Remote monitoring: Doomed to let down or an attractive promise?

Abstract

Device interrogation and management are time consuming, representing a relevant burden for pacing centers. In several situations, patients' management requires additional follow up visits. Remote Monitoring (RM) allows an optimal recall management and a rapid diagnosis of device or lead failure, without the need of additional in office visits. Further it allows a significant delay reduction between the adverse event and the reaction to the alarm, shortening the time needed to make a clinical decision. A role in risk-predicting patient-related outcomes has also been shown. RM permits detection of the arrhythmia from 1 to 5 months in advance compared to in-office visits. Importantly, by using specific algorithms with multiparametric analysis, RM has been studied as a potential instrument to identify early patients on risk of worsening HF using specific algorithms. Although the use of RM in HF setting remains controversial, it has been proposed to improve HF clinical outcomes and survival in clinical trials. In this sense, RM success could require a standardization of process within a management model, that may involve different health care professionals. In this review, we examine recent advances of RM providing an update of this tool through different clinical scenarios.

Keywords: AHRE, Atrial High Rate Episodes; ARTESIA, Apixaban for the Reduction of Thrombo-Embolism in Patients With Device-Detected Sub-Clinical Atrial Fibrillation; ASSERT, ASymptomatic atrial fibrillation and Stroke Evaluation in pacemaker patients and atrial fibrillation Reduction atrial pacing Trial; Atrial fibrillation; CHAMPION, CardioMEMS Heart Sensor Allows Monitoring of Pressure to Improve Outcomes in NYHA Class III Heart Failure Patients; CIED, Cardiac Implantable Electronic Devices; COMPAS, COMPArative follow-up Schedule with home monitoring; CONNECT, Clinical Evaluation of Remote Notification to Reduce Time to Clinical Decision; CRT, Cardiac Resynchronization Therapy; ECOST, Effectiveness and Cost of ICDs Follow-up Schedule with Telecardiology; EHRA, European Heart Rhythm Association; EVOLVO, Evolution of Management Strategies of Heart Failure Patients With Implantable Defibrillators; Heart failure; ICD, Implantable Cardioverter Defibrillator; IMPACT, Combined Use of BIOTRONIK Home Monitoring and Predefined Anticoagulation to Reduce Stroke Risk; IN-TIME, Influence of Home Monitoring on the Clinical Status of Heart Failure Patients With an Impaired Left Ventricular Function; ISHNE, International Society for Holter and Noninvasive Electrocardiology; Implantable devices; MORE-CARE, MOnitoring Resynchronization dEvices and CARdiac patiEnts; MULTISENSE HF, Multisensor Chronic Evaluation in Ambulatory Heart Failure Patients; MoniC, Model Project Monitor Centre; NOAH, Non–vitamin K antagonist Oral anticoagulants in patients with Atrial High rate episodes; NYHA, New York Heart Association; OPTILINK-HF, Optimization of Heart Failure Management Using Medtronic OptiVol Fluid Status Monitoring and CareLink Network; PARTNERS HF, Program to Access and Review Trending Information and Evaluate Correlation to Symptoms in Patients With Heart Failure; PMK, Pacemaker; REFORM Trial, Remote Follow-Up for ICD-Therapy in Patients Meeting MADIT II Criteria; RM, Remote Monitoring; RM-HF, REmote Monitoring: an evaluation of implantable devices for management of Heart Failure patients; Remote telemonitoring; SELENE, Selection of potential predictors of worsening Heart Failure; TARIFF, Evaluation Registry for Remote Follow-up; TRUST, Lumos-T Safely Reduces Routine Office Device Follow-up.

Fig. 1

A: Forest Plot of the comparison between RM and no RM for mortality. This shows a reduction in mortality of risk ratio around 16% in favour of RM. (I² = 48.7%) The low I square shows a low-moderate heterogeneity of the studies included in the paper (see Statistics section). B: Funnel Plot of the comparison between RM and no RM for mortality. Egger's Intercept = 1.86; tau = 0.53; p = 0.62; Begg and Mazumdar rank correlation tau = 0.4; p = 0.46). Both tests were not significant hence we can assume a low bias of the study (see Statistics section).

Fig. 2

A: Forest Plot of the comparison between RM and no RM for hospitalizations. The hazard risk of hospitalization in patients not undergoing RM was 15% higher as illustrated. (I² = 48.3). The low I square shows a low-moderate heterogeneity of the studies included in the paper (see Statistics section). B: Funnel Plot of the comparison between RM and no RM for hospitalizations. Egger's Intercept = 0.44; tau 0.1; p = 0.85; Begg and Mazumdar rank correlation tau =0.06; p = 0.85. Both tests were not significant hence we can assume a low bias of the study (see Statistics section).