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Piccirillo G, Moscucci F, Mezzadri M, Caltabiano C, Cisaria G, Vizza G, De Santis V, Giuffrè M, Stefano S, Scinicariello C, Carnovale M, Corrao A, Lospinuso I, Sciomer S, Rossi P. Artificial Intelligence Applied to Electrical and Non-Invasive Hemodynamic Markers in Elderly Decompensated Chronic Heart Failure Patients. Biomedicines 2024; 12:716. [PMID: 38672072 PMCID: PMC11048014 DOI: 10.3390/biomedicines12040716] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2024] [Revised: 03/16/2024] [Accepted: 03/18/2024] [Indexed: 04/28/2024] Open
Abstract
OBJECTIVES The first aim of this study was to assess the predictive power of Tend interval (Te) and non-invasive hemodynamic markers, based on bioimpedance in decompensated chronic heart failure (CHF). The second one was to verify the possible differences in repolarization and hemodynamic data between CHF patients grouped by level of left ventricular ejection fraction (LVEF). Finally, we wanted to check if repolarization and hemodynamic data changed with clinical improvement or worsening in CHF patients. METHODS Two hundred and forty-three decompensated CHF patients were studied by 5 min ECG recordings to determine the mean and standard deviation (TeSD) of Te (first study). In a subgroup of 129 patients (second study), non-invasive hemodynamic and repolarization data were recorded for further evaluation. RESULTS Total in-hospital and cardiovascular mortality rates were respectively 19 and 9%. Te was higher in the deceased than in surviving subjects (Te: 120 ± 28 vs. 100 ± 25 ms) and multivariable logistic regression analysis reported that Te was related to an increase of total (χ2: 35.45, odds ratio: 1.03, 95% confidence limit: 1.02-1.05, p < 0.001) and cardiovascular mortality (χ2: 32.58, odds ratio: 1.04, 95% confidence limit: 1.02-1.06, p < 0.001). Subjects with heart failure with reduced ejection fraction (HFrEF) reported higher levels of repolarization and lower non-invasive systolic hemodynamic data in comparison to those with preserved ejection fraction (HFpEF). In the subgroup, patients with the NT-proBNP reduction after therapy showed a lower rate of Te, heart rate, blood pressures, contractility index, and left ventricular ejection time in comparison with the patients without NT-proBNP reduction. CONCLUSION Electrical signals from ECG and bioimpedance were capable of monitoring the patients with advanced decompensated CHF. These simple, inexpensive, non-invasive, easily repeatable, and transmissible markers could represent a tool to remotely monitor and to intercept the possible worsening of these patients early by machine learning and artificial intelligence tools.
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Affiliation(s)
- Gianfranco Piccirillo
- Department of Internal and Clinical Medicine, Anesthesiology and Cardiovascular Sciences, Policlinico Umberto I, “Sapienza” University of Rome, 00185 Rome, Italy; (G.P.); (M.M.); (C.C.); (G.C.); (G.V.); (V.D.S.); (M.G.); (S.S.); (C.S.); (M.C.); (A.C.); (S.S.)
| | - Federica Moscucci
- Department of Internal Medicine and Medical Specialties, Policlinico Umberto I, Viale del Policlinico, 155, 00161 Rome, Italy;
| | - Martina Mezzadri
- Department of Internal and Clinical Medicine, Anesthesiology and Cardiovascular Sciences, Policlinico Umberto I, “Sapienza” University of Rome, 00185 Rome, Italy; (G.P.); (M.M.); (C.C.); (G.C.); (G.V.); (V.D.S.); (M.G.); (S.S.); (C.S.); (M.C.); (A.C.); (S.S.)
| | - Cristina Caltabiano
- Department of Internal and Clinical Medicine, Anesthesiology and Cardiovascular Sciences, Policlinico Umberto I, “Sapienza” University of Rome, 00185 Rome, Italy; (G.P.); (M.M.); (C.C.); (G.C.); (G.V.); (V.D.S.); (M.G.); (S.S.); (C.S.); (M.C.); (A.C.); (S.S.)
| | - Giovanni Cisaria
- Department of Internal and Clinical Medicine, Anesthesiology and Cardiovascular Sciences, Policlinico Umberto I, “Sapienza” University of Rome, 00185 Rome, Italy; (G.P.); (M.M.); (C.C.); (G.C.); (G.V.); (V.D.S.); (M.G.); (S.S.); (C.S.); (M.C.); (A.C.); (S.S.)
