Heart Failure Monitoring With Eko Electronic Stethoscopes (CardioMEMS)

Heart Failure Clinical Trial

Official title:

Heart Failure Monitoring With Eko Electronic Stethoscopes (CardioMEMS)

Clinical Trial Details — Status: Recruiting

Administrative data

• NCT number: NCT05080504
• Other study ID #: 2022.1
• Status: Recruiting
• Start date: February 1, 2021
• Est. completion date: May 1, 2023

Study information

• Verified date: November 2022
• Source: Eko Devices, Inc.
• Contact: Ben Verschoore, BS
• Phone: 443-545-6094
• Email: ben.verschoore[@]ekohealth.com
• Is FDA regulated: No
• Study type: Observational

Clinical Trial Summary

This study will enroll heart failure (HF) patients who are under active management with an implanted pulmonary artery pressure sensor (CardioMEMS). Subjects will be provided an electronic stethoscope (the Eko DUO) to take at-home heart sound, lung sound, and ECG recordings in conjunction with regimented CardioMEMS measurements. These two datasets will be used to confirm whether an AI/ML model to track HF status can be developed.

Description:

Heart failure (HF) affects an estimated 6.2 million Americans over the age of 20 and carries a very high healthcare system burden worldwide. Annual costs for HF management in the United States were estimated at $30.7 billion in 2012 and are projected to increase to $68.7 billion by 2030. The primary cost driver for HF management is a high rate of acute decompensation and subsequent hospitalization. The mean per-patient cost of an HF-related hospitalization is estimated to be $14,631.

Among the conditions that the Centers of Medicare and Medicaid Services (CMS) monitors for their Hospital Readmission Reduction Program, HF has the highest median readmission rate at days 1-29 (23%) and days 1-60 (11.4%) postdischarge. The cost burden of HF readmission is $2.7 billion in 2013. A meta-analysis from 2012 estimated that 23.1% of HF readmissions are avoidable, although individual studies ranged from 5% to 79%. Many health plans, including CMS, have focused on interventions that monitor patients for early detection of HF decompensation. Earlier interventions can help care teams prevent avoidable hospitalizations.

Invasive hemodynamic sensor devices have enabled HF care teams to better predict and prevent HF decompensation events, and thus prevent rehospitalizations. One such device is the CardioMEMS pulmonary artery (PA) sensor (Abbott Inc., Atlanta, GA, USA). The CardioMEMS is implanted in a branch of the left PA, allowing for daily measurements of PA pressures. PA pressures are used as a surrogate marker of filling pressure, and rising filling pressures, in turn, are a marker that precedes the exacerbation of HF. The CHAMPIONS trial demonstrated that remote diuretic management using CardioMEMS reduced HF all-cause hospitalizations by 43% and mortality by 57%. Unfortunately, CardioMEMS as an HF solution is invasive, costly (average sales price of $17,750), indicated for a restricted patient population (NYHA class III HF who have been hospitalized within the last year), and has limited reimbursement coverage due to equivocal cost-effectiveness projections.

This has stimulated a search for less expensive, non-invasive sensors that may correlate with fluid status in HF patients. A study in Taiwan demonstrated that outpatient therapy guided by an inpatient device with ECG and sound sensors reduced post-discharge HF utilization by 31% when compared to a control group using symptoms to guide therapy. The LINK-HF study demonstrated that a wearable patch with ECG and sound sensors could predict HF readmissions with a sensitivity of 76% to 88%, a specificity of 85%, and a median lead time of 6.5 days.

Despite these initially promising results, however, these devices have significant disadvantages. The inpatient device used in the Taiwanese study could not be adapted into a portable form factor for outpatient use. Wearable devices can be rigid, uncomfortable, and highly visible, all of which can interfere with patient function and decrease monitoring compliance.

Therefore, there remains an unmet clinical need for a widely available, non-invasive, affordable medical device that can estimate an HF patient's hemodynamic fluid status and inform the HF care management team. The ultimate goal remains to decrease an HF patient's risk for hospital readmission, all from the comfort of the patient's home.

