Abhisheik Prashar, Sanjana Shah, Richard Zhang, K. Mitchell, M. Sader
Background: Percutaneous closure of patent foramen ovale (PFO) and atrial septal defects (ASD) is being more commonly performed due to changes in international guidelines supporting its use. This study was performed to determine the clinical outcomes, safety and cost implications of same-day discharge (SDD) following such procedures and place this in an Australian context. Methods: This was a retrospective, observational study of patients undergoing elective percutaneous PFO or ASD closure at St. George Hospital, Australia between January 2011 and January 2020. Primary outcomes included 30-day major adverse cardiovascular endpoints (MACE) and readmission to hospital within 30 days. Results: Twenty-four patients were included in the primary analysis. Ten (41.7%) patients underwent elective ASD closure while 14 (58.3%) underwent PFO closure. Among the 24 patients who underwent elective percutaneous closure of structural heart disease, 23 patients (95.8%) were managed with SDD. There were no MACE outcomes at 30 days. No patients were re-admitted to hospital at 30 days following these procedures. When compared to overnight admission to hospital post-elective percutaneous structural heart condition closure, SDD yielded a cost saving of AUD 5999 per case. Conclusion: SDD following elective percutaneous closure of ASD and PFO was demonstrated to be a safe and effective strategy for managing patients. With more widespread use, it can lead to significant cost savings for hospitals without compromising patient care.
{"title":"Safety and Cost Implications of Same-Day Discharge Following Elective Percutaneous Closure of Patent Foramen Ovale and Atrial Septal Defects in Australia","authors":"Abhisheik Prashar, Sanjana Shah, Richard Zhang, K. Mitchell, M. Sader","doi":"10.3390/hearts2040041","DOIUrl":"https://doi.org/10.3390/hearts2040041","url":null,"abstract":"Background: Percutaneous closure of patent foramen ovale (PFO) and atrial septal defects (ASD) is being more commonly performed due to changes in international guidelines supporting its use. This study was performed to determine the clinical outcomes, safety and cost implications of same-day discharge (SDD) following such procedures and place this in an Australian context. Methods: This was a retrospective, observational study of patients undergoing elective percutaneous PFO or ASD closure at St. George Hospital, Australia between January 2011 and January 2020. Primary outcomes included 30-day major adverse cardiovascular endpoints (MACE) and readmission to hospital within 30 days. Results: Twenty-four patients were included in the primary analysis. Ten (41.7%) patients underwent elective ASD closure while 14 (58.3%) underwent PFO closure. Among the 24 patients who underwent elective percutaneous closure of structural heart disease, 23 patients (95.8%) were managed with SDD. There were no MACE outcomes at 30 days. No patients were re-admitted to hospital at 30 days following these procedures. When compared to overnight admission to hospital post-elective percutaneous structural heart condition closure, SDD yielded a cost saving of AUD 5999 per case. Conclusion: SDD following elective percutaneous closure of ASD and PFO was demonstrated to be a safe and effective strategy for managing patients. With more widespread use, it can lead to significant cost savings for hospitals without compromising patient care.","PeriodicalId":93563,"journal":{"name":"Hearts (Basel, Switzerland)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44442872","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
J. Bergquist, Lindsay C. Rupp, B. Zenger, James N. Brundage, Anna Busatto, R. Macleod
Body surface potential mapping (BSPM) is a noninvasive modality to assess cardiac bioelectric activity with a rich history of practical applications for both research and clinical investigation. BSPM provides comprehensive acquisition of bioelectric signals across the entire thorax, allowing for more complex and extensive analysis than the standard electrocardiogram (ECG). Despite its advantages, BSPM is not a common clinical tool. BSPM does, however, serve as a valuable research tool and as an input for other modes of analysis such as electrocardiographic imaging and, more recently, machine learning and artificial intelligence. In this report, we examine contemporary uses of BSPM, and provide an assessment of its future prospects in both clinical and research environments. We assess the state of the art of BSPM implementations and explore modern applications of advanced modeling and statistical analysis of BSPM data. We predict that BSPM will continue to be a valuable research tool, and will find clinical utility at the intersection of computational modeling approaches and artificial intelligence.