| | - Guendalina Vizza
- Department of Internal and Clinical Medicine, Anesthesiology and Cardiovascular Sciences, Policlinico Umberto I, “Sapienza” University of Rome, 00185 Rome, Italy; (G.P.); (M.M.); (C.C.); (G.C.); (G.V.); (V.D.S.); (M.G.); (S.S.); (C.S.); (M.C.); (A.C.); (S.S.)
| | - Valerio De Santis
- Department of Internal and Clinical Medicine, Anesthesiology and Cardiovascular Sciences, Policlinico Umberto I, “Sapienza” University of Rome, 00185 Rome, Italy; (G.P.); (M.M.); (C.C.); (G.C.); (G.V.); (V.D.S.); (M.G.); (S.S.); (C.S.); (M.C.); (A.C.); (S.S.)
| | - Marco Giuffrè
- Department of Internal and Clinical Medicine, Anesthesiology and Cardiovascular Sciences, Policlinico Umberto I, “Sapienza” University of Rome, 00185 Rome, Italy; (G.P.); (M.M.); (C.C.); (G.C.); (G.V.); (V.D.S.); (M.G.); (S.S.); (C.S.); (M.C.); (A.C.); (S.S.)
| | - Sara Stefano
- Department of Internal and Clinical Medicine, Anesthesiology and Cardiovascular Sciences, Policlinico Umberto I, “Sapienza” University of Rome, 00185 Rome, Italy; (G.P.); (M.M.); (C.C.); (G.C.); (G.V.); (V.D.S.); (M.G.); (S.S.); (C.S.); (M.C.); (A.C.); (S.S.)
| | - Claudia Scinicariello
- Department of Internal and Clinical Medicine, Anesthesiology and Cardiovascular Sciences, Policlinico Umberto I, “Sapienza” University of Rome, 00185 Rome, Italy; (G.P.); (M.M.); (C.C.); (G.C.); (G.V.); (V.D.S.); (M.G.); (S.S.); (C.S.); (M.C.); (A.C.); (S.S.)
| | - Myriam Carnovale
- Department of Internal and Clinical Medicine, Anesthesiology and Cardiovascular Sciences, Policlinico Umberto I, “Sapienza” University of Rome, 00185 Rome, Italy; (G.P.); (M.M.); (C.C.); (G.C.); (G.V.); (V.D.S.); (M.G.); (S.S.); (C.S.); (M.C.); (A.C.); (S.S.)
| | - Andrea Corrao
- Department of Internal and Clinical Medicine, Anesthesiology and Cardiovascular Sciences, Policlinico Umberto I, “Sapienza” University of Rome, 00185 Rome, Italy; (G.P.); (M.M.); (C.C.); (G.C.); (G.V.); (V.D.S.); (M.G.); (S.S.); (C.S.); (M.C.); (A.C.); (S.S.)
| | - Ilaria Lospinuso
- Department of Internal Medicine and Medical Specialties, Policlinico Umberto I, Viale del Policlinico, 155, 00161 Rome, Italy;
| | - Susanna Sciomer
- Department of Internal and Clinical Medicine, Anesthesiology and Cardiovascular Sciences, Policlinico Umberto I, “Sapienza” University of Rome, 00185 Rome, Italy; (G.P.); (M.M.); (C.C.); (G.C.); (G.V.); (V.D.S.); (M.G.); (S.S.); (C.S.); (M.C.); (A.C.); (S.S.)
