. SAI QRST and iVMQT were in substantial agreement with each other. CONCLUSION Reproducibility of a 10-second automated GEH ECG measurements was substantial, and precision was perfect.
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Affiliation(s)
| | | | | | | | - Michelle Estrella
- Johns Hopkins University, Baltimore, MD, USA
- University of California San Francisco, San Francisco, CA, USA
| | | | | | - Rulan Parekh
- Johns Hopkins University, Baltimore, MD, USA
- University of Toronto, Toronto, Canada
| | - Larisa Tereshchenko
- Oregon Health & Science University, Portland, OR, USA
- Johns Hopkins University, Baltimore, MD, USA
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Biering-Sørensen T, Kabir M, Waks JW, Thomas J, Post WS, Soliman EZ, Buxton AE, Shah AM, Solomon SD, Tereshchenko LG. Global ECG Measures and Cardiac Structure and Function: The ARIC Study (Atherosclerosis Risk in Communities). Circ Arrhythm Electrophysiol 2018; 11:e005961. [PMID: 29496680 PMCID: PMC5836803 DOI: 10.1161/circep.117.005961] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/07/2017] [Accepted: 01/16/2018] [Indexed: 01/13/2023]
Abstract
BACKGROUND Electric excitation initiates myocardial mechanical contraction and coordinates myocardial pumping. We hypothesized that ECG global electric heterogeneity (GEH) and its longitudinal changes are associated with cardiac structure and function. METHODS AND RESULTS Participants from the ARIC study (Atherosclerosis Risk in Communities) (N=5114; 58% female; 22% blacks) with resting 12-lead ECGs (visits 1-5) and echocardiographic assessment of left ventricular (LV) ejection fraction, LV global longitudinal strain, LV mass index, LV end-diastolic volume index, and LV end-systolic volume index at visit 5 were included. Longitudinal analysis included ARIC participants (N=14 609) with measured GEH at visits 1 to 4. GEH was quantified by spatial ventricular gradient, QRS-T angle, and sum absolute QRS-T integral. Cross-sectional and longitudinal regressions were adjusted for manifest and subclinical cardiovascular disease. Having 4 abnormal GEH parameters was associated with a 6.4% (95% confidence interval, 5.5-7.3) LV ejection fraction decline, a 24.2 g/m2 (95% confidence interval, 21.5-26.9) increase in LV mass index, a 10.3 mL/m2 (95% confidence interval, 8.9-11.7) increase in LV end-diastolic volume index, and a 7.8 mL/m2 (95% confidence interval, 6.9-8.6) increase in LV end-systolic volume index. Altogether, clinical and ECG parameters accounted for approximately one third of LV volume and 20% of systolic function variability. The associations were significantly stronger in cardiovascular disease. Sum absolute QRS-T integral increased by 20 mV*ms for each 3-year period in participants who demonstrated LV dilatation at visit 5. Sudden cardiac death victims demonstrated rapid GEH worsening, whereas those with LV dysfunction demonstrated slow GEH worsening. Healthy aging was associated with a distinct pattern of spatial ventricular gradient azimuth decrement. CONCLUSIONS GEH is a marker of subclinical abnormalities in cardiac structure and function.
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Affiliation(s)
- Tor Biering-Sørensen
- From the Brigham and Women's Hospital (T.B.-S., A.M.S., S.D.S.) and Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center (J.W.W., A.E.B.), Harvard Medical School, Boston, MA; Knight Cardiovascular Institute, Oregon Health & Science University, Portland (M.K., J.T., L.G.T.); Division of Cardiology, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD (W.S.P., L.G.T.); and Epidemiological Cardiology Research Center, Cardiology Section, Department of Medicine, Division of Public Health Sciences, Wake Forest School of Medicine, Winston Salem, NC (E.Z.S.)
| | - Muammar Kabir
- From the Brigham and Women's Hospital (T.B.-S., A.M.S., S.D.S.) and Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center (J.W.W., A.E.B.), Harvard Medical School, Boston, MA; Knight Cardiovascular Institute, Oregon Health & Science University, Portland (M.K., J.T., L.G.T.); Division of Cardiology, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD (W.S.P., L.G.T.); and Epidemiological Cardiology Research Center, Cardiology Section, Department of Medicine, Division of Public Health Sciences, Wake Forest School of Medicine, Winston Salem, NC (E.Z.S.)