To meet this need, Eko has developed the DUO, an FDA-cleared, portable, hand-held, wirelessly connected medical device with ECG and sound sensors. Data from the DUO can be wirelessly streamed to a mobile phone or tablet, which can then be transmitted to a HIPAA-compliant internet cloud infrastructure for storage and analysis. In 2020, Eko introduced into the US market a package of AI/ML algorithms that follows this workflow to identify heart murmurs, atrial fibrillation, and other cardiac conditions, and intends after this proof of concept study to build upon this platform to estimate and trend PA pressures.

But beyond measuring and trending PA pressures, the DUO can be used to capture additional important HF features that will further improve any HF algorithm's performance. For example, because patients with decompensated HF often have an audible third heart sound, characteristic ECG findings, and altered time interval durations between their heart sounds and ECG signals, the Eko DUO device may be uniquely positioned to detect these types of changing signals.

In addition, because heart failure and fluid overload are reflected in the lungs as crackles (and occasionally effusions), the lung examination is and has always been a cornerstone of the overall physical examination of HF patients. By using the DUO to capture lung sounds in patients with HF, and comparing not only the presence or absence of crackles, but also how these adventitious sounds change over time, we will be able to explore the utility of the Eko DUO in helping to predict exacerbated HF.

This proof-of-concept study evaluates the feasibility of the Eko DUO in capturing and measuring signals relevant to HF exacerbation (e.g., time intervals, adventitious lungs sounds, pathologic heart sounds), as well as the feasibility of developing an AI/ML algorithm to model PA pressures in HF patients with the implantable CardioMEMS device.

Recruitment information / eligibility

• Status: Recruiting
• Enrollment: 50
• Est. completion date: May 1, 2023
• Est. primary completion date: April 1, 2023
• Accepts healthy volunteers: No
• Gender: All
• Age group: 18 Years and older

Eligibility

Inclusion Criteria:

• Aged 18 years and older

• Patient or healthcare proxy willing to give written informed consent to participate

• Presence of an implanted CardioMEMS device or imminent implantation of a CardioMEMS device

• Expressed willingness to take DUO recordings immediately before or after taking their CardioMEMS measurements, on the same schedule prescribed by their physician

• Functioning iOS or Android smartphone or tablet that can download and run the companion Eko application

• Access to WiFi or cellular data connection at home

Exclusion Criteria:

• Patient or healthcare proxy is unwilling or unable to give written informed consent

• Patient is enrolled in another study that may interfere with the observations from this study

• Acute pericarditis

• Healing chest wall wounds (e.g., sternotomy or thoracotomy)

Related Conditions & MeSH terms

• Heart Failure

Intervention

Device:
• Eko DUO
Each subject will take an Eko DUO device home and take DUO recordings immediately before or after their prescribed CardioMEMS measurements. The DUO recordings will be taken at 3 predefined chest locations: the right upper sternal border, left upper sternal border, and right anterolateral. Each DUO recording lasts about 15 seconds. The total time per recording session is expected to be 2-4 minutes, which allows for time between recordings and any potential repeat recordings. Study participation will last for 90 days.

Locations

Country	Name	City	State
United States	Columbia University Irving Medical Center	New York	New York
United States	Sentara Cardiovascular Research Institute	Norfolk	Virginia

Sponsors (3)

Lead Sponsor	Collaborator
Eko Devices, Inc.	Columbia University, Sentara Norfolk General Hospital

Country where clinical trial is conducted

United States, 

References & Publications (20)

"Trends in Hospital Readmissions and Mortality Rates - American College of Cardiology." N.d. American College of Cardiology. Accessed April 2, 2020. https://www.acc.org/latest-in-cardiology/journal-scans/2019/07/10/09/53/evaluation-of-30-day-hospital-readmission.