| | - Pietro Rossi
- Arrhythmology Unit, Fatebenefratelli Hospital, Isola Tiberina-Gemelli Isola, 00186 Rome, Italy;
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Duca ȘT, Badescu MC, Costache AD, Chetran A, Miftode RȘ, Tudorancea I, Mitu O, Afrăsânie I, Ciorap RG, Șerban IL, Pavăl DR, Dmour B, Cepoi MR, Costache-Enache II. Harmony in Chaos: Deciphering the Influence of Ischemic Cardiomyopathy and Non-Cardiac Comorbidities on Holter ECG Parameters in Chronic Heart Failure Patients: A Pilot Study. MEDICINA (KAUNAS, LITHUANIA) 2024; 60:342. [PMID: 38399629 PMCID: PMC10889994 DOI: 10.3390/medicina60020342] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/12/2024] [Revised: 02/06/2024] [Accepted: 02/17/2024] [Indexed: 02/25/2024]
Abstract
Background and Objective: In the landscape of heart failure, non-cardiac comorbidities represent a formidable challenge, imparting adverse prognostic implications. Holter ECG monitoring assumes a supplementary role in delineating myocardial susceptibility and autonomic nervous system dynamics. This study aims to explore the potential correlation between Holter ECG parameters and comorbidities in individuals with ischemic cardiomyopathy experiencing heart failure (HF), with a particular focus on the primary utility of these parameters as prognostic indicators. Materials and Methods: In this prospective inquiry, a cohort of 60 individuals diagnosed with heart failure underwent stratification into subgroups based on the presence of comorbidities, including diabetes, chronic kidney disease, obesity, or hyperuricemia. Upon admission, a thorough evaluation of all participants encompassed echocardiography, laboratory panel analysis, and 24 h Holter monitoring. Results: Significant associations were uncovered between diabetes and unconventional physiological indicators, specifically the Triangular index (p = 0.035) and deceleration capacity (p = 0.002). Pertaining to creatinine clearance, notable correlations surfaced with RMSSD (p = 0.026), PNN50 (p = 0.013), and high-frequency power (p = 0.026). An examination of uric acid levels and distinctive Holter ECG patterns unveiled statistical significance, particularly regarding the deceleration capacity (p = 0.045). Nevertheless, in the evaluation of the Body Mass Index, no statistically significant findings emerged concerning Holter ECG parameters. Conclusions: The identified statistical correlations between non-cardiac comorbidities and patterns elucidated in Holter ECG recordings underscore the heightened diagnostic utility of this investigative modality in the comprehensive evaluation of individuals grappling with HF. Furthermore, we underscore the critical importance of the thorough analysis of Holter ECG recordings, particularly with regard to subtle and emerging parameters that may be overlooked or insufficiently acknowledged.
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Affiliation(s)
- Ștefania-Teodora Duca
- Department of Internal Medicine I, Faculty of Medicine, University of Medicine and Pharmacy “Grigore T. Popa”, 700115 Iasi, Romania; (Ș.-T.D.); (A.C.); (R.Ș.M.); (O.M.); (I.A.); (B.D.); (M.-R.C.); (I.-I.C.-E.)
- Department of Cardiology, “St. Spiridon” Emergency County Hospital, 700111 Iasi, Romania;
| | - Minerva Codruta Badescu
- Department of Internal Medicine I, Faculty of Medicine, University of Medicine and Pharmacy “Grigore T. Popa”, 700115 Iasi, Romania; (Ș.-T.D.); (A.C.); (R.Ș.M.); (O.M.); (I.A.); (B.D.); (M.-R.C.); (I.-I.C.-E.)
- Department of III Internal Medicine Clinic, “St. Spiridon” Emergency County Hospital, 700111 Iasi, Romania
| | - Alexandru-Dan Costache
- Department of Internal Medicine I, Faculty of Medicine, University of Medicine and Pharmacy “Grigore T. Popa”, 700115 Iasi, Romania; (Ș.-T.D.); (A.C.); (R.Ș.M.); (O.M.); (I.A.); (B.D.); (M.-R.C.); (I.-I.C.-E.)
- Department of Cardiovascular Rehabilitation, Clinical Rehabilitation Hospital, 700661 Iasi, Romania
| | - Adriana Chetran
- Department of Internal Medicine I, Faculty of Medicine, University of Medicine and Pharmacy “Grigore T. Popa”, 700115 Iasi, Romania; (Ș.-T.D.); (A.C.); (R.Ș.M.); (O.M.); (I.A.); (B.D.); (M.-R.C.); (I.-I.C.-E.)
- Department of Cardiology, “St. Spiridon” Emergency County Hospital, 700111 Iasi, Romania;
| | - Radu Ștefan Miftode
- Department of Internal Medicine I, Faculty of Medicine, University of Medicine and Pharmacy “Grigore T. Popa”, 700115 Iasi, Romania; (Ș.-T.D.); (A.C.); (R.Ș.M.); (O.M.); (I.A.); (B.D.); (M.-R.C.); (I.-I.C.-E.)
- Department of Cardiology, “St. Spiridon” Emergency County Hospital, 700111 Iasi, Romania;
| | - Ionuț Tudorancea
- Department of Cardiology, “St. Spiridon” Emergency County Hospital, 700111 Iasi, Romania;
- Department of Morpho-Functional Science II-Physiology, University of Medicine and Pharmacy “Grigore T. Popa”, 700115 Iasi, Romania;
| | - Ovidiu Mitu
- Department of Internal Medicine I, Faculty of Medicine, University of Medicine and Pharmacy “Grigore T. Popa”, 700115 Iasi, Romania; (Ș.-T.D.); (A.C.); (R.Ș.M.); (O.M.); (I.A.); (B.D.); (M.-R.C.); (I.-I.C.-E.)
