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 Table of Contents  
Year : 2019  |  Volume : 4  |  Issue : 2  |  Page : 35-42

The role of remote monitoring for cardiac implantable electronic devices

1 Division of Cardiology, Medical University of South Carolina, Charleston, SC, USA
2 Division of Cardiology, Medical University of South Carolina, Charleston, SC, USA; Department of Cardiology, Hirosaki University Graduate School of Medicine, Hirosaki, Aomori, Japan

Date of Submission07-Oct-2019
Date of Acceptance27-Mar-2020
Date of Web Publication15-Jun-2020

Correspondence Address:
Prof. Michael R Gold
Division of Cardiology, Medical University of South Carolina, 114 Doughty Street, MSC 592, Charleston, SC 29425-5920
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Source of Support: None, Conflict of Interest: None

DOI: 10.4103/IJHR.IJHR_4_19

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At present, remote monitoring (RM) is available for almost all cardiac implantable electronic devices. RM systems allow for enhanced surveillance and earlier detection of clinically significant events. In recent guidelines, RM is a Class I indication for device follow-up, and the Expert Consensus Statement endorses the use of RM to improve patient compliance. Many clinical studies including randomized clinical trials showed favorable outcomes with RM. This technology reduces costs, allows for early detection of arrhythmias, as well as lead to malfunctions. RM also lowers hospitalization rates, decreases inappropriate implantable cardioverter defibrillator shocks, and detects asymptomatic atrial fibrillation earlier than routine office visits. However, whether RM reduces mortality remains unclear. Prevention of heart failure exacerbation with early detection of surrogate markers of heart failure with RM has not been demonstrated using a single measure such as intrathoracic impedance. However, the use of multiple parameters has encouraging early results, showing improved detection of impending heart failure exacerbation.

Keywords: Cardiac implantable electronic devices, heart failure, home monitoring, implantable cardioverter defibrillator, pacemaker

How to cite this article:
John LA, Ishida Y, Gold MR. The role of remote monitoring for cardiac implantable electronic devices. Int J Heart Rhythm 2019;4:35-42

How to cite this URL:
John LA, Ishida Y, Gold MR. The role of remote monitoring for cardiac implantable electronic devices. Int J Heart Rhythm [serial online] 2019 [cited 2021 May 17];4:35-42. Available from: https://www.ijhronline.org/text.asp?2019/4/2/35/286765

  Introduction Top

Implantable pacemakers were developed more than 60 years ago, and implantable cardioverter defibrillators (ICDs) were approved in 1985. There have been many advances made over the ensuing decades of the engineering and features of these cardiac implantable electronic devices (CIEDs). One very important new technology was the development of remote monitoring (RM) of devices. First approved in 2001, RM was a niche feature available for only a small percentage of patients. Today, RM is available for all CIEDs across all major device manufacturers. RM systems allow for enhanced surveillance and earlier detection of clinically significant events. As supported by scientific data, RM improves patient outcomes, reduces hospitalizations, and decreases overall costs. This review article aims to highlight the rationale for the implementation of RM systems, with an emphasis on randomized clinical trials, outcome measures, resource utilization, and future directions.

  Database Search Strategy Top

A comprehensive literature search was performed on PubMed, Cochrane Central Registry, and Google Scholar using the search terms “remote monitoring and CIED”; “remote monitoring and pacemaker”; “remote monitoring and ICD”; “remote monitoring and defibrillator”; “remote monitoring and heart failure”; “intrathoracic impedance and monitoring”; and “atrial fibrillation, device, and stroke.”

  Logistics of Remote Monitoring Top

Currently, all major device manufacturers have RM technology, and each have variations of the different clinical parameters as depicted in [Table 1]. However, each manufacturer has their own proprietary system with unique features and important differences. For example, wireless transmission of data from devices may be automatic versus patient triggered, and the frequency of transmissions may be daily versus much less frequent.[1],[2] These differences need to be considered to understand the benefits of this technology. For example, automatic, daily transmissions are associated with higher probability of early detection of lead malfunctions when compared with periodic detection RM systems.[3]
Table 1: Cardiac implantable electronic device data

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Resource utilization

One of the primary benefits of RM is decreased resource utilization on health-care systems. In a US nationwide cohort study by Piccini et al.,[4] patients in the RM arm had an overall lower adjusted risk of all-cause hospitalization (adjusted hazard ratio [HR] = 0.82%; 95% confidence interval [CI]: 0.80–0.84; P < 0.001) and shorter mean length of hospitalization (5.3 days vs. 8.1 days; P < 0.0001) during follow-up.[4] In addition, there was a 30% reduction in hospitalization costs ($8720 mean cost per patient-year compared to $12,423 mean cost per patient-year).