{"title":"Body Surface Potential Mapping: Contemporary Applications and Future Perspectives.","authors":"J. Bergquist, Lindsay C. Rupp, B. Zenger, James N. Brundage, Anna Busatto, R. Macleod","doi":"10.3390/hearts2040040","DOIUrl":"https://doi.org/10.3390/hearts2040040","url":null,"abstract":"Body surface potential mapping (BSPM) is a noninvasive modality to assess cardiac bioelectric activity with a rich history of practical applications for both research and clinical investigation. BSPM provides comprehensive acquisition of bioelectric signals across the entire thorax, allowing for more complex and extensive analysis than the standard electrocardiogram (ECG). Despite its advantages, BSPM is not a common clinical tool. BSPM does, however, serve as a valuable research tool and as an input for other modes of analysis such as electrocardiographic imaging and, more recently, machine learning and artificial intelligence. In this report, we examine contemporary uses of BSPM, and provide an assessment of its future prospects in both clinical and research environments. We assess the state of the art of BSPM implementations and explore modern applications of advanced modeling and statistical analysis of BSPM data. We predict that BSPM will continue to be a valuable research tool, and will find clinical utility at the intersection of computational modeling approaches and artificial intelligence.","PeriodicalId":93563,"journal":{"name":"Hearts (Basel, Switzerland)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42084085","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Since its inception, the electrocardiogram (ECG) has been an essential tool in medicine. The ECG is more than a mere tracing of cardiac electrical activity; it can detect and diagnose various pathologies including arrhythmias, pericardial and myocardial disease, electrolyte disturbances, and pulmonary disease. The ECG is a simple, non-invasive, rapid, and cost-effective diagnostic tool in medicine; however, its clinical utility relies on the accuracy of its interpretation. Computer ECG analysis has become so widespread and relied upon that ECG literacy among clinicians is waning. With recent technological advances, the application of artificial intelligence-augmented ECG (AI-ECG) algorithms has demonstrated the potential to risk stratify, diagnose, and even interpret ECGs—all of which can have a tremendous impact on patient care and clinical workflow. In this review, we examine (i) the utility and importance of the ECG in clinical practice, (ii) the accuracy and limitations of current ECG interpretation methods, (iii) existing challenges in ECG education, and (iv) the potential use of AI-ECG algorithms for comprehensive ECG interpretation.
{"title":"ECG Interpretation: Clinical Relevance, Challenges, and Advances","authors":"N. Rafie, A. Kashou, P. Noseworthy","doi":"10.3390/hearts2040039","DOIUrl":"https://doi.org/10.3390/hearts2040039","url":null,"abstract":"Since its inception, the electrocardiogram (ECG) has been an essential tool in medicine. The ECG is more than a mere tracing of cardiac electrical activity; it can detect and diagnose various pathologies including arrhythmias, pericardial and myocardial disease, electrolyte disturbances, and pulmonary disease. The ECG is a simple, non-invasive, rapid, and cost-effective diagnostic tool in medicine; however, its clinical utility relies on the accuracy of its interpretation. Computer ECG analysis has become so widespread and relied upon that ECG literacy among clinicians is waning. With recent technological advances, the application of artificial intelligence-augmented ECG (AI-ECG) algorithms has demonstrated the potential to risk stratify, diagnose, and even interpret ECGs—all of which can have a tremendous impact on patient care and clinical workflow. In this review, we examine (i) the utility and importance of the ECG in clinical practice, (ii) the accuracy and limitations of current ECG interpretation methods, (iii) existing challenges in ECG education, and (iv) the potential use of AI-ECG algorithms for comprehensive ECG interpretation.","PeriodicalId":93563,"journal":{"name":"Hearts (Basel, Switzerland)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41844826","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
I. Doundoulakis, S. Soulaidopoulos, P. Arsenos, P. Dilaveris, D. Tsiachris, C. Antoniou, S. Sideris, A. Kordalis, A. Laina, Sotirios Kallinikidis, P. Xydis, S. Archontakis, K. Tsioufis, K. Gatzoulis
Syncope of cardiac origin may be associated with an increased risk of sudden cardiac death if not treated in a timely and appropriate manner. The diagnostic approach of syncope imposes a significant economic burden on society. The investigation and elucidation of the pathogenetic mechanism of syncope are of great clinical importance, as both prognosis and appropriate therapeutic approaches depend on these factors. The responsible mechanism of presyncope or syncope can only be revealed through the patient history, baseline clinical examination and electrocardiogram. The percentage of patients who are diagnosed with these tests alone exceeds 50%. In patients with a history of organic or acquired heart disease or/and the presence of abnormal findings on the electrocardiogram, a further diagnostic electrophysiology inclusive approach should be followed to exclude life threatening arrhythmiological mechanism. However, if the patient does not suffer from underlying heart disease and does not show abnormal electrocardiographic findings in the electrocardiogram, then the probability in the electrophysiology study to find a responsible cause is small but not absent. The role of a two-step electrophysiology study inclusive risk stratification approach for the effective management of the former is thoroughly discussed in this review.