- Department of Cardiology, “St. Spiridon” Emergency County Hospital, 700111 Iasi, Romania;
| | - Irina Afrăsânie
- Department of Internal Medicine I, Faculty of Medicine, University of Medicine and Pharmacy “Grigore T. Popa”, 700115 Iasi, Romania; (Ș.-T.D.); (A.C.); (R.Ș.M.); (O.M.); (I.A.); (B.D.); (M.-R.C.); (I.-I.C.-E.)
- Department of Cardiology, “St. Spiridon” Emergency County Hospital, 700111 Iasi, Romania;
| | - Radu-George Ciorap
- Department of Biomedical Science, Faculty of Medical Bioengineering, University of Medicine and Pharmacy “Grigore T. Popa”, 700145 Iasi, Romania;
| | - Ionela-Lăcrămioara Șerban
- Department of Morpho-Functional Science II-Physiology, University of Medicine and Pharmacy “Grigore T. Popa”, 700115 Iasi, Romania;
| | - D. Robert Pavăl
- Faculty of Health Sciences and Sport, University of Stirling, Stirling FK9 4LA, UK;
| | - Bianca Dmour
- Department of Internal Medicine I, Faculty of Medicine, University of Medicine and Pharmacy “Grigore T. Popa”, 700115 Iasi, Romania; (Ș.-T.D.); (A.C.); (R.Ș.M.); (O.M.); (I.A.); (B.D.); (M.-R.C.); (I.-I.C.-E.)
| | - Maria-Ruxandra Cepoi
- Department of Internal Medicine I, Faculty of Medicine, University of Medicine and Pharmacy “Grigore T. Popa”, 700115 Iasi, Romania; (Ș.-T.D.); (A.C.); (R.Ș.M.); (O.M.); (I.A.); (B.D.); (M.-R.C.); (I.-I.C.-E.)
| | - Irina-Iuliana Costache-Enache
- Department of Internal Medicine I, Faculty of Medicine, University of Medicine and Pharmacy “Grigore T. Popa”, 700115 Iasi, Romania; (Ș.-T.D.); (A.C.); (R.Ș.M.); (O.M.); (I.A.); (B.D.); (M.-R.C.); (I.-I.C.-E.)
- Department of Cardiology, “St. Spiridon” Emergency County Hospital, 700111 Iasi, Romania;
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Sams LE, Wörndl M, Bachinger L, Villegas Sierra LE, Mourouzis K, Naumann D, Freyer L, Rizas KD. Periodic repolarization dynamics: Different methods for quantifying low-frequency oscillations of repolarization. J Electrocardiol 2024; 82:11-18. [PMID: 37995553 DOI: 10.1016/j.jelectrocard.2023.11.005] [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: 06/15/2023] [Revised: 10/19/2023] [Accepted: 11/14/2023] [Indexed: 11/25/2023]
Abstract
BACKGROUND Periodic repolarization dynamics (PRD) is an electrocardiographic biomarker that quantifies low-frequency (LF) instabilities of repolarization. PRD is a strong predictor of mortality in patients with ischaemic and non-ischaemic cardiomyopathy. Until recently, two methods for calculating PRD have been proposed. The wavelet analysis has been widely tested and quantifies PRD in deg2 units by application of continuous wavelet transformation (PRDwavelet). The phase rectified signal averaging method (PRDPRSA) is an algebraic method, which quantifies PRD in deg. units. The correlation, as well as a conversion formula between the two methods remain unknown. METHOD The first step for quantifying PRD is to calculate the beat-to-beat change in the direction of repolarization, called dT°. PRD is subsequently quantified by means of either wavelet or PRSA-analysis. We simulated 1.000.000 dT°-signals. For each simulated signal we calculated PRD using the wavelet and PRSA-method. We calculated the ratio between PRDwavelet and PRDPRSA for different values of dT° and RR-intervals and applied this ratio in a real-ECG validation cohort of 455 patients after myocardial infarction (MI). We finally calculated the correlation coefficient between real and calculated PRDwavelet. PRDwavelet was dichotomized at the established cut-off value of ≥5.75 deg2. RESULTS The ratio between PRDwavelet and PRDPRSA increased with increasing heart-rate and mean dT°-values (p < 0.001 for both). The correlation coefficient between PRDwavelet and PRDPRSA in the validation cohort was 0.908 (95% CI 0.891-0.923), which significantly (p < 0.001) improved to 0.945 (95% CI 0.935-0.955) after applying the formula considering the ratio between PRDwavelet and PRDPRSA obtained from the simulation cohort. The calculated PRDwavelet correctly classified 98% of the patients as low-risk and 87% of the patients as high-risk and correctly identified 97% of high-risk patients, who died within the follow-up period. CONCLUSION This is the first analytical investigation of the different methods used to calculate PRD using simulated and clinical data. In this article we propose a novel algorithm for converting PRDPRSA to the widely validated PRDwavelet, which could unify the calculation methods and cut-offs for PRD.