RM also allows for more rapid detection of clinically significant events when compared to conventional follow-up among patients with CIEDs. This was well shown in the Lumos-T Safely Reduces Routine Office Device Follow-up (TRUST) trial, where the median time to evaluation for arrhythmic events was <2 days in the home monitoring group compared to 36 days in the conventional group (P < 0.001).[5] This study also demonstrated a reduction in total in-hospital device evaluations by 45% without affecting morbidity.[5] This finding was further emphasized in the Remote Follow-Up for ICD-Therapy in Patients Meeting MADIT II Criteria trial, which investigated less frequent in-office follow-up in primary prevention ICD patients under RM.[6] When compared to the 3-month follow-up interval, the 12-month interval resulted in a major reduction in the total number of in-office ICD follow-ups (1.60 vs. 3.85 per patient-year; P < 0.001).[6] Importantly, there was no significant difference in mortality, hospitalization rates, or hospitalization length during the 2-year observational period.[6] Similar results were observed among patients with pacemakers in the COMPArative follow-up schedule with home monitoring (COMPAS) trial[7] and in heart failure patients with ICDs in the Evolution of Management Strategies of Heart Failure Patients With Implantable Defibrillator (EVOLVO) study.[8] In COMPAS, the number of ambulatory visits was 56% lower in the RM group (P < 0.001), when compared to controls.[7] Furthermore, the RM group had fewer hospitalizations for atrial arrhythmias and strokes compared to the control group.[7] Although EVOLVO did not show significant annual cost savings for the health-care system, there was a significant reduction in patient costs in the remote arm compared to patients receiving standard in-person evaluations.[8]

In addition to the reduced number of in-office visits, the Clinical Evaluation of Remote Notification to Reduce Time to Clinical Decision (CONNECT) trial demonstrated that RM with automatic clinician alerts, when compared with standard face-to-face follow-ups, led to reduction in median clinical decision-making time in response to clinical events (22 vs. 4.6 days, P < 0.001).[7] There was also a decreased length of stay per cardiovascular hospitalization visit from 3.3 days in the RM arm compared with 4.0 days in the in-office arm (P < 0.002).[9]

Barriers to utilization of remote monitoring

In an observational cohort study, Varma et al.[10] in 2015 reported that only 47% of 269,471 patients with RM devices were actually utilizing RM; more concerning was that only 8% were still using RM 1 year after device implant. This low level of adherence occurred despite the Heart Rhythm Society Consensus Statement, which gives a Class I recommendation (LOE A) for the use of RM.[11] Bonnell and Mittal identified some of the barriers to implementation of RM, including technological barriers such as lack of cell phone compatibility in early systems, the inability of patients to understand the differences between RM and remote follow-up, inappropriate infrastructure in place for follow-up, and language barriers.[12] However, perhaps the single-most important factor contributing to the underutilization of remote patient monitoring (RPM) is the lack of enrollment into RPM systems.[13] The Patient-Related Determinants of ICD Remote Monitoring study showed that among the 39,158 patients with newly implanted RPM-capable devices, only 62% were RPM enrolled. Physician and institutional factors were associated with RPM enrollment, and enrollment varied greatly among institutions.[13]

In addition to institutional barriers, patient participation plays a crucial role in the implementation of RM. In a retrospective analysis, Rosenfeld et al.[14] found that younger age (≤40 years), female sex, wanded devices, and small clinic size were clinically important predictors of noncompliance (P < 0.01). These observations emphasize the need for strategies to improved compliance, which have been implemented with varying success. For instance, in-office setup of wireless pacemakers led to greater patient compliance and successful transmission in 91% of patients, as compared to 22%, in the home setup group (P < 0.0001).[2],[15] In addition, the 2015 Heart Rhythm Society Expert Consensus Statement endorses the use of RM patient agreement and/or contract to improve patient compliance.[2],[11]

  Outcomes Top

Many different study methodologies were employed in the study of RM [Table 2]. The very large databases of the manufacturers allow for “Big Data” analyses, which cannot be achieved with standard randomized clinical trials. In addition, prospective registries, as well as retrospective databases, were utilized.
Table 2: Summary of clinical trials regarding remote monitoring in the cardiac implantable electronic devices

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In 2009, the Pacemaker Remote Follow-up Evaluation and Review (PREFER) trial was the first study to show the earlier recognition of potentially important arrhythmias with RM.[16] A total of 897 pacemaker patients were randomized to follow-up with RM (remote arm) versus office visits and transtelephonic monitoring (TTM arm) to determine the time to first diagnosis of a clinically actionable event. Clinically actionable events were identified, on an average, 2 months earlier in the RM than in the TTM arm. The most frequent clinically actionable event reported was nonsustained ventricular tachycardia, followed by atrial tachyarrhythmia episodes >48 hours in duration. In 2019, the Safety and Efficiency of a Common and Simplified Protocol for Pacemaker and Defibrillator Surveillance based on Remote Monitoring only: a long-term randomized trial (RM-ALONE) showed that RM plus remote interrogation every 6 months proved safe and efficient in reducing hospital visits.[17] Another trial, Patient Perspective on Remote Monitoring of Cardiovascular Implantable Electronic Devices (REMOTE-CIED), showed that there was no difference between patient-reported health status and acceptance of ICD in patients receiving regular clinic visits versus RM.[18]


