HRS/EHRA/APHRS/LAHRS/ACC/AHA Worldwide Practice Update for Telehealth and Arrhythmia Monitoring During and After a Pandemic

Evaluating Clinical Outcomes and Physician Adoption of Telemedicine for Chronic Disease Management: Population-Based Retrospective Cohort Study

BACKGROUND

In recent years, the use and impact of telemedicine for providing health care services to patients has increased, reducing the requirement for physical, in-person encounters.

OBJECTIVE

This study aimed to compare the use of telemedicine for outpatient visits versus in-person visits across different medical specialties; assess its association with clinical outcomes; and examine the influence of patient and physician characteristics on telemedicine use in a large, tertiary, teaching hospital.

METHODS

The study cohort consisted of adult patients who attended outpatient clinics in five medical fields (psychiatry, endocrinology, nephrology, hemato-oncology, and gastroenterology) in 2019 and survived until the beginning of 2020. Telemedicine use during the period of 2019-2021 was the main exposure of interest. The primary outcomes were emergency department (ED) referrals and hospitalizations. The analysis used multivariate mixed models and subgroup analysis by patient demographic characteristics, chronic disease medical fields, and physicians' characteristics.

RESULTS

The cohort included 32,445 patients. In 2019, a total of 99.6% (82,668/83,000) of visits were in person, and by 2020-2021, a total of 22.6% (10,850/48,120) of patients had used telemedicine. Telemedicine patients were slightly older (standardized mean difference=0.281; P<.001), with a higher comorbidity burden than in-person patients or patients without visits (standardized mean difference=0.328; P<.001). Presurge telemedicine users had higher rates of ED referrals (incidence rate ratio [IRR] 1.15, 95% CI 1.09-1.21) and hospitalizations (IRR 1.14, 95% CI 1.08-1.20) than in-person visit users. These ratios remained stable during the surge (IRR 1.1, 95% CI 1.06-1.16 and IRR 1.12, 95% CI 1.05-1.19, respectively), with no evidence of worsening outcomes for telemedicine users relative to in-person care. Health care providers with higher telemedicine use had reduced rates of ED referrals (IRR 0.85, 95% CI 0.79-0.91) and hospitalizations (IRR 0.78, 95% CI 0.72-0.84) than providers with lower telemedicine use.

CONCLUSIONS

This study provides insights into telemedicine use patterns and their association with clinical outcomes in chronic disease management. Our findings suggest that the increase in telemedicine use was not associated with a rise in ED referrals or hospitalizations when compared to in-person visits. It highlights the importance of health care providers' perspectives and use of remote visits. Telemedicine should be tailored to individual patient-physician needs, considering the nature of the patient's disease.

Atrial Fibrillation Occurring During Acute Hospitalization: A Scientific Statement From the American Heart Association

Acute atrial fibrillation is defined as atrial fibrillation detected in the setting of acute care or acute illness; atrial fibrillation may be detected or managed for the first time during acute hospitalization for another condition. Atrial fibrillation after cardiothoracic surgery is a distinct type of acute atrial fibrillation. Acute atrial fibrillation is associated with high risk of long-term atrial fibrillation recurrence, warranting clinical attention during acute hospitalization and over long-term follow-up. A framework of substrates and triggers can be useful for evaluating and managing acute atrial fibrillation. Acute management requires a multipronged approach with interdisciplinary care collaboration, tailoring treatments to the patient's underlying substrate and acute condition. Key components of acute management include identification and treatment of triggers, selection and implementation of rate/rhythm control, and management of anticoagulation. Acute rate or rhythm control strategy should be individualized with consideration of the patient's capacity to tolerate rapid rates or atrioventricular dyssynchrony, and the patient's ability to tolerate the risk of the therapeutic strategy. Given the high risks of atrial fibrillation recurrence in patients with acute atrial fibrillation, clinical follow-up and heart rhythm monitoring are warranted. Long-term management is guided by patient substrate, with implications for intensity of heart rhythm monitoring, anticoagulation, and considerations for rhythm management strategies. Overall management of acute atrial fibrillation addresses substrates and triggers. The 3As of acute management are acute triggers, atrial fibrillation rate/rhythm management, and anticoagulation. The 2As and 2Ms of long-term management include monitoring of heart rhythm and modification of lifestyle and risk factors, in addition to considerations for atrial fibrillation rate/rhythm management and anticoagulation. Several gaps in knowledge related to acute atrial fibrillation exist and warrant future research.