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Affiliation(s)
- Lauren E Sams
- Medizinische Klinik und Poliklinik I, University Hospital Munich, Ludwig-Maximilians University, Munich, Germany; German Center for Cardiovascular Research (DZHK), Partner Site: Munich Heart Alliance, Munich, Germany
| | - Maximilian Wörndl
- Medizinische Klinik und Poliklinik I, University Hospital Munich, Ludwig-Maximilians University, Munich, Germany
| | - Leonie Bachinger
- Medizinische Klinik und Poliklinik I, University Hospital Munich, Ludwig-Maximilians University, Munich, Germany
| | - Laura E Villegas Sierra
- Medizinische Klinik und Poliklinik I, University Hospital Munich, Ludwig-Maximilians University, Munich, Germany
| | - Konstantinos Mourouzis
- Medizinische Klinik und Poliklinik I, University Hospital Munich, Ludwig-Maximilians University, Munich, Germany
| | - Dominik Naumann
- Medizinische Klinik und Poliklinik I, University Hospital Munich, Ludwig-Maximilians University, Munich, Germany
| | - Luisa Freyer
- Medizinische Klinik und Poliklinik I, University Hospital Munich, Ludwig-Maximilians University, Munich, Germany
| | - Konstantinos D Rizas
- Medizinische Klinik und Poliklinik I, University Hospital Munich, Ludwig-Maximilians University, Munich, Germany; German Center for Cardiovascular Research (DZHK), Partner Site: Munich Heart Alliance, Munich, Germany.
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4
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Kolk MZH, Ruipérez-Campillo S, Deb B, Bekkers EJ, Allaart CP, Rogers AJ, Van Der Lingen ALCJ, Alvarez Florez L, Isgum I, De Vos BD, Clopton P, Wilde AAM, Knops RE, Narayan SM, Tjong FVY. Optimizing patient selection for primary prevention implantable cardioverter-defibrillator implantation: utilizing multimodal machine learning to assess risk of implantable cardioverter-defibrillator non-benefit. Europace 2023; 25:euad271. [PMID: 37712675 PMCID: PMC10516624 DOI: 10.1093/europace/euad271] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2023] [Accepted: 08/07/2023] [Indexed: 09/16/2023] Open
Abstract
AIMS Left ventricular ejection fraction (LVEF) is suboptimal as a sole marker for predicting sudden cardiac death (SCD). Machine learning (ML) provides new opportunities for personalized predictions using complex, multimodal data. This study aimed to determine if risk stratification for implantable cardioverter-defibrillator (ICD) implantation can be improved by ML models that combine clinical variables with 12-lead electrocardiograms (ECG) time-series features. METHODS AND RESULTS A multicentre study of 1010 patients (64.9 ± 10.8 years, 26.8% female) with ischaemic, dilated, or non-ischaemic cardiomyopathy, and LVEF ≤ 35% implanted with an ICD between 2007 and 2021 for primary prevention of SCD in two academic hospitals was performed. For each patient, a raw 12-lead, 10-s ECG was obtained within 90 days before ICD implantation, and clinical details were collected. Supervised ML models were trained and validated on a development cohort (n = 550) from Hospital A to predict ICD non-arrhythmic mortality at three-year follow-up (i.e. mortality without prior appropriate ICD-therapy). Model performance was evaluated on an external patient cohort from Hospital B (n = 460). At three-year follow-up, 16.0% of patients had died, with 72.8% meeting criteria for non-arrhythmic mortality. Extreme gradient boosting models identified patients with non-arrhythmic mortality with an area under the receiver operating characteristic curve (AUROC) of 0.90 [95% confidence intervals (CI) 0.80-1.00] during internal validation. In the external cohort, the AUROC was 0.79 (95% CI 0.75-0.84). CONCLUSIONS ML models combining ECG time-series features and clinical variables were able to predict non-arrhythmic mortality within three years after device implantation in a primary prevention population, with robust performance in an independent cohort.