The ALTITUDE study showed the beneficial effects of RM on survival. This was a big data trial, which was a nonrandomized observational assessment of an industry database. It demonstrated a 50% reduction in mortality in ICD and cardiac resynchronization therapy-defibrillator (CRT-D) patients with remote follow-up on the network (n = 69,556), compared with follow-up in device clinic only (n = 116,222).[19] Subsequently, an even larger observational study with 269,471 patients demonstrated the association between RM and survival in a separate cohort of patients with pacemakers, ICDs, cardiac resynchronization therapy-pacemaker (CRT-P), and CRT-D devices. This study showed that the mortality benefit was larger with high adherence (>75%) to RM than with low adherence (<75%) and those without RM.[10]

Previously noted studies all used the RM system of a single manufacturer, so the generality of results is less clear. In contrast, the Clinical Efficacy of Remote Monitoring in the Management of Heart Failure (EFFECT) study was a prospective, nonrandomized, multicentric clinical trial of 987 patients with ICD/CRT-D implantation manufactured by multiple companies. This study showed that RM is associated with reduced death and cardiovascular hospitalizations.[20] These three large nonrandomized clinical studies laid the foundation for establishing the favorable outcomes of RM, helping to establish it as an important part of the clinical pathway for optimal care of patients with CIEDs.

Several randomized clinical trials (RCT) have reported less favorable results. A meta-analysis of nine RCTs found that RM did not improve all-cause mortality compared with conventional in-office follow-up.[21] Only the INfluence of home moniToring on mortality and morbidity in heart failure patients with IMpaired lEft ventricular function (IN-TIME) study has shown a significant reduction in all-cause mortality.[22] In this study, 664 patients were randomly assigned (333 to RM, 331 to standard care without RM). The mean ejection fraction was 26% with New York Heart Association (NYHA) functional Class II/III. At 1 year, RM was associated with a significant lower mortality compared to control (3.0% vs. 8.2%; hazard ratio [HR] = 0.36, 95% CI: 0.17–0.74; P = 0.004). A significant mortality reduction was also observed in a recent meta-analysis of IN-TIME,[22] the Effectiveness and Cost of ICDs Follow-up Schedule with Telecardiology (ECOST),[23] and TRUST.[5],[23] These three trials used the Biotronik system, which enabled daily monitoring transmission, whereas no mortality reduction was noted in an analysis of RCTs[24] that used less frequent transmission. Specifically, CONNECT,[9] EVOLVO,[25] and the MOnitoring Resynchronization dEvices and CARdiac patiEnts (MORE-CARE)[26] were analyzed in the latter study. In a more recent large observational study of 23,750 patients with CRT-D devices, the use of a quadripolar lead, compared to a bipolar lead (n = 23,570), was associated with a lower risk of death (HR = 0.77, 95% CI: 0.69–0.86, P < 0.001). RM remained an independent predictor of improved survival, regardless of left ventricle lead type (HR = 0.41, 95% CI: 0.36–0.45, P < 0.001).[27] It remains unclear if these differences in outcomes are due to differences in study size, frequency of transmission, RM system, or other unrecognized clinical factors such as patient compliance or physician response time.

Heart failure

As previously noted, RM can also be used to evaluate parameters associated with heart failure. The Diagnostic Outcome Trial in Heart Failure (DOT-HF) study assessed whether monitoring of device-based diagnostic tools including intrathoracic impedance would lead to a reduction in the morbidity or mortality compared with standard clinical assessment alone among patients with CRT-P or CRT-D devices. This diagnostic tool with an audible patient alert did not reduce the primary end point of all-cause mortality and HF hospitalization. Paradoxically, there were more HF hospitalizations (HR = 1.79, 95% CI: 1.08–2.95, P = 0.022) in the active arm, likely because of false-positive alerts.[28]

