Early Detection of Symptomatic Paroxysmal Cardiac Arrhythmias by Trans-Telephonic ECG Monitoring: Impact on Diagnosis and Treatment of Atrial Fibrillation

Advantages of using a portable cardiac monitor in outpatients with paroxysmal atrial fibrillation

Aim. To study the advantages of using a portable electrocardiographic (ECG) monitor in outpatients with paroxysmal atrial fibrillation (AF).

Material and methods. We examined 88 patients (26 men, 62 women, mean age, 63 [57;68] years) with paroxysmal AF with an average frequency of arrhythmia episodes of 1,0 [0.3;3.75] per month. Forty three (49%) patients were included in the remote monitoring (RM) group using the ECG Dongle monitor, and 45 (51%) patients were included in the conventional monitoring (CM) group. Patients underwent scheduled examinations 2, 6 and 12 months after the start of therapy. Unscheduled consultations were carried out in case of AF recurrence. Patients from the RM group, using portable cardiac monitor, additionally self-registered ECG 1 time per week and in case of symptoms suggestive of AF. ECG strips were sent to the clinical investigator for analysis.

Results. With the help of portable cardiac monitor, 2477 ECG strips were collected and analyzed: 2159 (87,2%) — sinus rhythm, 318 (12,8%) — AF and atypical atrial flutter. Forty four episodes of AF in 3 patients were asymptomatic. In addition, 211 (8,5%) sinus rhythm ECG strips were recorded by 13 patients with symptoms suggestive of AF. In the RM group, 7 (16%) patients were hospitalized due to recurrent AF, while in the CM group, 20 (44%) patients (p=0,004). The total number of emergency hospitalizations was 8 and 29 in the RM and CM groups, respectively. The number of patients who called an ambulance was significantly lower in the RM group: in the CM group, 37 calls for an ambulance were made by 22 patients, while in the RM group — 12 patients made 15 calls (p=0,044). The proportion of calls followed by hospitalization (40 vs 70%, p=0,043) was significantly lower in the RM group.

Conclusion. Remote ECG monitoring using the ECG Dongle system is a useful way to monitor patients with paroxysmal AF, which make it possible to register asymptomatic AF episodes, differentiate the causes of palpitations, and significantly reduce the frequency of emergency calls and hospitalizations.

Improving care for patients with atrial fibrillation through the use of a personal electrocardiogram

BACKGROUND

Atrial fibrillation (AF) is the most common arrhythmia affecting more than six million people in the United States. The economic burden is estimated to be >$6 billion annually with catastrophic events dramatically increasing expenditure. When patients experience symptoms, they commonly present to an acute care facility; this can be costly and anxiety provoking.

LOCAL PROBLEM

Same-day access issues prohibit patients from communicating directly with their cardiology provider, forcing them to use resources and increasing psychological burden.

METHODS

A convenience sample, made up of 43 patients, was given a KardiaMobile device. Eligible patients had ≥2 AF-related emergency department (ED) or urgent care (UC) visits over 12 months, needed rate control with medication titration, or were monitored for AF reoccurrence after reestablishing sinus rhythm.

INTERVENTIONS

Patients emailed recordings daily and when experiencing symptoms. The recordings were reviewed by a nurse practitioner (NP); abnormal readings were followed by a phone call, telehealth, or in-person visit.

RESULTS

An independently designed survey was conducted online; almost all respondents (97%) found value in the project and the device. Virtually all respondents (97%) felt that the program improved access. A majority (86%) reported decreased anxiety. Had the respondents not been in the program, 34% indicated that they would have presented to an ED and 25% would have presented to an UC, realizing a cost savings of $81,950 in reduced ED visits alone.

CONCLUSION

A personal electrocardiogram, with NP oversight, to manage AF is cost-effective and reduces unnecessary resource utilization. It is patient centered, improves access, and empowers patients to manage their symptoms.

Effects of Tau and Sampling Frequency on the Regularity Analysis of ECG and EEG Signals Using ApEn and SampEn Entropy Estimators

Electrocardiography (ECG) and electroencephalography (EEG) signals provide clinical information relevant to determine a patient’s health status. The nonlinear analysis of ECG and EEG signals allows for discovering characteristics that could not be found with traditional methods based on amplitude and frequency. Approximate entropy (ApEn) and sampling entropy (SampEn) are nonlinear data analysis algorithms that measure the data’s regularity, and these are used to classify different electrophysiological signals as normal or pathological. Entropy calculation requires setting the parameters r (tolerance threshold), m (immersion dimension), and τ (time delay), with the last one being related to how the time series is downsampled. In this study, we showed the dependence of ApEn and SampEn on different values of τ, for ECG and EEG signals with different sampling frequencies (F_s), extracted from a digital repository. We considered four values of F_s (128, 256, 384, and 512 Hz for the ECG signals, and 160, 320, 480, and 640 Hz for the EEG signals) and five values of τ (from 1 to 5). We performed parametric and nonparametric statistical tests to confirm that the groups of normal and pathological ECG and EEG signals were significantly different (p < 0.05) for each F and τ value. The separation between the entropy values of regular and irregular signals was variable, demonstrating the dependence of ApEn and SampEn with F_s and τ. For ECG signals, the separation between the conditions was more robust when using SampEn, the lowest value of F_s, and τ larger than 1. For EEG signals, the separation between the conditions was more robust when using SampEn with large values of F_s and τ larger than 1. Therefore, adjusting τ may be convenient for signals that were acquired with different F_s to ensure a reliable clinical classification. Furthermore, it is useful to set τ to values larger than 1 to reduce the computational cost.