Brugts JJ, Veenis JF, Radhoe SP, Linssen GCM, van Gent M, Borleffs CJW, van Ramshorst J, van Pol P, Tukkie R, Spee RF, Emans ME, Kok W, van Halm V, Handoko L, Beeres SLMA, Post MC, Boersma E, Lenzen MJ, Manintveld OC, Koffijberg H, van Baal P, Versteegh M, Smilde TD, van Heerebeek L, Rienstra M, Mosterd A, Delnoy PPH, Asselbergs FW, Brunner-La Rocca HP, de Boer RA. A randomised comparison of the effect of haemodynamic monitoring with CardioMEMS in addition to standard care on quality of life and hospitalisations in patients with chronic heart failure : Design and rationale of the MONITOR HF multicentre randomised clinical trial. Neth Heart J. 2020 Jan;28(1):16-26. doi: 10.1007/s12471-019-01341-9. — View Citation

Chaudhry SI, Mattera JA, Curtis JP, Spertus JA, Herrin J, Lin Z, Phillips CO, Hodshon BV, Cooper LS, Krumholz HM. Telemonitoring in patients with heart failure. N Engl J Med. 2010 Dec 9;363(24):2301-9. doi: 10.1056/NEJMoa1010029. Epub 2010 Nov 16. Erratum in: N Engl J Med. 2011 Feb 3;364(5):490. N Engl J Med. 2013 Nov 7;369(19):1869. — View Citation

Desai AS, Stevenson LW. Rehospitalization for heart failure: predict or prevent? Circulation. 2012 Jul 24;126(4):501-6. doi: 10.1161/CIRCULATIONAHA.112.125435. — View Citation

Dhruva SS, Krumholz HM. Championing Effectiveness Before Cost-Effectiveness. JACC Heart Fail. 2016 May;4(5):376-9. doi: 10.1016/j.jchf.2016.02.001. Epub 2016 Mar 30. — View Citation

Givertz MM, Stevenson LW, Costanzo MR, Bourge RC, Bauman JG, Ginn G, Abraham WT; CHAMPION Trial Investigators. Pulmonary Artery Pressure-Guided Management of Patients With Heart Failure and Reduced Ejection Fraction. J Am Coll Cardiol. 2017 Oct 10;70(15):1875-1886. doi: 10.1016/j.jacc.2017.08.010. — View Citation

Hulley SB, Cummings SR, Browner WS, Grady D, Newman TB. Designing Clinical Research: An Epidemiologic Approach. 4th ed. Philadelphia, PA: Lippincott Williams & Wilkins; 2013. Appendix 6C, p79.

Inglis SC, Clark RA, McAlister FA, Ball J, Lewinter C, Cullington D, Stewart S, Cleland JG. Structured telephone support or telemonitoring programmes for patients with chronic heart failure. Cochrane Database Syst Rev. 2010 Aug 4;(8):CD007228. doi: 10.1002/14651858.CD007228.pub2. Review. Update in: Cochrane Database Syst Rev. 2015;10:CD007228. — View Citation

Johnston M, Collins SP, Storrow AB. The third heart sound for diagnosis of acute heart failure. Curr Heart Fail Rep. 2007 Sep;4(3):164-8. Review. — View Citation

Kilgore M, Patel HK, Kielhorn A, Maya JF, Sharma P. Economic burden of hospitalizations of Medicare beneficiaries with heart failure. Risk Manag Healthc Policy. 2017 May 10;10:63-70. doi: 10.2147/RMHP.S130341. eCollection 2017. — View Citation

Koehler F, Winkler S, Schieber M, Sechtem U, Stangl K, Böhm M, Boll H, Baumann G, Honold M, Koehler K, Gelbrich G, Kirwan BA, Anker SD; Telemedical Interventional Monitoring in Heart Failure Investigators. Impact of remote telemedical management on mortality and hospitalizations in ambulatory patients with chronic heart failure: the telemedical interventional monitoring in heart failure study. Circulation. 2011 May 3;123(17):1873-80. doi: 10.1161/CIRCULATIONAHA.111.018473. Epub 2011 Mar 28. — View Citation

Madias JE. The resting electrocardiogram in the management of patients with congestive heart failure: established applications and new insights. Pacing Clin Electrophysiol. 2007 Jan;30(1):123-8. Review. — View Citation

Schmier JK, Ong KL, Fonarow GC. Cost-Effectiveness of Remote Cardiac Monitoring With the CardioMEMS Heart Failure System. Clin Cardiol. 2017 Jul;40(7):430-436. doi: 10.1002/clc.22696. Epub 2017 Mar 8. — View Citation

Sehatbakhsh, Samineh, Stephanie Hakimian, Yash Jobanputra, Rosmy Jimmy, Robert Chait, Mark Showronski, Kaustubh Kale, and Steven Borzak. 2018. "Assessment of LV Systolic Function Using Cardiac Time Intervals with an Acoustic Array Approach." Journal of Cardiac Failure 24 (8): S38.