There are now two more recent randomized, multicentric trials that also failed to show a benefit of RM for detecting HF. In the remote management of heart failure using implantable electronic devices (REM-HF) trial,[29] patients had symptomatic HF (NYHA Class II-IV) with a CIED (ICD, CRT-D, and CRT-P) implant manufactured by Boston Scientific, Medtronic, and St. Jude Medical. This trial showed no differences with the use of RM in the composite primary end point of all-cause mortality or hospitalization (HR = 1.01, 95% CI: 0.87–1.18, P = 0.87). In the MORE-CARE trial,[30] patients with CRT-D devices with NYHA Class III/IV functional status and a left ventricular ejection fraction < 35% were randomized 1:1 to wireless RM group or to a control group. No significant difference was observed in the primary end point of a composite of all-cause mortality, and cardiovascular and device-related hospitalization was observed (HR = 1.02, 95% CI: 0.80–1.30, P = 0.89). The Contemporary Modalities in the Treatment of Heart Failure Registry (COMMIT-HF) study showed that RM reduced mortality in ICD/CRT-D patients, but not heart failure-related hospitalizations.[31]

As mentioned above, the usefulness of RM in patients with HF is questionable. However, these studies were heterogeneous in methodological quality, sample size, population, intervention, and control group care.[32] For instance, there were important difference in the characteristics of the enrolled population. The MORE-CARE study included patients with more advanced HF (NYHA Class III/IV), compared to patients enrolled in the IN-TIME trial (NYHA class II/III). As a result, 1-year mortality in the control arm of IN-TIME was 1.8-fold that observed in the control arm of MORE-CARE (8.7% vs. 4.8%).[32] Furthermore, in the IN-TIME study, RM management was standardized, and a multiparametric approach was used, whereas the MORE-CARE study managed the RM according to local clinical practice.[33]

Diagnostic parameter of heart failure

Intrathoracic impedance is the most widely studied parameter to predict HF. Increased lung water leads to decreased intrathoracic impedance, which, thus, is a marker of pulmonary congestion. In the Medtronic Impedance Diagnostics in Heart Failure Trial (MIDHeFT), 33 patients with NYHA Class III/IV were evaluated, the intrathoracic impedance had a high sensitivity of 77% for detecting hospitalization for fluid overload, with 1.5 false-positive detections per patient-year.[34] However, the Sensitivity of the InSync Sentry OptiVol feature for the prediction of Heart Failure (SENSE-HF) study with 501 patients[35] demonstrated a low sensitivity of 20.7% with a positive predictive value of 4.7% in the blinded validation phase. A post hoc analysis of the same study resulted in a sensitivity of 29.3% in the blinded phase. (J-)Monitoring of Fluid Status in Heart Failure Patients by Intrathoracic Impedance Measurement (HomeCARE-II) Study also assessed the thoracic impedance-based algorithm for the prediction of imminent cardiac decompensation.[36] The algorithm resulted in a sensitivity of 41.5% with 0.95 false positivity per patient-year. The authors concluded that overall performance in predicting imminent decompensation by monitoring thoracic impedance alone is limited due to its high inter-patient variability.

Given these results, several studies combined multiple parameters to assess the predictive value for heart failure events. The Program to Access and Review Trending Information and Evaluate Correlation to Symptoms in Patients With Heart Failure (PARTNERS-HF) was a prospective, multicentric observational study with CRT-D.[37] A combined HF device diagnostic algorithm was developed. The algorithm was considered positive if a patient had two of the following abnormal criteria during a 1-month period: long atrial fibrillation (AF) duration, rapid ventricular rate during AF, high (≥60) fluid index (calculated by thoracic impedance), low patient activity, high night heart rate or low heart rate variability, or notable device therapy (low CRT pacing or implantable cardioverter-defibrillator shocks), or if they only had a very high (≥100) fluid index. Patients with a positive combined HF device diagnostic had a 5.5-fold increased risk of HF hospitalization with pulmonary signs or symptoms within the next month (HR = 5.5, 95% CI: 3.4–8.8, P < 0.0001).

The Multisensor Chronic Evaluation in Ambulatory Heart Failure Patients (MultiSENSE) study assessed the multiple parameters related to HF worsening, which included heart sounds, thoracic impedance, respiration, heart rate, and activity. These parameters integrated into the HeartLogic index that predicted impending worsening HF events with 70% sensitivity and a median 34-day advance warning before an HF event at the nominal threshold configuration.[38] Furthermore, this index and alert algorithm were able to identify periods of 10-fold increased risk of worsening HF events. When used in conjunction with a baseline measure of N-terminal pro B-type natriuretic peptide (NT-proBNP), periods with a 50-fold increased risk of heart failure events were identified compared with the majority of low-risk time.[39]

Implantable cardioverter defibrillators discharge

Inappropriate ICD shocks impair patients' quality of life and possibly increase the risk of mortality. In the previously mentioned meta-analysis of nine RCTs, RM demonstrated a significant reduction in inappropriate shocks (odds ratio [OR] = 0.55, 95% CI: 0.38–0.80, P = 0.002).[21] RM has also been shown to prevent inappropriate shocks especially due to lead fracture. In a study on 115 patients with lead fracture, there was no significant difference between the control and RM groups in the occurrence of a first inappropriate shock (32.9% vs. 30.3%).[40] However, shocked patients in the RM group underwent significantly fewer inappropriate shocks with a mean of six shocks per patient than those in the control group with a mean of 18 shocks per patient (P = 0.03).

