1
|
Naydenov S, Jekova I, Krasteva V. Recognition of Supraventricular Arrhythmias in Holter ECG Recordings by ECHOView Color Map: A Case Series Study. J Cardiovasc Dev Dis 2023; 10:360. [PMID: 37754789 PMCID: PMC10532174 DOI: 10.3390/jcdd10090360] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2023] [Revised: 08/22/2023] [Accepted: 08/22/2023] [Indexed: 09/28/2023] Open
Abstract
Ambulatory 24-72 h Holter ECG monitoring is recommended for patients with suspected arrhythmias, which are often transitory and might remain unseen in resting standard 12-lead ECG. Holter manufacturers provide software diagnostic tools to assist clinicians in evaluating these large amounts of data. Nevertheless, the identification of short arrhythmia events and differentiation of the arrhythmia type might be a problem in limited Holter ECG leads. This observational clinical study aims to explore a novel and weakly investigated ECG modality integrated into a commercial diagnostic tool ECHOView (medilog DARWIN 2, Schiller AG, Switzerland), while used for the interpretation of long-term Holter-ECG records by a cardiologist. The ECHOView transformation maps the beat waveform amplitude to a color-coded bar. One ECHOView page integrates stacked color bars of about 1740 sequential beats aligned by R-peak in a window (R ± 750 ms). The collected 3-lead Holter ECG recordings from 86 patients had a valid duration of 21 h 20 min (19 h 30 min-22 h 45 min), median (quartile range). The ECG rhythm was reviewed with 3491 (3192-3723) standard-grid ECG pages and a substantially few number of 51 (44-59) ECHOView pages that validated the ECHOView compression ratio of 67 (59-74) times. Comments on the ECG rhythm and ECHOView characteristic patterns are provided for 14 examples representative of the most common rhythm disorders seen in our population, including supraventricular arrhythmias (supraventricular extrasystoles, paroxysmal supraventricular arrhythmia, sinus tachycardia, supraventricular tachycardia, atrial fibrillation, and flutter) and ventricular arrhythmias (ventricular extrasystoles, non-sustained ventricular tachycardia). In summary, the ECHOView color map transforms the ECG modality into a novel diagnostic image of the patient's rhythm that is comprehensively interpreted by a cardiologist. ECHOView has the potential to facilitate the manual overview of Holter ECG recordings, to visually identify short-term arrhythmia episodes, and to refine the diagnosis, especially in high-rate arrhythmias.
Collapse
Affiliation(s)
- Stefan Naydenov
- Department of Internal Diseases “Prof. St. Kirkovich”, Medical University of Sofia, 1431 Sofia, Bulgaria;
| | - Irena Jekova
- Institute of Biophysics and Biomedical Engineering, Bulgarian Academy of Sciences, Acad. G. Bonchev Str. Bl. 105, 1113 Sofia, Bulgaria;
| | - Vessela Krasteva
- Institute of Biophysics and Biomedical Engineering, Bulgarian Academy of Sciences, Acad. G. Bonchev Str. Bl. 105, 1113 Sofia, Bulgaria;
| |
Collapse
|
3
|
Brown DL, Xu G, Belinky Krzyske AM, Buhay NC, Blaha M, Wang MM, Farrehi P, Borjigin J. Electrocardiomatrix Facilitates Accurate Detection of Atrial Fibrillation in Stroke Patients. Stroke 2019; 50:1676-1681. [PMID: 31177972 DOI: 10.1161/strokeaha.119.025361] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
Background and Purpose- Cardiac telemetry is a routine part of inpatient ischemic stroke/transient ischemic attack evaluation to assess for atrial fibrillation (AF). Yet, tools to assist stroke clinicians in the evaluation of the large quantities of telemetry data are limited. The investigators developed a new method to evaluate electrocardiographic signals, electrocardiomatrix, that was applied to stroke unit telemetry data to determine its feasibility, validity, and usefulness. Electrocardiomatrix displays telemetry data in a 3-dimensional matrix that allows for more accurate and less time consuming P-wave analysis. Methods- In this single-center, prospective, observational study conducted in a stroke unit, all telemetry data from ischemic stroke and transient ischemic attack patients were collected (April 2017-January 2018) for examination facilitated by electrocardiomatrix. AF>30 seconds was identified through review of electrocardiomatrix-generated matrices by a nonphysician researcher. Electrocardiomatrix results were compared with the clinical team's medical record documentation of AF identified through telemetry. A study cardiologist reviewed the standard telemetry associated with all AF episodes identified by electrocardiomatrix and each case of disagreement. Results- Telemetry data (median 46 hours [interquartile range: 22-90]) were analyzed among 265 unique subjects (88% ischemic stroke). Electrocardiomatrix was successfully applied in 260 (98%) of cases. The positive predictive value of electrocardiomatrix compared with the clinical documentation was 86% overall and 100% among the subset with no prior history of AF. For the 5 false-positive and 5 false-negative cases, expert overview disagreed with the clinical documentation and confirmed the electrocardiomatrix-based diagnosis. Conclusions- The application of electrocardiomatrix to stroke unit-acquired telemetry data is feasible and appears to have superior accuracy compared with traditional monitor analysis by noncardiologists.
Collapse
Affiliation(s)
- Devin L Brown
- From the Departments of Neurology (D.L.B., N.B., M.M.W., J.B.), University of Michigan Medical School, Ann Arbor.,Cardiovascular Center (D.L.B., M.M.W., J.B.), University of Michigan Medical School, Ann Arbor
| | - Gang Xu
- Molecular and Integrative Physiology (G.X., A.M.B.K., M.B., M.M.W., J.B.), University of Michigan Medical School, Ann Arbor
| | - Alexandra Mary Belinky Krzyske
- Molecular and Integrative Physiology (G.X., A.M.B.K., M.B., M.M.W., J.B.), University of Michigan Medical School, Ann Arbor
| | - Nicholas C Buhay
- From the Departments of Neurology (D.L.B., N.B., M.M.W., J.B.), University of Michigan Medical School, Ann Arbor
| | - Madeline Blaha
- Molecular and Integrative Physiology (G.X., A.M.B.K., M.B., M.M.W., J.B.), University of Michigan Medical School, Ann Arbor
| | - Michael M Wang
- From the Departments of Neurology (D.L.B., N.B., M.M.W., J.B.), University of Michigan Medical School, Ann Arbor.,Molecular and Integrative Physiology (G.X., A.M.B.K., M.B., M.M.W., J.B.), University of Michigan Medical School, Ann Arbor.,Cardiovascular Center (D.L.B., M.M.W., J.B.), University of Michigan Medical School, Ann Arbor.,the VA Ann Arbor Healthcare System, MI (M.M.W.)
| | - Peter Farrehi
- Internal Medicine-Cardiology (P.F.), University of Michigan Medical School, Ann Arbor
| | - Jimo Borjigin
- From the Departments of Neurology (D.L.B., N.B., M.M.W., J.B.), University of Michigan Medical School, Ann Arbor.,Molecular and Integrative Physiology (G.X., A.M.B.K., M.B., M.M.W., J.B.), University of Michigan Medical School, Ann Arbor.,Cardiovascular Center (D.L.B., M.M.W., J.B.), University of Michigan Medical School, Ann Arbor
| |
Collapse
|