Using technology to improve reconnection to remote monitoring in cardiac implantable electronic device patients.

Background: Remote monitoring (RM) of cardiac implantable electronic device (CIED) patients is now considered standard of care. However, a fundamental requirement of RM is continuous connectivity between the patient's implanted device and the CIED manufacturer's central server. This study examined the rate of RM disconnections in CIED recipients and the impact of short message service (SMS) to facilitate reconnections. Methods: Using a platform that collects RM data from CIED manufacturers, we retrospectively examined the disconnection and reconnection events in 6085 patients from 20 medical centers. Each medical center reported their usual practice regarding RM disconnections, which consisted of either an automatic SMS from the platform to patients who were disconnected for 2 weeks or the standard of care (SC) of a phone call to patients. Results: During a 1-year period, 43% of patients had at least 1 disconnection. Half of these patients experienced multiple disconnections. The use of SMS reduced the time to reconnection by 43% in comparison to SC. The median time to reconnect a disconnected patient was 11.0 [3.2, 29.0] days for SC vs 6.3 [1.3, 22.0] days for SMS (P < .0001). Furthermore, there was a high rate of reconnections within the first 48 hours of the SMS message, which was nearly double that in the SC arm. Conclusion: This study demonstrates the feasibility of an automatic system to deliver an SMS to patients with a disconnected CIED to facilitate early reconnection to RM.

Filtering of remote monitoring alerts transmitted by cardiac implantable electronic devices and reclassification of atrial fibrillation events by a new algorithm.

Background: Cardiac implantable electronic devices (CIEDs) are an important means of atrial fibrillation (AF) detection. However, the AF burden measurements and notifications transmitted by CIEDs are not directly related to the clinical classification of paroxysmal, persistent, or permanent AF. Moreover, AF alerts are the most frequent form of notification, imposing a time-consuming review on caregivers. Objective: The purpose of this study was to compare the incidence of standard AF burden-related notifications in remotely monitored (RM) patients with the incidence of events detected after filtering by a new proprietary algorithm implementing the standard European Society of Cardiology classification of AF. Methods: Between 2017 and 2022, all RM patients with daily AF burden measurements available for ≥30 days and ≥1 AF burden-related alerts were enrolled at 68 medical centers. The incidence of CIED-transmitted alerts was compared to that of AF episodes detected by a new proprietary algorithm and classified as "first recorded episode of AF", "paroxysmal AF", "increased paroxysmal AF", "persistent AF", or "end of persistent AF back to paroxysmal AF or back to sinus rhythm." Results: Between January 2017 and September 2022, this retrospective study analyzed data from 4162 recipients of an Abbott, Biotronik, Boston Scientific, or Medtronic CIED, RM over mean follow-up of 605 ± 386 days. The algorithm broke down 67,883 AF burden-related alerts into 9728 (14.3%) clinically relevant AF events. Conclusion: A new AF alert algorithm successfully identified clinically significant AF events in RM CIED recipients and would markedly limit the total number of transmitted alerts that require review by caregivers.

Improved diagnostic performance of insertable cardiac monitors by an artificial intelligence-based algorithm.

AIMS: The increasing use of insertable cardiac monitors (ICM) produces a high rate of false positive (FP) diagnoses. Their verification results in a high workload for caregivers. We evaluated the performance of an artificial intelligence (AI)-based ILR-ECG Analyzer™ (ILR-ECG-A). This machine-learning algorithm reclassifies ICM-transmitted events to minimize the rate of FP diagnoses, while preserving device sensitivity. METHODS AND RESULTS: We selected 546 recipients of ICM followed by the Implicity™ monitoring platform. To avoid clusterization, a single episode per ICM abnormal diagnosis (e.g. asystole, bradycardia, atrial tachycardia (AT)/atrial fibrillation (AF), ventricular tachycardia, artefact) was selected per patient, and analyzed by the ILR-ECG-A, applying the same diagnoses as the ICM. All episodes were reviewed by an adjudication committee (AC) and the results were compared. Among 879 episodes classified as abnormal by the ICM, 80 (9.1%) were adjudicated as 'Artefacts', 283 (32.2%) as FP, and 516 (58.7%) as 'abnormal' by the AC. The algorithm reclassified 215 of the 283 FP as normal (76.0%), and confirmed 509 of the 516 episodes as abnormal (98.6%). Seven undiagnosed false negatives were adjudicated as AT or non-specific abnormality. The overall diagnostic specificity was 76.0% and the sensitivity was 98.6%. CONCLUSION: The new AI-based ILR-ECG-A lowered the rate of FP ICM diagnoses significantly while retaining a > 98% sensitivity. This will likely alleviate considerably the clinical burden represented by the review of ICM events.