Dedicated noise alerts further reduce inappropriate shocks. In a study reported by Ploux et al.,[41] ICD lead failure and subsequent device interventions were prospectively collected in patients with and without a lead noise alert in their RM system. Inappropriate shocks were delivered in only one patient of each group (3%). The absence of a lead noise alert was associated with a 16-fold increase in the likelihood of initiating either a shock or ATP (OR = 16.0, 95% CI: 1.8–143.3, P = 0.01).

In a French registry of the subcutaneous ICD (S-ICD) (n = 69), during the average follow-up of approximately 1 year, 12% of the patients (n = 8) had events transmitted by the RM system. These events were related to nine ICD shocks and eight untreated events. ICD shocks comprised six appropriate and three inappropriate shocks. Among the transmitted events, 9 of 17 events (53%) led to interventions such as correction of bad compliance to medical treatment, pharmacological treatment modification, ICD reprogramming, and ventricular tachycardia ablation. The early detection of these events allowed physicians to reduce the number of further shocks and avoid adverse events.[42]

Atrial fibrillation and stroke

AF is an important cause of embolic stroke of undetermined source (ESUS). The average frequency of the ESUS of ischemic stroke has been reported to be 17% (ranged from 9% to 25%).[43] CIED and implantable loop recorders can detect subclinical episode of AF, which were associated with an increased risk of thromboembolic event.[44],[45],[46],[47] In a sub-study of the HomeGuide study,[48] 1650 patients with CIEDs and median CHA2 DS2-VASC score of 3.0 were followed remotely for up to 4 years. During the period, 93% of AF episodes were detected remotely, 66% of whom had no history of AF. Eighty-five percent of the episodes resulted in a medical intervention. The median response time was 1 (0–6) day for remotely detected episodes and 33 (14–121) days for episodes detected in clinic (P < 0.0001). It is well established that RM detects asymptomatic AF earlier, which may be beneficial in lowering ischemic stroke rates.

  Future Directions Top

RM continues to evolve rapidly, although there are still limitations of systems. There are significant differences between the time to detection and acknowledgment of clinically relevant events.[49] In one recent study, it was shown that the proportion of events acknowledged within 24 h varied between 18% and 72% among manufacturers, and the median times for alerts varied between 18 and 222 h.[49] More rapid response times should be a goal of technologic advancements of these systems.

Several app-based RM technologies have been developed for both implantable loop recorders and pacing devices. In a recent study of pacemaker patients who were provided with an app-based monitor, 84.4% were able to activate the RM platform.[50] Furthermore, 89.5% of patients who activated app-based RM remained adherent and sent another transmission within 1 year after activation. There were statistically different activation rates noted among the different age groups, with the highest activation rates in the 60–69-year-old group (87.7%).[50] The lowest rates of activation was noted in the 78+-year-old group (79.0%). With regard to RM adherence, rates were also highest in the 60–69-year-old group (91.4%) and lowest in the 18–59-year-old group (87.7%) (P < 0.001).[50] Although there was a statistically significant difference noted among age groups, from a clinical standpoint, these differences were small.[50] For these reasons, it would be useful to make apps more universally available for facilitating RM use. Finally, optimizing algorithms for detecting heart failure and lead failure events will help to maximize the benefit of RM and reduce false-positive alerts. This will very likely entail the use of multiple parameters to improve sensitivity and specificity.

  Conclusion Top

RM is now available for almost every CIED. RM is a Class I indication for device follow-up and should be implemented whenever possible. The use of RM reduces costs and allows for early detection of arrhythmias. This technology lowers hospitalization rates, decreases inappropriate ICD shock, and detects asymptomatic AF earlier. Whether RM reduces mortality remains unclear. The use of multiple parameters has encouraging early results that show improved detection of impending heart failure exacerbation.

Financial support and sponsorship


Conflicts of interest

There are no conflicts of interest.