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Affiliation(s)
- Maarten Z H Kolk
- Department of Cardiology, Heart Center, Amsterdam UMC location University of Amsterdam, Meibergdreef 9, 1105 AZ Amsterdam, The Netherlands
- Amsterdam Cardiovascular Sciences, Heart Failure and Arrhythmias, Meibergdreef 9, 1105 AZ Amsterdam, The Netherlands
| | - Samuel Ruipérez-Campillo
- Department of Medicine and Cardiovascular Institute, Stanford University, 780 Welch Road, MC 5773, Stanford, CA 94305, USA
- Department of Information Technology and Electrical Engineering, Swiss Federal Institute of Technology Zurich (ETHz), Zurich, Switzerland
| | - Brototo Deb
- Department of Medicine and Cardiovascular Institute, Stanford University, 780 Welch Road, MC 5773, Stanford, CA 94305, USA
| | - Erik J Bekkers
- Faculty of Science, University of Amsterdam, Science Park 904, 1098 XH Amsterdam, the Netherlands
| | - Cornelis P Allaart
- Department of Cardiology, Amsterdam UMC location Vrije Universiteit Amsterdam, De Boelelaan 1117, 1081 HV Amsterdam, The Netherlands
| | - Albert J Rogers
- Department of Medicine and Cardiovascular Institute, Stanford University, 780 Welch Road, MC 5773, Stanford, CA 94305, USA
| | - Anne-Lotte C J Van Der Lingen
- Department of Cardiology, Amsterdam UMC location Vrije Universiteit Amsterdam, De Boelelaan 1117, 1081 HV Amsterdam, The Netherlands
| | - Laura Alvarez Florez
- Department of Cardiology, Heart Center, Amsterdam UMC location University of Amsterdam, Meibergdreef 9, 1105 AZ Amsterdam, The Netherlands
- Amsterdam Cardiovascular Sciences, Heart Failure and Arrhythmias, Meibergdreef 9, 1105 AZ Amsterdam, The Netherlands
- Department of Biomedical Engineering and Physics, Amsterdam UMC location University of Amsterdam, Meibergdreef 9, 1105 AZ Amsterdam, The Netherlands
| | - Ivana Isgum
- Faculty of Science, University of Amsterdam, Science Park 904, 1098 XH Amsterdam, the Netherlands
- Department of Biomedical Engineering and Physics, Amsterdam UMC location University of Amsterdam, Meibergdreef 9, 1105 AZ Amsterdam, The Netherlands
- Department of Radiology and Nuclear Medicine, Amsterdam UMC location University of Amsterdam, Meibergdreef 9, 1105 AZ Amsterdam, The Netherlands
| | - Bob D De Vos
- Department of Biomedical Engineering and Physics, Amsterdam UMC location University of Amsterdam, Meibergdreef 9, 1105 AZ Amsterdam, The Netherlands
| | - Paul Clopton
- Department of Medicine and Cardiovascular Institute, Stanford University, 780 Welch Road, MC 5773, Stanford, CA 94305, USA
| | - Arthur A M Wilde
- Department of Cardiology, Heart Center, Amsterdam UMC location University of Amsterdam, Meibergdreef 9, 1105 AZ Amsterdam, The Netherlands
- Amsterdam Cardiovascular Sciences, Heart Failure and Arrhythmias, Meibergdreef 9, 1105 AZ Amsterdam, The Netherlands
| | - Reinoud E Knops
- Department of Cardiology, Heart Center, Amsterdam UMC location University of Amsterdam, Meibergdreef 9, 1105 AZ Amsterdam, The Netherlands
- Amsterdam Cardiovascular Sciences, Heart Failure and Arrhythmias, Meibergdreef 9, 1105 AZ Amsterdam, The Netherlands
| | - Sanjiv M Narayan
- Department of Medicine and Cardiovascular Institute, Stanford University, 780 Welch Road, MC 5773, Stanford, CA 94305, USA
| | - Fleur V Y Tjong
- Department of Cardiology, Heart Center, Amsterdam UMC location University of Amsterdam, Meibergdreef 9, 1105 AZ Amsterdam, The Netherlands
- Amsterdam Cardiovascular Sciences, Heart Failure and Arrhythmias, Meibergdreef 9, 1105 AZ Amsterdam, The Netherlands
- Department of Medicine and Cardiovascular Institute, Stanford University, 780 Welch Road, MC 5773, Stanford, CA 94305, USA
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5
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Duca ȘT, Roca M, Costache AD, Chetran A, Afrăsânie I, Miftode RȘ, Tudorancea I, Matei I, Ciorap RG, Mitu O, Bădescu MC, Iliescu-Halitchi D, Halițchi-Iliescu CO, Mitu F, Lionte C, Costache II. T-Wave Analysis on the 24 h Holter ECG Monitoring as a Predictive Assessment of Major Adverse Cardiovascular Events in Patients with Myocardial Infarction: A Literature Review and Future Perspectives. Life (Basel) 2023; 13:life13051155. [PMID: 37240799 DOI: 10.3390/life13051155] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2023] [Revised: 05/01/2023] [Accepted: 05/08/2023] [Indexed: 05/28/2023] Open
