HeartMed-HF Digital Therapeutics Improves Exercise Capacity in CHF Patients After AMI

NCT ID: NCT06478732

Last Updated: 2024-07-16

Basic Information

• Recruitment Status: NOT_YET_RECRUITING
• Clinical Phase: NA
• Total Enrollment: 710 participants
• Study Classification: INTERVENTIONAL
• Study Start Date: 2024-07-30
• Study Completion Date: 2026-12-31

Brief Summary

Chronic heart failure (HF) is a severe manifestation and terminal stage of various cardiovascular diseases, with high incidence and mortality rates. Myocardial infarction (MI) is currently one of the most common and significant causes of HF globally. The occurrence of HF after MI significantly increases the mortality risk for patients. Actively controlling risk factors and strengthening outpatient management of HF patients post-MI are crucial for alleviating clinical symptoms and enhancing exercise capacity. Recently, digital health interventions (DHI) have shown promising potential in managing cardiovascular disease patients. However, the application in patients with HF post-MI has not been well-reported. Therefore, this study independently and innovatively designed the HeartMed-HF digital therapeutics to demonstrate its effectiveness and safety in patients with HF after MI.

Detailed Description

Acute myocardial infarction (AMI) is caused by acute occlusion of the coronary artery and interruption of blood flow, which leads to myocardium necrosis in the blood supply area of the culprit vessel. AMI can lead to the loss of cardiomyocytes, which in turn causes ventricular enlargement, myocardial hypertrophy, eventually leading to the decline of cardiac function. In severe cases，AMI may even result in acute or chronic heart failure (HF). Patients with HF after MI have significantly decreased quality of life, high mortality and poor clinical prognosis. Studies have shown that the incidence of HF in patients with ST-segment elevation myocardial infarction (STEMI) is about 21.8%, and the 30-day mortality rate of patients with HF after MI is up to 25%. The occurrence of HF after MI is associated with various factors. Advanced age, hypertension, diabetes, renal insufficiency, rapid heart rate, atrial fibrillation (AF), low left ventricular ejection fraction (LVEF), stroke are all risk factors. Actively controlling these factors is crucial. However, due to the lack of medical knowledge, poor self-mobility among HF patients, outpatient management faces severe challenges. Therefore, strengthening outpatient management for patients with HF after MI is of great significance in alleviating clinical symptoms and improving patients' exercise capacity.

Recently, the digital health intervention (DHI) industry composed of internet, artificial intelligence (AI), mobile terminals and wearable devices has developed rapidly worldwide, which plays an important role in health care. DHI has shown promising prospects in the management of cardiovascular diseases. It can be used for AF screening, blood pressure management, and reducing mortality in HF patients, among other applications. However, the use in patients with HF after MI lacks large-scale evidence-based medical support.

Therefore, this study has independently designed the HeartMed-HF digital heart failure clinical management system for patients with HF after MI. The system monitors patients' weight, heart rate, blood pressure, fluid intake and output, and other HF evaluation indicators at home using wearable devices. Combining data from patients' medical histories, laboratory test results, and surgical records, the system uses AI algorithms to generate personalized outpatient HF management plans, achieving precise home-based clinical management for patients. The core management components include health education, symptom management, continuous monitoring, risk warning, medication management, and cardiac exercise rehabilitation. Additionally, the study will form a comprehensive clinical management team consisting of physician assistants, rehabilitation trainers, nutritionists, psychologists, and health managers. Through an internet platform and mobile terminals, the system closely connects patients and doctors, extending inpatient treatment to the home and realizing a closed-loop clinical management model that integrates real-time monitoring, early warning, and timely intervention.

Conditions

Heart Failure

Study Design

• Allocation Method: RANDOMIZED
• Intervention Model: PARALLEL
• Primary Study Purpose: HEALTH_SERVICES_RESEARCH
• Blinding Strategy: NONE

Study Groups

the experimental group

receive comprehensive heart failure management

Group Type: EXPERIMENTAL

health services

Intervention Type: OTHER

Implement comprehensive heart failure management for patients in the experimental group using the HeartMed-HF digital therapy

the controlled group

receive the current outpatient follow-up management

Group Type: NO_INTERVENTION

No interventions assigned to this group

Interventions

health services

Implement comprehensive heart failure management for patients in the experimental group using the HeartMed-HF digital therapy

Intervention Type: OTHER

Eligibility Criteria

Inclusion Criteria

1. Be of either sex with age ≥ 18 years and ≤ 75 years.

2. Hospitalization due to AMI (onset to randomization ≤ 2 weeks), including STEMI and NSTEMI.

3. Meeting the diagnostic criteria for chronic HF, including:

(1) Symptoms and/or signs of heart failure; (2) LVEF (Simpson's method) < 50%, and NT-proBNP ≥ 125pg/mL before enrollment. 4. Patients must be willing to comply with the study protocol and give the informed consent.