  References Top

Ganeshan R, Enriquez AD, Freeman JV. Remote monitoring of implantable cardiac devices: Current state and future directions. Curr Opin Cardiol 2018;33:20-30.  Back to cited text no. 1
Zeitler EP, Piccini JP. Remote monitoring of cardiac implantable electronic devices (CIED). Trends Cardiovasc Med 2016;26:568-77.  Back to cited text no. 2
de Ruvo E, Sciarra L, Martino AM, Rebecchi M, Iulianella RV, Sebastiani F, et al. A prospective comparison of remote monitoring systems in implantable cardiac defibrillators: Potential effects of frequency of transmissions. J Interv Card Electrophysiol 2016;45:81-90.  Back to cited text no. 3
Piccini JP, Mittal S, Snell J, Prillinger JB, Dalal N, Varma N. Impact of remote monitoring on clinical events and associated health care utilization: A nationwide assessment. Heart Rhythm 2016;13:2279-86.  Back to cited text no. 4
Varma N, Epstein AE, Irimpen A, Schweikert R, Love C; TRUST Investigators. Efficacy and safety of automatic remote monitoring for implantable cardioverter-defibrillator follow-up: The Lumos-T Safely Reduces Routine Office Device Follow-up (TRUST) trial. Circulation 2010;122:325-32.  Back to cited text no. 5
Hindricks G, Elsner C, Piorkowski C, Taborsky M, Geller JC, Schumacher B, et al. Quarterly vs. yearly clinical follow-up of remotely monitored recipients of prophylactic implantable cardioverter-defibrillators: Results of the REFORM trial. Eur Heart J 2014;35:98-105.  Back to cited text no. 6
Mabo P, Victor F, Bazin P, Ahres S, Babuty D, Da Costa A, et al. A randomized trial of long-term remote monitoring of pacemaker recipients (the COMPAS trial). Eur Heart J 2012;33:1105-11.  Back to cited text no. 7
Zanaboni P, Landolina M, Marzegalli M, Lunati M, Perego GB, Guenzati G, et al. Cost-utility analysis of the EVOLVO study on remote monitoring for heart failure patients with implantable defibrillators: Randomized controlled trial. J Med Internet Res 2013;15:e106.  Back to cited text no. 8
Crossley GH, Boyle A, Vitense H, Chang Y, Mead RH; CONNECT Investigators. The CONNECT (Clinical Evaluation of Remote Notification to Reduce Time to Clinical Decision) trial: The value of wireless remote monitoring with automatic clinician alerts. J Am Coll Cardiol 2011;57:1181-9.  Back to cited text no. 9
Varma N, Piccini JP, Snell J, Fischer A, Dalal N, Mittal S. The relationship between level of adherence to automatic wireless remote monitoring and survival in pacemaker and defibrillator patients. J Am Coll Cardiol 2015;65:2601-10.  Back to cited text no. 10
Slotwiner D, Varma N, Akar JG, Annas G, Beardsall M, Fogel RI, et al. HRS Expert Consensus Statement on remote interrogation and monitoring for cardiovascular implantable electronic devices. Heart Rhythm 2015;12:e69-100.  Back to cited text no. 11
Bonnell S, Mittal S. Clinical guidelines for remote monitoring. Card Electrophysiol Clinics 2013;5:283-91.  Back to cited text no. 12
Akar JG, Bao H, Jones P, Wang Y, Chaudhry SI, Varosy P, et al. Use of remote monitoring of newly implanted cardioverter-defibrillators: Insights from the patient related determinants of ICD remote monitoring (PREDICT RM) study. Circulation 2013;128:2372-83.  Back to cited text no. 13
Rosenfeld LE, Patel AS, Ajmani VB, Holbrook RW, Brand TA. Compliance with remote monitoring of ICDS/CRTDS in a real-world population. Pacing Clin Electrophysiol 2014;37:820-7.  Back to cited text no. 14
Ren X, Apostolakos R, Vo T, Shaw R, Shields K, Banki N, et al. Remote monitoring of implantable pacemakers: In office set up significantly improves successful data transmission. Clin Cardiol 2013;36:634-7.  Back to cited text no. 15
Crossley GH, Chen J, Choucair W, Cohen TJ, Gohn DC, Johnson WB, et al. Clinical benefits of remote versus transtelephonic monitoring of implanted pacemakers. J Am Coll Cardiol 2009;54:2012-9.  Back to cited text no. 16
Garcia-Fernandez F, Osca A, Romero R, Fernandez L, Larrazabal J, Martinez F, et al. Safety and efficiency of common and simplified protocol for pacemaker and defibrillator surveillance based on remote monitoring only: A long-term randomized trial (RM-ALONE). Eur Heart J 2019;23:1837-46.  Back to cited text no. 17
Versteeg H, Timmermans I, Widdershoven J, Kimman G, Prevot S, Rauwolf T et al. Effect of remote monitoring on patient-reported outcomes in European heart failure patients with an implantable cardioverter-defibrillator: Primary results of the REMOTE-CIED randomized trial. Eurospace 2019;9:1360-8.  Back to cited text no. 18