{"title":"Unexplained Syncope: The Importance of the Electrophysiology Study","authors":"I. Doundoulakis, S. Soulaidopoulos, P. Arsenos, P. Dilaveris, D. Tsiachris, C. Antoniou, S. Sideris, A. Kordalis, A. Laina, Sotirios Kallinikidis, P. Xydis, S. Archontakis, K. Tsioufis, K. Gatzoulis","doi":"10.3390/hearts2040038","DOIUrl":"https://doi.org/10.3390/hearts2040038","url":null,"abstract":"Syncope of cardiac origin may be associated with an increased risk of sudden cardiac death if not treated in a timely and appropriate manner. The diagnostic approach of syncope imposes a significant economic burden on society. The investigation and elucidation of the pathogenetic mechanism of syncope are of great clinical importance, as both prognosis and appropriate therapeutic approaches depend on these factors. The responsible mechanism of presyncope or syncope can only be revealed through the patient history, baseline clinical examination and electrocardiogram. The percentage of patients who are diagnosed with these tests alone exceeds 50%. In patients with a history of organic or acquired heart disease or/and the presence of abnormal findings on the electrocardiogram, a further diagnostic electrophysiology inclusive approach should be followed to exclude life threatening arrhythmiological mechanism. However, if the patient does not suffer from underlying heart disease and does not show abnormal electrocardiographic findings in the electrocardiogram, then the probability in the electrophysiology study to find a responsible cause is small but not absent. The role of a two-step electrophysiology study inclusive risk stratification approach for the effective management of the former is thoroughly discussed in this review.","PeriodicalId":93563,"journal":{"name":"Hearts (Basel, Switzerland)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46838030","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The ambulatory ECG (AECG) is an important diagnostic tool for many heart electrophysiology-related cases. AECG covers a wide spectrum of devices and applications. At the core of these devices and applications are the algorithms responsible for signal conditioning, ECG beat detection and classification, and event detections. Over the years, there has been huge progress for algorithm development and implementation thanks to great efforts by researchers, engineers, and physicians, alongside the rapid development of electronics and signal processing, especially machine learning (ML). The current efforts and progress in machine learning fields are unprecedented, and many of these ML algorithms have also been successfully applied to AECG applications. This review covers some key AECG applications of ML algorithms. However, instead of doing a general review of ML algorithms, we are focusing on the central tasks of AECG and discussing what ML can bring to solve the key challenges AECG is facing. The center tasks of AECG signal processing listed in the review include signal preprocessing, beat detection and classification, event detection, and event prediction. Each AECG device/system might have different portions and forms of those signal components depending on its application and the target, but these are the topics most relevant and of greatest concern to the people working in this area.
{"title":"Applications of Machine Learning in Ambulatory ECG","authors":"J. Xue, Long Yu","doi":"10.3390/hearts2040037","DOIUrl":"https://doi.org/10.3390/hearts2040037","url":null,"abstract":"The ambulatory ECG (AECG) is an important diagnostic tool for many heart electrophysiology-related cases. AECG covers a wide spectrum of devices and applications. At the core of these devices and applications are the algorithms responsible for signal conditioning, ECG beat detection and classification, and event detections. Over the years, there has been huge progress for algorithm development and implementation thanks to great efforts by researchers, engineers, and physicians, alongside the rapid development of electronics and signal processing, especially machine learning (ML). The current efforts and progress in machine learning fields are unprecedented, and many of these ML algorithms have also been successfully applied to AECG applications. This review covers some key AECG applications of ML algorithms. However, instead of doing a general review of ML algorithms, we are focusing on the central tasks of AECG and discussing what ML can bring to solve the key challenges AECG is facing. The center tasks of AECG signal processing listed in the review include signal preprocessing, beat detection and classification, event detection, and event prediction. Each AECG device/system might have different portions and forms of those signal components depending on its application and the target, but these are the topics most relevant and of greatest concern to the people working in this area.","PeriodicalId":93563,"journal":{"name":"Hearts (Basel, Switzerland)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44029726","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This chapter is a review of studies that have examined false arrhythmia alarms during in-hospital electrocardiographic (ECG) monitoring in the intensive care unit. In addition, we describe an annotation effort being conducted at the UCSF School of Nursing, Center for Physiologic Research designed to improve algorithms for lethal arrhythmias (i.e., asystole, ventricular fibrillation, and ventricular tachycardia). Background: Alarm fatigue is a serious patient safety hazard among hospitalized patients. Data from the past five years, showed that alarm fatigue was responsible for over 650 deaths, which is likely lower than the actual number due to under-reporting. Arrhythmia alarms are a common source of false alarms and 90% are false. While clinical scientists have implemented a number of interventions to reduce these types of alarms (e.g., customized alarm settings; daily skin electrode changes; disposable vs. non-disposable lead wires; and education), only minor improvements have been made. This is likely as these interventions do not address the primary problem of false arrhythmia alarms, namely deficient and outdated arrhythmia algorithms. In this chapter we will describe a number of ECG features associated with false arrhythmia alarms. In addition, we briefly discuss an annotation effort our group has undertaken to improve lethal arrhythmia algorithms.