Closed-Loop Vagus Nerve Stimulation Based on State Transition Models.

OBJECTIVE: Vagus nerve stimulation (VNS) is a potential therapeutic approach in a number of clinical applications. Although VNS is commonly delivered in an open-loop approach, it is now recognized that closed-loop stimulation may be necessary to optimize the therapy. In this paper, we propose an original generic closed-loop control system that can be readily integrated into an implantable device and allows for the adaptive modulation of multiple VNS parameters. METHODS: The proposed control method consists of a state transition model (STM), in which each state represents a set of VNS parameters, and a state transition algorithm that optimally selects the best STM state, minimizing the error between an observed physiological variable and a given target value. The proposed method has been integrated into a real-time adaptive VNS prototype system and has been applied here to the regulation of the instantaneous heart rate, working synchronously with cardiac cycles. A quantitative performance evaluation is performed on seven sheep by computing classical control performance indicators. A comparison with a proportional-integral (PI) controller is also performed. RESULTS: The STM controller presents a median mean square error, overshoot, and settling time, respectively, equal to 622.21 ms , 72.8%, and 7.5 beats. CONCLUSION: The proposed control method yields satisfactory accuracy and time response, while presenting a number of benefits over classical PI controllers. It represents a feasible approach for multiparametric VNS control on implantable devices. SIGNIFICANCE: Closed-loop multiparametric stimulation may improve response and minimize side effects on current pathologies treated by VNS.

A novel controller based on state-transition models for closed-loop vagus nerve stimulation: Application to heart rate regulation.

Vagus nerve stimulation (VNS) is an established adjunctive therapy for pharmacologically refractory epilepsy and depression and is currently in active clinical research for other applications. In current clinical studies, VNS is delivered in an open-loop approach, where VNS parameters are defined during a manual titration phase. However, the physiological response to a given VNS configuration shows significant inter and intra-patient variability and may significantly evolve through time. VNS closed-loop approaches, allowing for the optimization of the therapy in an adaptive manner, may be necessary to improve efficacy while reducing side effects. This paper proposes a generic, closed-loop control VNS system that is able to optimize a number of VNS parameters in an adaptive fashion, in order to keep a control variable within a specified range. Although the proposed control method is completely generic, an example application using the cardiac beat to beat interval (RR) as control variable will be developed in this paper. The proposed controller is based on a state transition model (STM) that can be configured using a partially or a fully-connected architecture, different model orders and different state-transition algorithms. The controller is applied to the adaptive regulation of heart rate and evaluated on 6 sheep, for 13 different targets, using partially-connected STM with 10 states. Also, partially and fully-connected STM defined by 30 states were applied to 7 other sheep for the same 10 targets. Results illustrate the interest of the proposed fully-connected STM and the feasibility of integrating this control system into an implantable neuromodulator.

Sensitivity Analysis of Vagus Nerve Stimulation Parameters on Acute Cardiac Autonomic Responses: Chronotropic, Inotropic and Dromotropic Effects.

Although the therapeutic effects of Vagus Nerve Stimulation (VNS) have been recognized in pre-clinical and pilot clinical studies, the effect of different stimulation configurations on the cardiovascular response is still an open question, especially in the case of VNS delivered synchronously with cardiac activity. In this paper, we propose a formal mathematical methodology to analyze the acute cardiac response to different VNS configurations, jointly considering the chronotropic, dromotropic and inotropic cardiac effects. A latin hypercube sampling method was chosen to design a uniform experimental plan, composed of 75 different VNS configurations, with different values for the main parameters (current amplitude, number of delivered pulses, pulse width, interpulse period and the delay between the detected cardiac event and VNS onset). These VNS configurations were applied to 6 healthy, anesthetized sheep, while acquiring the associated cardiovascular response. Unobserved VNS configurations were estimated using a Gaussian process regression (GPR) model. In order to quantitatively analyze the effect of each parameter and their combinations on the cardiac response, the Sobol sensitivity method was applied to the obtained GPR model and inter-individual sensitivity markers were estimated using a bootstrap approach. Results highlight the dominant effect of pulse current, pulse width and number of pulses, which explain respectively 49.4%, 19.7% and 6.0% of the mean global cardiovascular variability provoked by VNS. More interestingly, results also quantify the effect of the interactions between VNS parameters. In particular, the interactions between current and pulse width provoke higher cardiac effects than the changes on the number of pulses alone (between 6 and 25% of the variability). Although the sensitivity of individual VNS parameters seems similar for chronotropic, dromotropic and inotropic responses, the interacting effects of VNS parameters provoke significantly different cardiac responses, showing the feasibility of a parameter-based functional selectivity. These results are of primary importance for the optimal, subject-specific definition of VNS parameters for a given therapy and may lead to new closed-loop methods allowing for the optimal adaptation of VNS therapy through time.