Saxon L, Hayes D, Gilliam F, Heidenreich P, Day J, Seth M, et al. Long-term outcome after ICD and CRT implantation and influence of remote device follow-up: The ALTITUDE survival study. Circulation 2010;122:2359-67.   Back to cited text no. 19
Simone A, Leoni L, Luzi M, Amellone C, Stabile G, Rocca V, et al. Remote monitoring improves outcome after ICD implantation: the clinical efficacy in the management of heart failure (EFFECT) study. 2015;17:1267-75.   Back to cited text no. 20
Parthiban N, Esterman A, Mahajan R, Twomey D, Pathak R, Lau D, et al. Remote Monitoring of Implantable Cardioverter-Defibrillators: A Systematic Review and Meta-Analysis of Clinical Outcomes. J Am Coll Cardiol 2015;65:2591-600.   Back to cited text no. 21
Hindricks G, Taborsky M, Glikson M, Heinrich U, Schumacher B, Katz A, et al. Implant-based multiparameter telemonitoring of patients with heart failure (IN-TIME): A randomised controlled trial. Lancet 2014;384:583-90.   Back to cited text no. 22
Hindricks G, Varma N, Kacet S, Lewalter T, Søgaard P, Guédon-Moreau L, et al. Daily remote monitoring of implantable cardioverter-defibrillators: Insights from the pooled patient-level data from three randomized controlled trials (IN-TIME, ECOST, TRUST). Eur Heart J 2017;38:1749-1755.   Back to cited text no. 23
Al-Khatib S, Piccini J, Knight D, Stewart M, Clapp-Channing N, Sanders G. Remote monitoring of implantable cardioverter defibrillators versus quarterly device interrogations in clinic: Results from a randomized pilot clinical trial. J Cardiovasc Electrophysiol 2010;21:545-50.   Back to cited text no. 24
Landolina M, Perego G, Lunati M, Curnis A, Guenzati G, Vicentini A, et al. Remote monitoring reduces healthcare use and improves quality of care in heart failure patients with implantable defibrillators: The evolution of management strategies of heart failure patients with implantable defibrillators (EVOLVO) study. Circulation 2012;125:2985-2992.   Back to cited text no. 25
Boriani G, DaCosta A, Ricci R, Quesada A, Favale S, Iacopino S, et al. The monitoring resynchronization devices and cardiac patients (MORE-CARE) randomized controlled trial: Phase 1 results on dynamics of early intervention with remote monitoring. J Med Internet Res 2013;15:e167.  Back to cited text no. 26
Turakhia M, Cao M, Fischer A, Nabutovsky Y, Sloman L, Dalal N, et al. Reduced morality associated with quadripolar compared to bipolar left ventricular leads in cardiac resynchronization therapy. J Am Coll Cardiol EP 2016;2:426-33.  Back to cited text no. 27
Braunschweig F, Ford I, Conraads V, Cowie M, Jondeau G, Kautzner J, et al. Can monitoring of intrathoracic impedance reduce morbidity and morality in patients with chronic heart failure? Rationale and design of the Diagnostic Outcome Trial in Heart Failure (DOT-HF). Eur J Heart Fail 2008;10:907-16.  Back to cited text no. 28
Morgan J, Kitt S, Gill J, McComb J, Ng G, Raftery J et al. Remote management of heart failure using implantable electronic devices. Eur Heart J 2017;38:2352-60.   Back to cited text no. 29
Boriani G, DaCosta A, Quesada A, Ricci R, Favale S, Boscolo G, et al. Effects of remote monitoring on clinical outcomes and use of healthcare resources in heart failure patients with biventricular defibrillators: results of the MORE-CARE multicentre randomized controlled trial. Eur J Heart Fail 2017;19:416-25.   Back to cited text no. 30
Kurek A, Tajstra M, Gadula-Gacek E, Buchta P, Skryzpek M, Pyka L et al. Impact of remote monitoring on long-term prognosis in heart failure patients in a real-world cohort: results from all-comers COMMIT-HF trial. J Cardiovasc Electrophysiol 2017;4:425-31.   Back to cited text no. 31
Hawkins N, Virani S, Sperrin M, Buchan I, Mcmurray J, Krahn A. Predicting heart failure decompensation using cardiac implantable electronic devices: A review of practices and challenges. Eur J Heart Fail 2016;18:977-986.   Back to cited text no. 32
Lucà F, Cipolletta L, Di Fusco SA, Iorio A, Pozzi A, Rao CM, et al. Remote monitoring: Doomed to let down or an attractive promise? Int J Cardiol Heart Vasc 2019;24:100380.   Back to cited text no. 33