Beta-blockers in cardiac arrhythmias-Clinical pharmacologist's point of view

β-blockers is a vast group of antiarrhythmic drugs which differ in their pharmacokinetic and chemical properties. Some of them block β-adrenergic receptors selectively while the others work non-selectively. Consequently, they reduce the influence of the sympathetic nervous system on the heart, acting negatively inotropic, chronotropic, bathmotropic and dromotropic. Although they have been present in medicine since the beginning of the 1960s, they still play a crucial role in the treatment of cardiac arrhythmias. They are also first-line group of drugs used to control the ventricular rate in patients with the most common arrhythmia-atrial fibrillation. Previous reports indicate that infection with SARS-CoV-2 virus may constitute an additional risk factor for arrhythmia. Due to the aging of the population in developed countries and the increase in the number of patients with cardiac burden, the number of people suffering from cardiac arrhythmias will increase in the upcoming years. As a result the role of above-mentioned beta-blockers will remain significant. Particularly noteworthy is propranolol-the oldest beta adrenergic antagonist, which in recent years has found additional applications due to its unique properties. In this article, we reviewed the accessible literature and summarized the current guidelines on the use of beta-blockers in the treatment of cardiac arrhythmias.

Smartphone-based cardiac implantable electronic device remote monitoring: improved compliance and connectivity

Aims

Remote monitoring (RM) is the standard of care for follow up of patients with cardiac implantable electronic devices. The aim of this study was to compare smartphone-based RM (SM-RM) using patient applications (myMerlinPulse™ app) with traditional bedside monitor RM (BM-RM).

Methods and results

The retrospective study included de-identified US patients who received either SM-RM or BM-RM capable of implantable cardioverter defibrillators or cardiac resynchronization therapy defibrillators (Abbott, USA). Patients in SM-RM and BM-RM groups were propensity-score matched on age and gender, device type, implant year, and month. Compliance with RM was quantified as the proportion of patients enrolling in the RM system (Merlin.net™) and transmitting data at least once. Connectivity was measured by the median number of days between consecutive transmissions per patient. Of the initial 9714 patients with SM-RM and 26 679 patients with BM-RM, 9397 patients from each group were matched. Remote monitoring compliance was higher in SM-RM; significantly more patients with SM-RM were enrolled in RM compared with BM-RM (94.4 vs. 85.0%, P < 0.001), similar number of patients in the SM-RM group paired their device (95.1 vs. 95.0%, P = 0.77), but more SM-RM patients transmitted at least once (98.1 vs. 94.3%, P < 0.001). Connectivity was significantly higher in the SM-RM, with patients transmitting data every 1.2 (1.1, 1.7) vs. every 1.7 (1.5, 2.0) days with BM-RM (P < 0.001) and remained better over time. Significantly more SM-RM patients utilized patient-initiated transmissions compared with BM-RM (55.6 vs. 28.1%, P < 0.001).

Conclusion

In this large real-world study, patients with SM-RM demonstrated improved compliance and connectivity compared with BM-RM.