Abstract
Myocardial ischemia is a pathophysiological state characterized by inadequate perfusion of the myocardium, resulting in an imbalance between myocardial oxygen demand and supply. It is most commonly caused by coronary artery disease, in which atherosclerotic plaques lead to luminal narrowing and reduced blood flow to the heart. Myocardial ischemia can manifest as angina pectoris or silent myocardial ischemia and can progress to myocardial infarction or heart failure if left untreated. Diagnosis of myocardial ischemia typically involves a combination of clinical evaluation, electrocardiography and imaging studies. Electrocardiographic parameters, as assessed by 24 h Holter ECG monitoring, can predict the occurrence of major adverse cardiovascular events in patients with myocardial ischemia, independent of other risk factors. The T-waves in patients with myocardial ischemia have prognostic value for predicting major adverse cardiovascular events, and their electrophysiological heterogeneity can be visualized using various techniques. Combining the electrocardiographic findings with the assessment of myocardial substrate may offer a better picture of the factors that can contribute to cardiovascular death.
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Affiliation(s)
- Ștefania-Teodora Duca
- Department of Internal Medicine I, Faculty of Medicine, University of Medicine and Pharmacy "Grigore T. Popa", 700115 Iasi, Romania
- Department of Cardiology, "St. Spiridon" Emergency County Hospital, 700111 Iasi, Romania
| | - Mihai Roca
- Department of Internal Medicine I, Faculty of Medicine, University of Medicine and Pharmacy "Grigore T. Popa", 700115 Iasi, Romania
- Department of Cardiovascular Rehabilitation, Clinical Rehabilitation Hospital, 700661 Iasi, Romania
| | - Alexandru-Dan Costache
- Department of Internal Medicine I, Faculty of Medicine, University of Medicine and Pharmacy "Grigore T. Popa", 700115 Iasi, Romania
- Department of Cardiovascular Rehabilitation, Clinical Rehabilitation Hospital, 700661 Iasi, Romania
| | - Adriana Chetran
- Department of Internal Medicine I, Faculty of Medicine, University of Medicine and Pharmacy "Grigore T. Popa", 700115 Iasi, Romania
- Department of Cardiology, "St. Spiridon" Emergency County Hospital, 700111 Iasi, Romania
| | - Irina Afrăsânie
- Department of Cardiology, "St. Spiridon" Emergency County Hospital, 700111 Iasi, Romania
| | - Radu-Ștefan Miftode
- Department of Internal Medicine I, Faculty of Medicine, University of Medicine and Pharmacy "Grigore T. Popa", 700115 Iasi, Romania
- Department of Cardiology, "St. Spiridon" Emergency County Hospital, 700111 Iasi, Romania
| | - Ionuț Tudorancea
- Department of Cardiology, "St. Spiridon" Emergency County Hospital, 700111 Iasi, Romania
- Department of Morpho-Functional Science II-Physiology, University of Medicine and Pharmacy "Grigore T. Popa", 700115 Iasi, Romania
| | - Iulian Matei
- Department of Cardiology, "St. Spiridon" Emergency County Hospital, 700111 Iasi, Romania
| | - Radu-George Ciorap
- Department of Biomedical Science, Faculty of Medical Bioengineering, University of Medicine and Pharmacy "Grigore T. Popa", 700145 Iasi, Romania
| | - Ovidiu Mitu
- Department of Internal Medicine I, Faculty of Medicine, University of Medicine and Pharmacy "Grigore T. Popa", 700115 Iasi, Romania
- Department of Cardiology, "St. Spiridon" Emergency County Hospital, 700111 Iasi, Romania
| | - Minerva Codruța Bădescu
- Department of Internal Medicine I, Faculty of Medicine, University of Medicine and Pharmacy "Grigore T. Popa", 700115 Iasi, Romania
- Department of III Internal Medicine Clinic, "St. Spiridon" Emergency County Hospital, 700111 Iasi, Romania
| | - Dan Iliescu-Halitchi
- Department of Internal Medicine I, Faculty of Medicine, University of Medicine and Pharmacy "Grigore T. Popa", 700115 Iasi, Romania
- Department of Cardiology, Arcadia Hospital, 700620 Iasi, Romania
| | - Codruța-Olimpiada Halițchi-Iliescu