Exclusion Criteria

1. Contraindications to cardiopulmonary exercise testing (bicycle ergometer) or 6-minute walking test.

2. Pregnancy, breastfeeding, or planning pregnacy within 1 year.

3. Patients who have undergone mechanical circulatory support (including intra-aortic balloon pump, Impella, ECMO, etc.) or endotracheal intubation.

4. History of viral cardiomytis or non-ischemic cardiomyopathy including dilated cardiomyopathy, hypertrophic cardiomyopathy, perinatal cardiomyopathy, etc.

5. Moderate to severe valvular heart disease or a history of valve replacement.

6. Severe liver dysfunction [ALT ≥ 3 times the upper limit of normal range or renal dysfunction (eGFR<60 mL /min/1.73m2)].

7. Malignant tumors or other diseases, with expected life expectancy <1 year.

8. Inability to use smartphones or communicate with the management team for any reason.

9. Enrolled in other clinical trials.

10. Any other clinical conditions unsuitable for this study by the investigator.

• Minimum Eligible Age: 18 Years
• Maximum Eligible Age: 75 Years
• Eligible Sex: ALL
• Accepts Healthy Volunteers: No

Sponsors

The First Affiliated Hospital with Nanjing Medical University

OTHER

Sponsor Role: lead

Responsible Party

Chunjian Li

Director of Cardiology

Responsibility Role: PRINCIPAL_INVESTIGATOR

Central Contacts

Chunjian Li, PHD

Role: CONTACT

lijay@njmu.edu.cn

13701465229

Tian Wu, MD

Role: CONTACT

wu_tian97@163.com

15651751103

References

Wang H, Chai K, Du M, Wang S, Cai JP, Li Y, Zeng P, Zhu W, Zhan S, Yang J. Prevalence and Incidence of Heart Failure Among Urban Patients in China: A National Population-Based Analysis. Circ Heart Fail. 2021 Oct;14(10):e008406. doi: 10.1161/CIRCHEARTFAILURE.121.008406. Epub 2021 Aug 28.

Reference Type: BACKGROUND

PMID: 34455858 (View on PubMed)

Savarese G, Becher PM, Lund LH, Seferovic P, Rosano GMC, Coats AJS. Global burden of heart failure: a comprehensive and updated review of epidemiology. Cardiovasc Res. 2023 Jan 18;118(17):3272-3287. doi: 10.1093/cvr/cvac013.

Reference Type: BACKGROUND

PMID: 35150240 (View on PubMed)

Velagaleti RS, Pencina MJ, Murabito JM, Wang TJ, Parikh NI, D'Agostino RB, Levy D, Kannel WB, Vasan RS. Long-term trends in the incidence of heart failure after myocardial infarction. Circulation. 2008 Nov 11;118(20):2057-62. doi: 10.1161/CIRCULATIONAHA.108.784215. Epub 2008 Oct 27.

Reference Type: BACKGROUND

PMID: 18955667 (View on PubMed)

Cohen AB, Dorsey ER, Mathews SC, Bates DW, Safavi K. A digital health industry cohort across the health continuum. NPJ Digit Med. 2020 May 12;3:68. doi: 10.1038/s41746-020-0276-9. eCollection 2020.

Reference Type: BACKGROUND

PMID: 32411829 (View on PubMed)

Chen C, Ding S, Wang J. Digital health for aging populations. Nat Med. 2023 Jul;29(7):1623-1630. doi: 10.1038/s41591-023-02391-8. Epub 2023 Jul 18.

Reference Type: BACKGROUND

PMID: 37464029 (View on PubMed)

Vardas PE, Asselbergs FW, van Smeden M, Friedman P. The year in cardiovascular medicine 2021: digital health and innovation. Eur Heart J. 2022 Jan 31;43(4):271-279. doi: 10.1093/eurheartj/ehab874.