Transtelephonic ECG Monitoring to Guide Outpatient Antiarrhythmic Drug Therapy in Patients With Non-Permanent Atrial Fibrillation: Efficacy and Safety From a Single-Center Experience

Initiation of antiarrhythmic drug therapy (AADx) for atrial fibrillation (AF) on an outpatient basis requires intensive ECG monitoring in order to assess antiarrhythmic efficacy as well as ECG signals of potential proarrhythmia. Dronedarone (DRO) reduces cardiovascular endpoints in AF patients fulfilling criteria of the ATHENA trial [1]. In the present study transtelephonic ECG monitoring was used to guide initiation of AADx in AF patients fulfilling the ATHENA criteria. In 19 consecutive patients (37% female; age 65+10 years; LVEF 62+7%; mean CHA2DS2-VASc score 2.9 + 1.6 (median=2), with symptomatic non-permanent AF and additional cardiovascular risk factors, DRO was prescribed as AADx of first choice. Initiation of therapy and follow-up were monitored by transtelephonic ECG recordings (VITAPHONE™100 IR; Vitaphone GmbH; Germany). In patients with persistent AF, electrical cardioversion was performed on an outpatient basis when DRO was started. Patients were followed for changes in QT intervals as well as AF recurrency. ECGs were transmitted according to a scheduled FU form as well as any time in case of pts symptoms. Patients in whom DRO did not prevent AF recurrence were switched to alternative AADx, or to pulmonary vein isolation (PVI), respectively. At the end of long-term follow-up, DRO alone was successful in preventing AF recurrence in 5 of 19 patients (26%). When pts who responded to AADx of second or third choice or who underwent PVI were included, SR could be maintained in 17/19 pts (89%). No patient required discontinuation of AADx due to ventricular depolarization abnormalities, symptomatic bradycardia or pathologic QT prolongation. In conclusion, transtelephonic ECG transmission is useful for close rhythm monitoring during initiation and follow-up of AADx, also during change from DRO to other AADx. DRO was effective to prevent AF recurrence in 26% of patients during a mean long-term follow-up of more than 30 months - which is well in line with data from the literature.

Blending Electronics with the Human Body: A Pathway toward a Cybernetic Future

At the crossroads of chemistry, electronics, mechanical engineering, polymer science, biology, tissue engineering, computer science, and materials science, electrical devices are currently being engineered that blend directly within organs and tissues. These sophisticated devices are mediators, recorders, and stimulators of electricity with the capacity to monitor important electrophysiological events, replace disabled body parts, or even stimulate tissues to overcome their current limitations. They are therefore capable of leading humanity forward into the age of cyborgs, a time in which human biology can be hacked at will to yield beings with abilities beyond their natural capabilities. The resulting advances have been made possible by the emergence of conformal and soft electronic materials that can readily integrate with the curvilinear, dynamic, delicate, and flexible human body. This article discusses the recent rapid pace of development in the field of cybernetics with special emphasis on the important role that flexible and electrically active materials have played therein.

A PHONOCARDIOGRAM-BASED NOISE-ROBUST REAL-TIME HEART RATE MONITORING ALGORITHM FOR OUTPATIENTS DURING NORMAL ACTIVITIES

For outpatients who need continuous monitoring of heart rate (HR) variation, it is important that HR can be monitored during normal activities such as speaking and walking. In this study, a noise-robust real-time HR monitoring algorithm based on phonocardiogram (PCG) signals is proposed. PCG signals were recorded using an electronic stethoscope; electrocardiogram (ECG) signals were recorded simultaneously with HR references. The proposed algorithm consisted of pre-processing, peak/nonpeak classification, voice noise processing, walking noise processing, and HR calculation. The performance of the algorithm was evaluated using PCG/ECG signals from 11 healthy participants. For comparison, the absolute errors between manually extracted ECG-based HR values and automatically calculated PCG-based HR values were calculated for the proposed algorithm and the comparison algorithm in two different test protocols. Experimental results showed that the average absolute errors of the proposed algorithm were 72.03%, 22.92%, and 36.39% of the values of the comparison algorithm for resting-state, speaking-state, and walking-state data, respectively, in protocol-1. In protocol-2, the average absolute error was 36.99% of that of the comparison algorithm. A total of 1102 cases in protocol-1 and 783 in protocol-2 had an absolute error [Formula: see text] beats per minute (BPM) using the comparison algorithm and an absolute error [Formula: see text] BPM using the proposed algorithm. On the basis of these results, we anticipate that the proposed algorithm can potentially improve the performance of continuous real-time HR monitoring during activities of normal life, thereby improving the safety of outpatients with cardiovascular diseases.