- Department of Mother and Child Medicine-Pediatrics, University of Medicine and Pharmacy "Grigore T. Popa", 700115 Iasi, Romania
- Department of Pedriatics, Arcadia Hospital, 700620 Iasi, Romania
| | - Florin Mitu
- Department of Internal Medicine I, Faculty of Medicine, University of Medicine and Pharmacy "Grigore T. Popa", 700115 Iasi, Romania
- Department of Cardiovascular Rehabilitation, Clinical Rehabilitation Hospital, 700661 Iasi, Romania
| | - Cătălina Lionte
- Department of Internal Medicine III, Faculty of Medicine, University of Medicine and Pharmacy "Grigore T. Popa", 700145 Iasi, Romania
- Department of Cardiology, Helicomed Hospital, 700115 Iasi, Romania
| | - Irina-Iuliana Costache
- Department of Internal Medicine I, Faculty of Medicine, University of Medicine and Pharmacy "Grigore T. Popa", 700115 Iasi, Romania
- Department of Cardiology, "St. Spiridon" Emergency County Hospital, 700111 Iasi, Romania
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Electrocardiography Assessment of Sympatico-Vagal Balance during Resting and Pain Using the Texas Instruments ADS1299. Bioengineering (Basel) 2023; 10:bioengineering10020205. [PMID: 36829699 PMCID: PMC9952434 DOI: 10.3390/bioengineering10020205] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2022] [Revised: 01/27/2023] [Accepted: 01/31/2023] [Indexed: 02/08/2023] Open
Abstract
Sympatico-vagal balance is essential for regulating cardiac electrophysiology and plays an important role in arrhythmogenic conditions. Various noninvasive methods, including electrocardiography (ECG), have been used for clinical assessment of the sympatico-vagal balance. This study aimed to use a custom-designed wearable device to record ECG and ECG-based cardiac function biomarkers to assess sympatico-vagal balance during tonic pain in healthy controls. Nineteen healthy volunteers were included for the ECG measurements using the custom-designed amplifier based on the Texas Instruments ADS1299. The ECG-based biomarkers of the sympatico-vagal balance, (including heart rate variability, deceleration capacity of the heart rate, and periodic repolarization dynamic), were calculated and compared between resting and pain conditions (tonic pain). The custom-designed device provided technically satisfactory ECG recordings. During exposure to tonic pain, the periodic repolarization dynamics increased significantly (p = 0.02), indicating enhancement of sympathetic nervous activity. This study showed that custom-designed wearable devices can potentially be useful in healthcare as a new telemetry technology. The ECG-based novel biomarkers, including periodic repolarization dynamic and deceleration capacity of heart rate, can be used to identify the cold pressor-induced activation of sympathetic and parasympathetic systems, making it useful for future studies on pain-evoked biomarkers.
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Yurasova ES, Blinova EV, Sakhnova TA. On the history of vectorcardiography: past, present, future. TERAPEVT ARKH 2022; 94:1122-1125. [DOI: 10.26442/00403660.2022.09.201841] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2022] [Indexed: 11/05/2022]
Abstract
The vector concept in the analysis of the electrical signals of the heart began to be used at the dawn of the development of electrocardiology. For several decades, vectorcardiography has developed in parallel with electrocardiography; reached its peak in the 60s, and after a period of cooling experienced a resurgence since the early 90s, when it became possible to mathematically synthesize vectorcardiograms (VCG) from digital electrocardiograms in 12 leads. VCG reflects the same phenomena as electrocardiography, but allows you to calculate and visualize a number of three-dimensional characteristics of the electrical signals of the heart. The article describes the main milestones in the development of the VCG, the history of international cooperation in this area, the contribution of domestic scientists to this field of science. Modern promising areas of research related to the vector concept of the analysis of the electrical signals of the heart are briefly reflected.
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