Yu C, Wang L, Chau E, Chan R, Kong S, Tang M, et al. Intrathoracic Impedance Monitoring in Patients With Heart Failure Correlation With Fluid Status and Feasibility of Early Warning Preceding Hospitalization. Circulation 2005;112:841-8.   Back to cited text no. 34
Conraads V, Tavazzi L, Santini M, Oliva F, Gerritse B, Yu C, et al. Sensitivity and positive predictive value of implantable intrathoracic impedance monitoring as a predictor of heart failure hospitalizations: the SENSE-HF trial. Eur Heart J 2011;32:2266-73.   Back to cited text no. 35
Maier S, Paule S, Jung W, Koller M, Ventura R, Quesada A, et al. Evaluation of thoracic impedance trends for implant-based remote monitoring in heart failure patients - Results from the (J-)HomeCARE-II Study. J Electrocardiol 2019;53:100-8.   Back to cited text no. 36
Whellan D, Ousdigian K, Al-Khatib S, Pu W, Sarkar S, Porter C, et al. Combined heart failure device diagnostics identify patients at higher risk of subsequent heart failure hospitalizations. results from PARTNERS HF (Program to Access and Review Trending Information and Evaluate Correlation to Symptoms in Patients With Heart Failure) study. J Am Coll Cardiol 2010;55:1803-10.   Back to cited text no. 37
Boehmer J, Hariharan R, Devecchi F, Smith A, Molon G, Capucci A, et al. A Multisensor Algorithm Predicts Heart Failure Events in Patients With Implanted Devices: Results From the MultiSENSE Study. JACC Heart Fail 2017;5:216-25.   Back to cited text no. 38
Gardner R, Singh J, Stancak B, Nair D, Cao M, Schulze C, et al. HeartLogic multisensor algorithm identifies patients during periods of significantly increased risk of heart failure events: Results from the MultiSENSE Study. Circ Hear Fail 2018;11:1-10.   Back to cited text no. 39
Souissi Z, Guédon-Moreau L, Boulé S, Kouakam C, Finat L, Marquie C, et al. Impact of remote monitoring on reducing the burden of inappropriate shocks related to implantable cardioverter-defibrillator lead fractures: Insights from a French single-centre registry. Europace 2016;18:820-7.   Back to cited text no. 40
Ploux S, Swerdlow C, Strik M, Welte N, Klotz N, Ritter P, et al. Towards eradication of inappropriate therapies for ICD lead failure by combining comprehensive remote monitoring and lead noise alerts. J Cardiovasc Electrophysiol 2018;29:1125-34.   Back to cited text no. 41
Ninni S, Delahaye C, Klein C, Marquie C, Klug D, Lacroix D, et al. A report on the impace of remote monitoring in patients with S-ICD: Insights from a prospectice registry. Pacing Clin Electrophysiol 2019;42:349-55.  Back to cited text no. 42
Hart R, Catanese L, Perera K, Ntaios G, Connolly S. Embolic stroke of undetermined source: a systematic review and clinical update. Stroke 2017;48:867-72.   Back to cited text no. 43
Glotzer T, Daoud E, Wyse D, Singer D, Ezekowitz M, Hilker C, et al. The relationship between daily atrial tachyarrhythmia burden from implantable device diagnostics and stroke risk. Circ Arrhythm Electrophysiol 2009;2:474-80.   Back to cited text no. 44
Healey J, Connolly S, Gold M, Carsten I, VanGelder I, Capucci A, et al. Subclinical atrial fibrillation and the risk of stroke. N Engl J Med 2012;366:120-9.   Back to cited text no. 45
Van Gelder I, Healey J, Crijns H, Wang J, Hohnloser S, Gold M, et al. Duration of device-detected subclinical atrial fibrillation and occurrence of stroke in ASSERT. Eur Heart J 2017;38:1339-44.   Back to cited text no. 46
Sanna T, Diener HC, Passman RS, Di Lazzaro V, Bernstein RA, Morillo CA, et al. Cryptogenic stroke and underlying atrial fibrillation. N Engl J Med 2014;370:2478-86.  Back to cited text no. 47
Ricci RP, Vaccari D, Morichelli L, Zanotto G, Calò L, D'Onofrio A, et al. Stroke incidence in patients with cardiac implantable electronic devices remotely controlled with automatic alerts of atrial fibrillation. A sub-analysis of the HomeGuide study. Int J Cardiol 2016;219:251-6.  Back to cited text no. 48
Söth-Hansen M, Witt CT, Rasmussen M, Kristensen J, Gerdes C, Nielsen JC. Time until diagnosis of clinical events with different remote monitoring systems in implantable cardioverter-defibrillator patients. Heart Rhythm 2018;15:1648-54.  Back to cited text no. 49
Tarakji KG, Vives CA, Patel AS, Fagan DH, Sims JJ, Varma N. Success of pacemaker remote monitoring using app-based technology: Does patient age matter? Pacing Clin Electrophysiol 2018;41:1329-35.  Back to cited text no. 50


  [Table 1], [Table 2]


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