Featured Case

A Multisensor Approach to Heart Failure Monitoring

Devi G. Nair, MD, FACC, FHRS,

Director of Cardiac Electrophysiology

St. Bernard’s Heart & Vascular Center, & White River Medical Center

Jonesboro, Arkansas

Devi G. Nair, MD, FACC, FHRS,

Director of Cardiac Electrophysiology

St. Bernard’s Heart & Vascular Center, & White River Medical Center

Jonesboro, Arkansas

Introduction

Heart failure (HF) is the number one cause of hospitalization in the developed world.1 With more people surviving heart attacks, an aging population, and a sharp rise in diabetes and obesity, HF rates are expected to skyrocket by 46 percent by 2030. HF also involves costly hospitalizations, with 25 percent of HF patients requiring readmission within 30 days.2 In the U.S., over 50% of the economic costs of heart failure are related to hospitalizations.3

Technology has transformed the way patients monitor their health. Everything from sleep and oxygen intake can be tracked, enabling real-time changes in health behavior. Now, tracking technology is modernizing cardiac care for those at risk of HF. Diagnostics in ICDs and CRT-Ds with associated remote monitoring systems may provide an opportunity to better identify worsening status, but technology to date has used single sensors with high false detection rates or required manual review of multiple measures, limiting utility and adoption.4

In 2017, the U.S. Food and Drug Administration (FDA) approved HeartLogic Heart Failure Diagnostic (Boston Scientific), a diagnostic tool programmed within the Resonate (Boston Scientific) family of ICDs and CRT-Ds, that helps predict and alert physicians of potential heart failure events weeks before they happen, allowing for a proactive approach for treating HF events.

Case Description

A 69-year-old male with coronary artery disease requiring revascularization in February 2018, left bundle branch block, ejection fraction of 25%, NYHA Class III HF symptoms on maximum goal-directed medical therapy, and seven HF-related admissions in 2017-2018, underwent implantation of a CRT-D device in July 2018 for AV synchrony, primary prevention of sudden cardiac death, and biventricular synchrony. The CRT-D device (Resonate X4, Boston Scientific) has standard CRT-D capability as well as HeartLogic, a HF diagnostic tool that provides continuous measurement of multiple sensors evaluating heart sounds, respiration rate and volume, thoracic impedance (TI), heart rate (HR), and activity, and then integrates these into a composite score. The HeartLogic alert threshold was programmed at 16 (nominal value). The patient’s device parameters and HF parameters were followed through the manufacturer’s remote monitoring system (LATITUDE NXT, Boston Scientific). Approximately seven weeks after his device implant, the HeartLogic value reached 48 and an alert was triggered through LATITUDE, as the index crossed the programmed threshold (Figure 1). The contributing factors that led to the alert were device measured S3, and S3/S1 ratio. The HF team called the patient, who had no symptoms at that time, and decided to continue to follow trends and closely monitor the patient. The index continued to rise to 58 (HeartLogic index value) one week later, at which time the contributing factors were noted to be S3, S3/S1 ratio, thoracic impedance, respiratory rate, and nighttime heart rate (Figure 2). The patient’s sleep incline had increased as well. The patient was brought to the office and was noted to be in atrial fibrillation, which was a new diagnosis for the patient. The patient’s diuretic regimen was increased by the HF team, and a cardioversion was performed along with addition of an antiarrhythmic regimen. Two weeks later, the patient was out of alert status. Four weeks after the cardioversion, the patient went back into alert status (Figure 3), with the contributing factors being S3, S3/S1 ratio, and nighttime heart rate (Figure 4). The patient was seen in the office right away, and was noted to have recurrence of his atrial fibrillation on antiarrhythmic therapy. Radiofrequency catheter ablation for pulmonary vein isolation and cavotricuspid isthmus ablation for inducible isthmus-dependent right atrial flutter was performed successfully. The patient maintained normal sinus rhythm post procedure, and came out of alert status three weeks after the procedure (Figure 5). The patient is currently off antiarrhythmic therapy 10 weeks post ablation, and has maintained sinus rhythm and stayed out of alert status since then. He has also not had any HF hospitalization since his device implant, unlike his course prior to device implant.

Discussion

Despite significant advances in medical and device therapy during the past 30 years, the morbidity, mortality, and economic burden of heart failure (HF) remains high. However, because of the variability in patient outcomes, estimating prognosis can be particularly challenging, and yet this is becoming increasingly important to allow limited healthcare resources to be prioritized wisely. A promising step beyond current approaches, HeartLogic is a diagnostic tool that includes a composite index monitored over time and is designed to deliver proactive alerts of worsening heart failure to clinicians. Multiple sensors track key physiological trends related to heart failure from within the high-voltage Resonate family of devices, including heart sounds, thoracic impedance, respiration rate and volume, nighttime heart rate, and activity over time. Device-measured third heart sounds were better at stratifying patient risk for a heart failure event than auscultated third heart sounds.5 Respiration measures changed significantly prior to heart failure events in the MultiSENSE Clinical Study. Respiration rate at rest and during activity increased, tidal volume decreased during activity, and Rapid Shallow Breathing Index (RSBI = Respiration Rate / Tidal Volume) increased most strongly, particularly during activity.6 Thoracic impedance is a measure of resistance of electrical flow through the thorax (from RV lead to the device) determined by lung conductivity and tissue resistance. Increased lung water leads to decreased intrathoracic impedance, reflecting persistent pulmonary congestion. Orthopnea or paroxysmal nocturnal dyspnea (O-PND) are common posture-related symptoms in heart failure. A sleep incline >15° provided 83% sensitivity and 76% specificity to O-PND.7 Resting heart rates may have prognostic values in patients with chronic heart failure.8 Device-based heart rate can provide continuous monitoring over long periods of time, which may provide prognostic implications for heart failure stability.8 Activity is a measure of the health of the patient, and a lower level of physical activity may be associated with increased risk of experiencing a HF event.9 The HeartLogic index is a weighted calculation of the patient’s change in the sensor trends calculated daily into one composite index. Once it crosses a programmable, clinician-set threshold, clinicians are sent a proactive alert and given access to a detailed report. The HeartLogic alert threshold is programmable, with nominal at 16. Alerts, index trends, and sensor trends will be transmitted via LATITUDE remote monitoring or via in-office visits.