Reference Type: BACKGROUND

PMID: 34974610 (View on PubMed)

Perez MV, Mahaffey KW, Hedlin H, Rumsfeld JS, Garcia A, Ferris T, Balasubramanian V, Russo AM, Rajmane A, Cheung L, Hung G, Lee J, Kowey P, Talati N, Nag D, Gummidipundi SE, Beatty A, Hills MT, Desai S, Granger CB, Desai M, Turakhia MP; Apple Heart Study Investigators. Large-Scale Assessment of a Smartwatch to Identify Atrial Fibrillation. N Engl J Med. 2019 Nov 14;381(20):1909-1917. doi: 10.1056/NEJMoa1901183.

Reference Type: BACKGROUND

PMID: 31722151 (View on PubMed)

Kerwagen F, Koehler K, Vettorazzi E, Stangl V, Koehler M, Halle M, Koehler F, Stork S. Remote patient management of heart failure across the ejection fraction spectrum: A pre-specified analysis of the TIM-HF2 trial. Eur J Heart Fail. 2023 Sep;25(9):1671-1681. doi: 10.1002/ejhf.2948. Epub 2023 Jul 31.

Reference Type: BACKGROUND

PMID: 37368507 (View on PubMed)

Alshahrani NS, Hartley A, Howard J, Hajhosseiny R, Khawaja S, Seligman H, Akbari T, Alharbi BA, Bassett P, Al-Lamee R, Francis D, Kaura A, Kelshiker MA, Peters NS, Khamis R. Randomized Trial of Remote Assessment of Patients After an Acute Coronary Syndrome. J Am Coll Cardiol. 2024 Jun 11;83(23):2250-2259. doi: 10.1016/j.jacc.2024.03.398. Epub 2024 Apr 6.

Reference Type: BACKGROUND

PMID: 38588928 (View on PubMed)

McManus RJ, Little P, Stuart B, Morton K, Raftery J, Kelly J, Bradbury K, Zhang J, Zhu S, Murray E, May CR, Mair FS, Michie S, Smith P, Band R, Ogburn E, Allen J, Rice C, Nuttall J, Williams B, Yardley L; HOME BP investigators. Home and Online Management and Evaluation of Blood Pressure (HOME BP) using a digital intervention in poorly controlled hypertension: randomised controlled trial. BMJ. 2021 Jan 19;372:m4858. doi: 10.1136/bmj.m4858.

Reference Type: BACKGROUND

PMID: 33468518 (View on PubMed)

Victoria-Castro AM, Martin ML, Yamamoto Y, Melchinger H, Weinstein J, Nguyen A, Lee KA, Gerber B, Calderon F, Subair L, Lee V, Williams A, Shaw M, Arora T, Garcez A, Desai NR, Ahmad T, Wilson FP. Impact of Digital Health Technology on Quality of Life in Patients With Heart Failure. JACC Heart Fail. 2024 Feb;12(2):336-348. doi: 10.1016/j.jchf.2023.09.022. Epub 2023 Nov 8.

Reference Type: BACKGROUND

PMID: 37943227 (View on PubMed)

Dorje T, Zhao G, Tso K, Wang J, Chen Y, Tsokey L, Tan BK, Scheer A, Jacques A, Li Z, Wang R, Chow CK, Ge J, Maiorana A. Smartphone and social media-based cardiac rehabilitation and secondary prevention in China (SMART-CR/SP): a parallel-group, single-blind, randomised controlled trial. Lancet Digit Health. 2019 Nov;1(7):e363-e374. doi: 10.1016/S2589-7500(19)30151-7. Epub 2019 Oct 10.

Reference Type: BACKGROUND

PMID: 33323210 (View on PubMed)

Treskes RW, van Winden LAM, van Keulen N, van der Velde ET, Beeres SLMA, Atsma DE, Schalij MJ. Effect of Smartphone-Enabled Health Monitoring Devices vs Regular Follow-up on Blood Pressure Control Among Patients After Myocardial Infarction: A Randomized Clinical Trial. JAMA Netw Open. 2020 Apr 1;3(4):e202165. doi: 10.1001/jamanetworkopen.2020.2165.

Reference Type: BACKGROUND

PMID: 32297946 (View on PubMed)

Other Identifiers

031

Identifier Type: -

Identifier Source: org_study_id