{"title":"Computer Assisted Patient Monitoring: Associated Patient, Clinical and ECG Characteristics and Strategy to Minimize False Alarms","authors":"M. Pelter, D. Mortara, F. Badilini","doi":"10.3390/hearts2040036","DOIUrl":"https://doi.org/10.3390/hearts2040036","url":null,"abstract":"This chapter is a review of studies that have examined false arrhythmia alarms during in-hospital electrocardiographic (ECG) monitoring in the intensive care unit. In addition, we describe an annotation effort being conducted at the UCSF School of Nursing, Center for Physiologic Research designed to improve algorithms for lethal arrhythmias (i.e., asystole, ventricular fibrillation, and ventricular tachycardia). Background: Alarm fatigue is a serious patient safety hazard among hospitalized patients. Data from the past five years, showed that alarm fatigue was responsible for over 650 deaths, which is likely lower than the actual number due to under-reporting. Arrhythmia alarms are a common source of false alarms and 90% are false. While clinical scientists have implemented a number of interventions to reduce these types of alarms (e.g., customized alarm settings; daily skin electrode changes; disposable vs. non-disposable lead wires; and education), only minor improvements have been made. This is likely as these interventions do not address the primary problem of false arrhythmia alarms, namely deficient and outdated arrhythmia algorithms. In this chapter we will describe a number of ECG features associated with false arrhythmia alarms. In addition, we briefly discuss an annotation effort our group has undertaken to improve lethal arrhythmia algorithms.","PeriodicalId":93563,"journal":{"name":"Hearts (Basel, Switzerland)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48655205","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Gabriela M. M. Paixão, Emilly M Lima, P. R. Gomes, D. Oliveira, Manoel Horta Ribeiro, Jamil S. Nascimento, A. H. Ribeiro, P. Macfarlane, A. L. Ribeiro
Computerized electrocardiography (ECG) has been widely used and allows linkage to electronic medical records. The present study describes the development and clinical applications of an electronic cohort derived from a digital ECG database obtained by the Telehealth Network of Minas Gerais, Brazil, for the period 2010–2017, linked to the mortality data from the national information system, the Clinical Outcomes in Digital Electrocardiography (CODE) dataset. From 2,470,424 ECGs, 1,773,689 patients were identified. A total of 1,666,778 (94%) underwent a valid ECG recording for the period 2010 to 2017, with 1,558,421 patients over 16 years old; 40.2% were men, with a mean age of 51.7 [SD 17.6] years. During a mean follow-up of 3.7 years, the mortality rate was 3.3%. ECG abnormalities assessed were: atrial fibrillation (AF), right bundle branch block (RBBB), left bundle branch block (LBBB), atrioventricular block (AVB), and ventricular pre-excitation. Most ECG abnormalities (AF: Hazard ratio [HR] 2.10; 95% CI 2.03–2.17; RBBB: HR 1.32; 95%CI 1.27–1.36; LBBB: HR 1.69; 95% CI 1.62–1.76; first degree AVB: Relative survival [RS]: 0.76; 95% CI0.71–0.81; 2:1 AVB: RS 0.21 95% CI0.09–0.52; and RS 0.36; third degree AVB: 95% CI 0.26–0.49) were predictors of overall mortality, except for ventricular pre-excitation (HR 1.41; 95% CI 0.56–3.57) and Mobitz I AVB (RS 0.65; 95% CI 0.34–1.24). In conclusion, a large ECG database established by a telehealth network can be a useful tool for facilitating new advances in the fields of digital electrocardiography, clinical cardiology and cardiovascular epidemiology.