Stehlik J, Schmalfuss C, Bozkurt B, Nativi-Nicolau J, Wohlfahrt P, Wegerich S, Rose K, Ray R, Schofield R, Deswal A, Sekaric J, Anand S, Richards D, Hanson H, Pipke M, Pham M. Continuous Wearable Monitoring Analytics Predict Heart Failure Hospitalization: The LINK-HF Multicenter Study. Circ Heart Fail. 2020 Mar;13(3):e006513. doi: 10.1161/CIRCHEARTFAILURE.119.006513. Epub 2020 Feb 25. — View Citation

Sung, Shih-Hsien, Wen-Chung Yu, Hao-Min Cheng, Yu-Ping Chang, and Chen-Huan Chen. 2019. "USE OF ACOUSTIC CARDIOGRAPHY TO GUIDE OUTPATIENT THERAPY OF PATIENTS WITH ACUTE HEART FAILURE SYNDROME." Journal of the American College of Cardiology 63 (12 Supplement): A541.

Toukhsati SR, Driscoll A, Hare DL. Patient Self-management in Chronic Heart Failure - Establishing Concordance Between Guidelines and Practice. Card Fail Rev. 2015 Oct;1(2):128-131. doi: 10.15420/cfr.2015.1.2.128. — View Citation

van Walraven C, Jennings A, Forster AJ. A meta-analysis of hospital 30-day avoidable readmission rates. J Eval Clin Pract. 2012 Dec;18(6):1211-8. doi: 10.1111/j.1365-2753.2011.01773.x. Epub 2011 Nov 9. — View Citation

Virani SS, Alonso A, Benjamin EJ, Bittencourt MS, Callaway CW, Carson AP, Chamberlain AM, Chang AR, Cheng S, Delling FN, Djousse L, Elkind MSV, Ferguson JF, Fornage M, Khan SS, Kissela BM, Knutson KL, Kwan TW, Lackland DT, Lewis TT, Lichtman JH, Longenecker CT, Loop MS, Lutsey PL, Martin SS, Matsushita K, Moran AE, Mussolino ME, Perak AM, Rosamond WD, Roth GA, Sampson UKA, Satou GM, Schroeder EB, Shah SH, Shay CM, Spartano NL, Stokes A, Tirschwell DL, VanWagner LB, Tsao CW; American Heart Association Council on Epidemiology and Prevention Statistics Committee and Stroke Statistics Subcommittee. Heart Disease and Stroke Statistics-2020 Update: A Report From the American Heart Association. Circulation. 2020 Mar 3;141(9):e139-e596. doi: 10.1161/CIR.0000000000000757. Epub 2020 Jan 29. — View Citation

Zohrabian A, Kapp JM, Simoes EJ. The economic case for US hospitals to revise their approach to heart failure readmission reduction. Ann Transl Med. 2018 Aug;6(15):298. doi: 10.21037/atm.2018.07.30. — View Citation

* Note: There are 20 references in all — Click here to view all references

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	Correlation between AI/ML model output and the ground-truth of CardioMEMS PA pressure measurements.	The primary objective of this proof of concept study is to demonstrate whether Eko data scientists can create an artificial intelligence machine learning (AI/ML) model of pulmonary artery (PA) pressures by analyzing sound and electrical (ECG) signals of heart activity captured by the non-invasive, FDA-cleared, Eko DUO electronic stethoscope.	6 months
Secondary	Composite of the incidence of poor-quality ECG or PCG data and tabulation of patient compliance with the data measurement schedule	A secondary objective of the study is to assess the usability of the Eko DUO by patients at home	6 months
Secondary	Intra-subject reproducibility of measured variables		6 months