Temporal trends in cardiovascular care: Insights from the COVID-19 pandemic

In response to the ongoing COVID-19 pandemic, public health care measures have been implemented to limit spread of the contagion and ensure adequate healthcare resource allocation. Correlating with these measures are observed changes in the incidence and outcomes of cardiovascular conditions in the absence of COVID-19 infection. The pandemic has resulted in a reduction in acute coronary syndrome, heart failure and arrhythmia admissions but with worsened outcomes in those diagnosed with these conditions. This is concerning of an underdiagnosis of cardiovascular diseases during the pandemic. Furthermore, cardiovascular services and investigations have decreased to provide healthcare allocation to COVID-19 related services. This threatens an increasing future prevalence of cardiovascular morbidity in healthcare systems that are still adapting to the challenges of a continuing pandemic. Adaption of virtual training and patient care delivery platforms have been shown to be useful, but adequate resources allocation is needed to ensure effectiveness in vulnerable populations.

Automated detection of low ejection fraction from a one-lead electrocardiogram: application of an AI algorithm to an electrocardiogram-enabled Digital Stethoscope. EUROPEAN HEART JOURNAL. DIGITAL HEALTH 2022;3:373-379. [PMID: 36712160 PMCID: PMC9708035 DOI: 10.1093/ehjdh/ztac030]

AIMS

Electrocardiogram (ECG)-enabled stethoscope (ECG-Scope) acquires a single-lead ECGs during cardiac auscultation and may facilitate real-time screening for pathologies not routinely identified by cardiac auscultation alone. We previously demonstrated an artificial intelligence (AI) algorithm can identify left ventricular dysfunction (LVSD) [defined as ejection fraction (EF) ≤ 40%] with an area under the curve (AUC) of 0.91 using a 12-lead ECG.

METHODS AND RESULTS

One hundred patients referred for clinically indicated echocardiography were prospectively recruited. ECG-Scope recordings with the patient supine and sitting were obtained in multiple electrode locations at the time of the echocardiogram. The AI algorithm for the detection of LVSD was retrained using single leads from ECG-12 and validated against ECG-Scope to determine accuracy for low EF detection (≤35%, <40%, or <50%). We evaluated the algorithm with respect to body position and lead location. Amongst 100 patients (aged 61.3 ± 13.8; 61% male, BMI: 30.0 ± 5.4), eight had EF≤40%, and six had EF 40-50%. The best single recording position was V2 with the patient supine [AUC: 0.88 (CI: 0.80-0.97) for EF≤35%, 0.85 (CI: 0.75-0.95) for EF≤40%, and 0.81 (CI: 0.71-0.90) for EF < 50%]. When using an AI model to select the recording automatically, AUC was 0.91 (CI: 0.84-0.97) for EF≤35%, 0.89 (CI: 0.83-0.96) for EF≤40%, and 0.84 (CI: 0.73-0.94) for EF < 50%.

CONCLUSION

An AI algorithm applied to an ECG-enabled stethoscope recording in standard auscultation positions reliably detected the presence of a low EF in this prospective study of patients referred for echocardiography. The ability to screen patients with a possible low EF during routine physical examination may facilitate rapid detection of LVSD.

Physical activity, patient-reported symptoms, and clinical events: Insights into postprocedural recovery from personal digital devices

Background

Personal digital devices may offer insights into patient recovery and an approach for remote monitoring after procedures.

Objective

To examine associations between activity measured using personal digital devices, patient-reported outcome measures (PROMs), and clinical events among patients after catheter ablation for atrial fibrillation (AF) or bariatric surgery.

Methods

We aggregated personal digital device, PROM, and electronic health record data in a study conducted at 2 health systems. We used Fitbit devices for step count assessments, KardiaMobile for cardiac rhythm assessments, and PROMs for pain and palpitations over 5 weeks.