{"title":"Electrocardiographic Predictors of Mortality: Data from a Primary Care Tele-Electrocardiography Cohort of Brazilian Patients","authors":"Gabriela M. M. Paixão, Emilly M Lima, P. R. Gomes, D. Oliveira, Manoel Horta Ribeiro, Jamil S. Nascimento, A. H. Ribeiro, P. Macfarlane, A. L. Ribeiro","doi":"10.3390/hearts2040035","DOIUrl":"https://doi.org/10.3390/hearts2040035","url":null,"abstract":"Computerized electrocardiography (ECG) has been widely used and allows linkage to electronic medical records. The present study describes the development and clinical applications of an electronic cohort derived from a digital ECG database obtained by the Telehealth Network of Minas Gerais, Brazil, for the period 2010–2017, linked to the mortality data from the national information system, the Clinical Outcomes in Digital Electrocardiography (CODE) dataset. From 2,470,424 ECGs, 1,773,689 patients were identified. A total of 1,666,778 (94%) underwent a valid ECG recording for the period 2010 to 2017, with 1,558,421 patients over 16 years old; 40.2% were men, with a mean age of 51.7 [SD 17.6] years. During a mean follow-up of 3.7 years, the mortality rate was 3.3%. ECG abnormalities assessed were: atrial fibrillation (AF), right bundle branch block (RBBB), left bundle branch block (LBBB), atrioventricular block (AVB), and ventricular pre-excitation. Most ECG abnormalities (AF: Hazard ratio [HR] 2.10; 95% CI 2.03–2.17; RBBB: HR 1.32; 95%CI 1.27–1.36; LBBB: HR 1.69; 95% CI 1.62–1.76; first degree AVB: Relative survival [RS]: 0.76; 95% CI0.71–0.81; 2:1 AVB: RS 0.21 95% CI0.09–0.52; and RS 0.36; third degree AVB: 95% CI 0.26–0.49) were predictors of overall mortality, except for ventricular pre-excitation (HR 1.41; 95% CI 0.56–3.57) and Mobitz I AVB (RS 0.65; 95% CI 0.34–1.24). In conclusion, a large ECG database established by a telehealth network can be a useful tool for facilitating new advances in the fields of digital electrocardiography, clinical cardiology and cardiovascular epidemiology.","PeriodicalId":93563,"journal":{"name":"Hearts (Basel, Switzerland)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47978013","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This article traces the development of automated electrocardiography from its beginnings in Washington, DC around 1960 through to its current widespread application worldwide. Changes in the methodology of recording ECGs in analogue form using sizeable equipment through to digital recording, even in wearables, are included. Methods of analysis are considered from single lead to three leads to twelve leads. Some of the influential figures are mentioned while work undertaken locally is used to outline the progress of the technique mirrored in other centres. Applications of artificial intelligence are also considered so that the reader can find out how the field has been constantly evolving over the past 50 years.
{"title":"Automated ECG Interpretation—A Brief History from High Expectations to Deepest Networks","authors":"P. Macfarlane, Julie Kennedy","doi":"10.3390/hearts2040034","DOIUrl":"https://doi.org/10.3390/hearts2040034","url":null,"abstract":"This article traces the development of automated electrocardiography from its beginnings in Washington, DC around 1960 through to its current widespread application worldwide. Changes in the methodology of recording ECGs in analogue form using sizeable equipment through to digital recording, even in wearables, are included. Methods of analysis are considered from single lead to three leads to twelve leads. Some of the influential figures are mentioned while work undertaken locally is used to outline the progress of the technique mirrored in other centres. Applications of artificial intelligence are also considered so that the reader can find out how the field has been constantly evolving over the past 50 years.","PeriodicalId":93563,"journal":{"name":"Hearts (Basel, Switzerland)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42810502","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A. Bayés-de-Luna, Miquel Fiol-Sala, M. Martínez‐Sellés, A. Baranchuk
Interatrial blocks like other types of block may be of first degree or partial second degree, also named transient atrial block or atrial aberrancy, and third degree or advanced. In first degree, partial interatrial block (P-IAB), the electrical impulse is conducted to the left atrium, through the Bachmann’s region, but with delay. The ECG shows a P-wave ≥ 120 ms. In third-degree, advanced interatrial block (A-IAB), the electrical impulse is blocked in the upper part of the interatrial septum (Bachmann region); the breakthrough to LA has to be performed retrogradely from the AV junction zone. This explains the p ± in leads II, III and aVF. In typical cases of A-IAB, the P-wave morphology is biphasic (±) in leads II, III and aVF, because the left atrium is activated retrogradely and, therefore, the last part of the atrial activation falls in the negative hemifield of leads II, III and aVF. Recently, some atypical cases of A-IAB have been described. The presence of A-IAB is a risk factor for atrial fibrillation, stroke, dementia, and premature death.