As evidenced in the MultiSENSE Study10, which assessed more than 900 patients who had enhanced sensor data collection enabled in their CRT-D systems, the alert is the first and only HF diagnostic in an implantable device that has been validated to have an observed sensitivity of 70 percent as well as the ability to provide weeks of advance notice, a median of 34 days ahead of an impending HF event and low burden for detecting indications of worsening HF. The HeartLogic alert showed a clinically significant 10x increase in heart failure event probability when the patient was in HeartLogic alert status versus out of alert status.11 Dynamic assessment using the sensors within HeartLogic by itself or in conjunction with NT-proBNP measurements can identify time intervals when patients are at significantly increased risk of worsening HF and potentially better triage resources to this vulnerable patient population.11

The ability for HeartLogic to integrate into a clinical workflow, including alerting healthcare professionals at a point when patients may be pre-symptomatic, and the impact on patient outcomes and healthcare resources, is currently unknown. Based on the ability of this index to discriminate high- and low-risk intervals, a study (Multiple Cardiac Sensors for Management of Heart Failure, or MANAGE-HF) designed to optimize the clinical integration of HeartLogic and to evaluate its impact on clinical outcomes is currently underway.

In the care of this patient, the team was able to proactively address the worsening heart failure status before actual development of symptoms, and take care of the triggering event before it led to a hospitalization. Without the HeartLogic data, it was very likely that the patient would have been hospitalized for worsening heart failure from his arrhythmia and only a reactive care plan could have been in place.

Conclusion

High sensitivity, low alert burden, and weeks of advanced notice allows the HeartLogic diagnostic tool to provide physicians the ability to pivot from a reactive HF treatment plan to more proactive care with the goal of reducing HF-related hospitalizations. 

Disclosures: Dr. Nair reports consultancy and research grants for Boston Scientific and Medtronic, consultancy for Biosense Webster, Pfizer, Janssen, and a research grant to Abbott.

This article is published with support from Boston Scientific.

References
  1. Yan AT, Yan RT, Liu PP. Narrative review: pharmacotherapy for chronic heart failure: evidence from recent clinical trials. Ann Intern Med. 2005;142(2):132-145.
  2. Lloyd-Jones D, Adams RJ, Brown TM, et al. American Heart Association. Heart disease and stroke statistics—2010 update: a report from the American Heart Association. Circulation. 2010;121(7):e46-e215.
  3. American Heart Association. One in Four Hospitalized Heart Failure Patients with Medicare Back in Hospital within a Month. Science Daily. Published November 10, 2009. Available at https://bit.ly/2BnCQMW. Accessed December 14, 2018.
  4. Conraads VM, Tavazzi L, Santini M, 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(18):2266-2273.
  5. Cao M, Gardner R, Hariharan R, et al. Abstract 15126: Device-Measured S3 Showed a Stronger Stratification Power Than Auscultation When Assessed at Follow-Up Visits. Circulation. 2018;136:A15126.
  6. Rials S, Merkely B, Gardner R, et al. Device-Measured Rapid Shallow Breathing With Exertion Worsens Prior to Heart Failure Decompensation. J Card Fail. 2015;21(8 Suppl):S77.
  7. Rials SJ, Hatlestad JD, Smith A, et al. Night-time Elevation Angle in Heart Failure Patients Indicates Orthopnea and Paroxysmal Nocturnal Dyspnea. J Card Fail. 2017;23(8):S81.
  8. Fox K, Borer JS, Camm AJ, et al. Resting heart rate in cardiovascular disease. J Am Coll Cardiol. 2007;50:823-830.
  9. Hariharan R, Molon G, An Q, et al. Patients with reduced level of physical activity are at higher risk of worsening heart failure events in 30 days [abstract]. Heart Rhythm. 2016; 13(5):S149-S150.
  10. Boehmer JP, Hariharan R, Devecchi FG, et al. A Multisensor Algorithm Predicts Heart Failure Events in Patients With Implanted Devices: Results From the MultiSENSE Study. JACC Heart Fail. 2017;5(3):216-225.
  11. Gardner RS, Singh JP, Stancak B, et al. HeartLogic Multisensor algorithm identifies patients during periods of significantly increased risk of heart failure events: results from the MultiSENSE study. Circ Heart Fail. 2018;11:e004669.
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