Results

Among 59 patients, 30 underwent AF ablation and 29 bariatric surgery. Thirty-six patients (63%) reported pain. There was no difference in median [interquartile range] daily steps between patients with and those without pain (4419 [3286–7041] vs 3498 [2609–5888]; P = .23). Among AF ablation patients, 21 (70%) reported palpitations. Median daily steps were lower among those with palpitations than among those without (4668 [3021–6116] vs 8040 [6853–10,394]; P = .03). When accounting for within-subject correlation, recordings of AF were associated with a significant mean decrease in median daily steps (–351; 95% confidence interval –524 to –177; P <.01). Patients who received a new antiarrhythmic drug prescription had AF recorded in a median of 5 [5–5] of 5 total weeks, whereas patients who did not receive a new antiarrhythmic recorded AF in a median of 1 [0–3] week (P = .02).

Conclusion

Personal digital device and PROM data can provide insight into postprocedural recovery outside of usual clinical settings and may inform follow-up and clinical decision-making. (ClinicalTrials.gov Identifier: NCT03436082)

A Narrative Review of Factors Historically Influencing Telehealth Use across Six Medical Specialties in the United States

Prior to the COVID-19 pandemic, studies in the US have identified wide variations in telehealth use across medical specialties. This is an intriguing problem, because the US has historically lacked a standardized set of telehealth coverage and reimbursement policies, which has posed a barrier to telehealth use across all specialties. Although all medical specialties in the US have been affected by these macro (policy-level) barriers, some specialties have been able to integrate telehealth use into mainstream practice, while others are just gaining momentum with telehealth during COVID-19. Although the temporary removal of policy (coverage) restrictions during the pandemic has accelerated telehealth use, uncertainties remain regarding future telehealth sustainability. Since macro (policy-level) factors by themselves do not serve to explain the variation in telehealth use across specialties, it would be important to examine meso (organizational-level) and micro (individual-level) factors historically influencing telehealth use across specialties, to understand underlying reasons for variation and identify implications for widespread sustainability. This paper draws upon the existing literature to develop a conceptual framework on macro-meso-micro factors influencing telehealth use within a medical specialty. The framework is then used to guide a narrative review of the telehealth literature across six medical specialties, including three specialties with lower telehealth use (allergy-immunology, family medicine, gastroenterology) and three with higher telehealth use (psychiatry, cardiology, radiology) in the US, in order to synthesize themes and gain insights into barriers and facilitators to telehealth use. In doing so, this review addresses a gap in the literature and provides a foundation for future research. Importantly, it helps to identify implications for ensuring widespread sustainability of telehealth use in the post-pandemic future.

2021 ISHNE/HRS/EHRA/APHRS Expert Collaborative Statement on mHealth in Arrhythmia Management: Digital Medical Tools for Heart Rhythm Professionals: From the International Society for Holter and Noninvasive Electrocardiology/Heart Rhythm Society/European Heart Rhythm Association/Asia-Pacific Heart Rhythm Society

This collaborative statement from the International Society for Holter and Noninvasive Electrocardiology/Heart Rhythm Society/European Heart Rhythm Association/Asia-Pacific Heart Rhythm Society describes the current status of mobile health technologies in arrhythmia management. The range of digital medical tools and heart rhythm disorders that they may be applied to and clinical decisions that may be enabled are discussed. The facilitation of comorbidity and lifestyle management (increasingly recognized to play a role in heart rhythm disorders) and patient self-management are novel aspects of mobile health. The promises of predictive analytics but also operational challenges in embedding mobile health into routine clinical care are explored.

Arrhythmia in COVID-19

The current outbreak of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) also known as coronavirus disease 2019 (COVID-19) has quickly progressed to a global pandemic. There are well-documented cardiac complications of COVID-19 in patients with and without prior cardiovascular disease. The cardiac complications include myocarditis, heart failure, and acute coronary syndrome resulting from coronary artery thrombosis or SARS-CoV-2-related plaque ruptures. There is growing evidence showing that arrhythmias are also one of the major complications. Myocardial inflammation caused by viral infection leads to electrophysiological and structural remodeling as a possible mechanism for arrhythmia. This could also be the mechanism through which SARS-CoV-2 leads to different arrhythmias. In this review article, we discuss arrhythmia manifestations in COVID-19.