{"title":"Current ECG Aspects of Interatrial Block","authors":"A. Bayés-de-Luna, Miquel Fiol-Sala, M. Martínez‐Sellés, A. Baranchuk","doi":"10.3390/hearts2030033","DOIUrl":"https://doi.org/10.3390/hearts2030033","url":null,"abstract":"Interatrial blocks like other types of block may be of first degree or partial second degree, also named transient atrial block or atrial aberrancy, and third degree or advanced. In first degree, partial interatrial block (P-IAB), the electrical impulse is conducted to the left atrium, through the Bachmann’s region, but with delay. The ECG shows a P-wave ≥ 120 ms. In third-degree, advanced interatrial block (A-IAB), the electrical impulse is blocked in the upper part of the interatrial septum (Bachmann region); the breakthrough to LA has to be performed retrogradely from the AV junction zone. This explains the p ± in leads II, III and aVF. In typical cases of A-IAB, the P-wave morphology is biphasic (±) in leads II, III and aVF, because the left atrium is activated retrogradely and, therefore, the last part of the atrial activation falls in the negative hemifield of leads II, III and aVF. Recently, some atypical cases of A-IAB have been described. The presence of A-IAB is a risk factor for atrial fibrillation, stroke, dementia, and premature death.","PeriodicalId":93563,"journal":{"name":"Hearts (Basel, Switzerland)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44371195","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Updates to industry consensus standards for ECG equipment is a work-in-progress by the ISO/IEC Joint Work Group 22. This work will result in an overhaul of existing industry standards that apply to ECG electromedical equipment and will result in a new single international industry, namely 80601-2-86. The new standard will be entitled “80601, Part 2-86: Particular requirements for the basic safety and essential performance of electrocardiographs, including diagnostic equipment, monitoring equipment, ambulatory equipment, electrodes, cables, and leadwires”. This paper will provide a high-level overview of the work in progress and, in particular, will describe the impact it will have on requirements and testing methods for computerized ECG interpretation algorithms. The conclusion of this work is that manufacturers should continue working with clinical ECG experts to make clinically meaningful improvements to automated ECG interpretation, and the clinical validation of ECG analysis algorithms should be disclosed to guide appropriate clinical use. More cooperation is needed between industry, clinical ECG experts and regulatory agencies to develop new data sets that can be made available for use by industry standards for algorithm performance evaluation.
{"title":"The New ISO/IEC Standard for Automated ECG Interpretation","authors":"B. Young, J. Schmid","doi":"10.3390/hearts2030032","DOIUrl":"https://doi.org/10.3390/hearts2030032","url":null,"abstract":"Updates to industry consensus standards for ECG equipment is a work-in-progress by the ISO/IEC Joint Work Group 22. This work will result in an overhaul of existing industry standards that apply to ECG electromedical equipment and will result in a new single international industry, namely 80601-2-86. The new standard will be entitled “80601, Part 2-86: Particular requirements for the basic safety and essential performance of electrocardiographs, including diagnostic equipment, monitoring equipment, ambulatory equipment, electrodes, cables, and leadwires”. This paper will provide a high-level overview of the work in progress and, in particular, will describe the impact it will have on requirements and testing methods for computerized ECG interpretation algorithms. The conclusion of this work is that manufacturers should continue working with clinical ECG experts to make clinically meaningful improvements to automated ECG interpretation, and the clinical validation of ECG analysis algorithms should be disclosed to guide appropriate clinical use. More cooperation is needed between industry, clinical ECG experts and regulatory agencies to develop new data sets that can be made available for use by industry standards for algorithm performance evaluation.","PeriodicalId":93563,"journal":{"name":"Hearts (Basel, Switzerland)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48658814","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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