| | - Jonathan W Waks
- From the Brigham and Women's Hospital (T.B.-S., A.M.S., S.D.S.) and Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center (J.W.W., A.E.B.), Harvard Medical School, Boston, MA; Knight Cardiovascular Institute, Oregon Health & Science University, Portland (M.K., J.T., L.G.T.); Division of Cardiology, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD (W.S.P., L.G.T.); and Epidemiological Cardiology Research Center, Cardiology Section, Department of Medicine, Division of Public Health Sciences, Wake Forest School of Medicine, Winston Salem, NC (E.Z.S.)
| | - Jason Thomas
- From the Brigham and Women's Hospital (T.B.-S., A.M.S., S.D.S.) and Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center (J.W.W., A.E.B.), Harvard Medical School, Boston, MA; Knight Cardiovascular Institute, Oregon Health & Science University, Portland (M.K., J.T., L.G.T.); Division of Cardiology, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD (W.S.P., L.G.T.); and Epidemiological Cardiology Research Center, Cardiology Section, Department of Medicine, Division of Public Health Sciences, Wake Forest School of Medicine, Winston Salem, NC (E.Z.S.)
| | - Wendy S Post
- From the Brigham and Women's Hospital (T.B.-S., A.M.S., S.D.S.) and Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center (J.W.W., A.E.B.), Harvard Medical School, Boston, MA; Knight Cardiovascular Institute, Oregon Health & Science University, Portland (M.K., J.T., L.G.T.); Division of Cardiology, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD (W.S.P., L.G.T.); and Epidemiological Cardiology Research Center, Cardiology Section, Department of Medicine, Division of Public Health Sciences, Wake Forest School of Medicine, Winston Salem, NC (E.Z.S.)
| | - Elsayed Z Soliman
- From the Brigham and Women's Hospital (T.B.-S., A.M.S., S.D.S.) and Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center (J.W.W., A.E.B.), Harvard Medical School, Boston, MA; Knight Cardiovascular Institute, Oregon Health & Science University, Portland (M.K., J.T., L.G.T.); Division of Cardiology, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD (W.S.P., L.G.T.); and Epidemiological Cardiology Research Center, Cardiology Section, Department of Medicine, Division of Public Health Sciences, Wake Forest School of Medicine, Winston Salem, NC (E.Z.S.)
| | - Alfred E Buxton
- From the Brigham and Women's Hospital (T.B.-S., A.M.S., S.D.S.) and Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center (J.W.W., A.E.B.), Harvard Medical School, Boston, MA; Knight Cardiovascular Institute, Oregon Health & Science University, Portland (M.K., J.T., L.G.T.); Division of Cardiology, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD (W.S.P., L.G.T.); and Epidemiological Cardiology Research Center, Cardiology Section, Department of Medicine, Division of Public Health Sciences, Wake Forest School of Medicine, Winston Salem, NC (E.Z.S.)
| | - Amil M Shah
- From the Brigham and Women's Hospital (T.B.-S., A.M.S., S.D.S.) and Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center (J.W.W., A.E.B.), Harvard Medical School, Boston, MA; Knight Cardiovascular Institute, Oregon Health & Science University, Portland (M.K., J.T., L.G.T.); Division of Cardiology, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD (W.S.P., L.G.T.); and Epidemiological Cardiology Research Center, Cardiology Section, Department of Medicine, Division of Public Health Sciences, Wake Forest School of Medicine, Winston Salem, NC (E.Z.S.)
| | - Scott D Solomon
- From the Brigham and Women's Hospital (T.B.-S., A.M.S., S.D.S.) and Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center (J.W.W., A.E.B.), Harvard Medical School, Boston, MA; Knight Cardiovascular Institute, Oregon Health & Science University, Portland (M.K., J.T., L.G.T.); Division of Cardiology, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD (W.S.P., L.G.T.); and Epidemiological Cardiology Research Center, Cardiology Section, Department of Medicine, Division of Public Health Sciences, Wake Forest School of Medicine, Winston Salem, NC (E.Z.S.)
| | - Larisa G Tereshchenko
- From the Brigham and Women's Hospital (T.B.-S., A.M.S., S.D.S.) and Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center (J.W.W., A.E.B.), Harvard Medical School, Boston, MA; Knight Cardiovascular Institute, Oregon Health & Science University, Portland (M.K., J.T., L.G.T.); Division of Cardiology, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD (W.S.P., L.G.T.); and Epidemiological Cardiology Research Center, Cardiology Section, Department of Medicine, Division of Public Health Sciences, Wake Forest School of Medicine, Winston Salem, NC (E.Z.S.).
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