Vagus nerve stimulation: state of the art of stimulation and recording strategies to address autonomic function neuromodulation.

OBJECTIVE: Neural signals along the vagus nerve (VN) drive many somatic and autonomic functions. The clinical interest of VN stimulation (VNS) is thus potentially huge and has already been demonstrated in epilepsy. However, side effects are often elicited, in addition to the targeted neuromodulation. APPROACH: This review examines the state of the art of VNS applied to two emerging modulations of autonomic function: heart failure and obesity, especially morbid obesity. MAIN RESULTS: We report that VNS may benefit from improved stimulation delivery using very advanced technologies. However, most of the results from fundamental animal studies still need to be demonstrated in humans.

Influence of Vagus Nerve Stimulation parameters on chronotropism and inotropism in heart failure.

Vagus Nerve Stimulation (VNS) has been shown to be useful in heart failure patients, including antiarrhythmic effects, improvement of cardiac function and reduction of the mortality. However, the optimal configuration of VNS can be a difficult task, since there are several adjustable parameters, such as current amplitude (mA), pulse width (ms), burst frequency (Hz), number of pulses and, in the case of cardiac-triggered VNS, the delay (ms) between the R-wave and the beginning of the stimulation. The objective of this paper is to analyse the effect of these parameters, and their interaction, on the chronotropic and inotropic responses to vagal stimulation. 306 VNS sequences were tested on 12 sheep with induced heart failure. Autonomic markers of the chronotropic (changes in RR interval) and inotropic (changes in dP/dtmax) effects were extracted from the observed data. In order to analyse the influence of stimulation parameters on these markers, a sensitivity analysis method was applied. Results illustrate the strong interaction between the delay and the others parameters. The number of pulses, the current and the frequency seem to be particularly influent on chronotropism and inotropism although the effect of the frequency is highly non-linear or it depends on other parameters.

On-off closed-loop control of vagus nerve stimulation for the adaptation of heart rate.

Vagus nerve stimulation (VNS) is a potential therapeutic approach in a number of clinical applications. Although VNS is commonly delivered in an open-loop approach, it is now recognized that closed-loop approaches may be necessary to optimize the therapy and minimize side effects of neuro-stimulation devices. In this paper, we describe a prototype system for real-time control of the instantaneous heart rate, working synchronously with the heart period. As a first step, an on-off control method has been integrated. The system is evaluated on one sheep with induced heart failure, showing the interest of the proposed approach.

Comparison of the cardiopulmonary response to exercise in recipients of dual sensor DDDR pacemakers Versus a Healthy control group.

The authors previously have shown in healthy subjects that age related loss of muscular strength did not alter the chronotropic response during treadmill exercise, whether with sudden onset of effort, as in the chronotropic assessment exercise protocol (CAEP) or more gradual effort as in the Harbor exercise protocol. This study was performed to verify that in patients suffering from chronotropic insufficiency, and in absence of other effort-limiting disorders, "physiologic" pacing enables a cardiorespiratory response comparable to that of age-matched healthy subjects. Furthermore, the aim of the study was to confirm that the response of a new dual sensor-based pacing system was properly adapted to the metabolic demand, whether during CAEP or during Harbor test, by subjecting patients to both protocols. All study participants were able to undergo treadmill exercise testing, had normal cardiopulmonary function tests at rest, and no cardiac, muscular, or pulmonary disease. A healthy group (control) included 16 subjects (mean age 70.4 +/- 3.9 years), and the test group (pacemaker [PM] included 9 subjects (mean age 67.1 +/- 10.8 years) permanently paced for isolated chronotropic insufficiency with a dual sensor pacing system. All subjects underwent CAEP and Harbor tests with measurements of gas exchange, 24 hours apart, in randomized order. All subjects reached an appropriate level of exercise, as expressed by mean lactate plasma concentrations, which were slightly higher in the control than the PM group during CAEP (4.9 +/- 1.9 vs 3.7 +/- 1.9 mmol/L, NS) and Harbor (5.3 +/- 1.9 vs. 3.8 +/- 1.8 mmol/L, P < 0.05) tests. No statistical difference was observed in VO2 and VE at peak exercise between the two groups during either test. In the PM group, heart rate at peak exercise and metabolic reserve slope were higher during the CAEP than the Harbor protocol. These two measurements were significantly lower than in the control group. The PM group also had lower plasma lactate concentrations and dyspnea/fatigue scores. The Harbor test seems less suitable than the CAEP test to study the chronotropic response of pacemakers with dual sensors during exercise. A high performance of the new dual sensor-based pulse generator was confirmed in this physically fit patient population, whose peak heart rate was considerably higher than in other similar studies.