Improvement of a Digital Health Platform for Remote Monitoring of Patients With Heart Failure

NCT05708846 | Completed Results

• 1 other identifier: FOLLOWHEALTH-2023-01
• Study Type: observational
• Target: 154
• Locations: 2 countries
• Sites: 7

Brief Summary

In the present project, we propose to run an observational study in order to create a huge dataset with telemonitoring data from heart failure (HF) patients. The dataset will contain physiological measurements, socio-demographic data, risk factor information, medication tracking, symptomatology, clinical events and health-related questionnaire answers from each patient. Furthermore, health-related alarms will be delivered to the medical professionals whenever a measure from a patient is out of a predefined clinical range. These alarms and its defined level of relevance (indicated by the medical professionals) will also be Included in the dataset. With the annotated dataset we will be able to implement and train Machine Learning (ML) models that will improve the alarm-based system by making it more robust, trustworthy and reliable.

Conditions

Heart Failure

Keywords

Heart Failure; Telemonitoring; Remote monitoring; Remote care; Healthcare; Home care; Artificial Intelligence; Chronic patients

Outcome Measures

Primary Outcomes (2)

• Number of Patients Included in the Dataset

  The dataset will contain the data from HF patients being telemonitored. This outcome shows the number of patients from which data will be used to build a dataset to train ML models for patient health prediction.

  6 months

• Implement ML Models to Improve the Current Alarm-based System Using the Dataset Created

  The models should: Provide a relevance level for each new alarm by reducing the number of irrelevant alarms and thus fostering personalized follow-up. Be robust across different new hospitals and reliable and fair across different target populations, considering the diverse sociodemographic data that will be available in the dataset.

  6 months

Secondary Outcomes (3)

• Track All Clinical Interventions and Events to be Included in the Database

  6 months

• Assess Patient and Medical Professional Satisfaction With the Digital Platform

  6 months

• Mean SUS Score to Assess the Usability of the Digital Platform App

  6 months

Study Arms (1)

Heart Failure patients telemonitored

Patients will be monitored with the vitalera app and platform

Other: Telemonitoring

Interventions

Telemonitoring OTHER

All patients will be telemonitored in order to create a labeled and diverse dataset that will include the following data: Physiological parameters (measured periodically), socio-demographic data, risk factors, medication tracking, symptomatology questionnaire for patients, NYHA-class, clinical interventions, health questionnaire answers, classified alarms with their respective timestamp and annotation by the MD, and measurement ranges for each personalized alarm and their changes

Heart Failure patients telemonitored

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

Heart Failure patients will be recruited from a diversity of hospitals mainly from Spain but also from countries in the south of Europe and Eastern Europe.

You may qualify if:

• Heart failure (HF) patients with NYHA Functional Class \>= II (according to 2021 EU guidelines).
• Patients older than 18 years old.
• Patients who have suffered an acute decompensation of HF (first and recurrent) in the 30 days prior to enrollment in the study.
• NT-pro BNP ≥300 pg/ml at the moment of hospitalization for patients without ongoing atrial fibrillation/flutter. If ongoing atrial fibrillation/flutter, NT-pro BNP must be ≥600 pg/mL
• Patients must have had an echocardiogram during their HF hospitalization or in the previous 12 months.
• Prior to initiating any procedures, the hospital will ensure that the patient obtains an informed consent document, if applicable.
• All patients will be eligible regardless of the level of LVEF: HFrEF, HFmrEF, and HFpEF.

You may not qualify if:

• Oncology patients with metastasis or with chemotherapy treatment ongoing
• Patients participating in other studies or trials.
• Patients not willing to participate.
• Patients over 150 kg
• Patients who do not use Catalan, Spanish, English, Portuguese, Italian, Dutch, German, Swedish, Hungarian, Romanian or French.
• Patients without a mobile phone
• Patients without internet connexion
• Patients with moderate or severe cognitive impairment without a competent caregiver
• Patients with serious psychiatric illness
• Patients with planned cardiac surgery
• Patients with planned heart transplantation or LVAD implant

Sponsors & Collaborators

• humanITcare: lead
• European Innovation Council: collaborator
• Hospital Universitario de Torrevieja: collaborator
• University of Barcelona: collaborator

Study Sites (7)

Hospital of Galati

Galati, Galați County, 800225, Romania

Location

Hospital Floreasca

Bucharest, 014461, Romania

Location

Colentina Hospital

Bucharest, 020125, Romania

Location

Hospital Universitario de Torrevieja

Torrevieja, Alicante, 03186, Spain

Location

Hospital de Figueres

Figueres, Girona, 17600, Spain

Location

Hospital General Universitario Nuestra Señora del Prado

Talavera de la Reina, Toledo, 45600, Spain

Location

Hospital Universitari de Girona Doctor Josep Trueta

Girona, 17007, Spain

Location

Related Publications (12)

• Tripoliti EE, Papadopoulos TG, Karanasiou GS, Naka KK, Fotiadis DI. Heart Failure: Diagnosis, Severity Estimation and Prediction of Adverse Events Through Machine Learning Techniques. Comput Struct Biotechnol J. 2016 Nov 17;15:26-47. doi: 10.1016/j.csbj.2016.11.001. eCollection 2017.

  PMID: 27942354 BACKGROUND

• Authors/Task Force Members:; McDonagh TA, Metra M, Adamo M, Gardner RS, Baumbach A, Bohm M, Burri H, Butler J, Celutkiene J, Chioncel O, Cleland JGF, Coats AJS, Crespo-Leiro MG, Farmakis D, Gilard M, Heymans S, Hoes AW, Jaarsma T, Jankowska EA, Lainscak M, Lam CSP, Lyon AR, McMurray JJV, Mebazaa A, Mindham R, Muneretto C, Francesco Piepoli M, Price S, Rosano GMC, Ruschitzka F, Kathrine Skibelund A; ESC Scientific Document Group. 2021 ESC Guidelines for the diagnosis and treatment of acute and chronic heart failure: Developed by the Task Force for the diagnosis and treatment of acute and chronic heart failure of the European Society of Cardiology (ESC). With the special contribution of the Heart Failure Association (HFA) of the ESC. Eur J Heart Fail. 2022 Jan;24(1):4-131. doi: 10.1002/ejhf.2333.

  PMID: 35083827 BACKGROUND

• Schiff GD, Fung S, Speroff T, McNutt RA. Decompensated heart failure: symptoms, patterns of onset, and contributing factors. Am J Med. 2003 Jun 1;114(8):625-30. doi: 10.1016/s0002-9343(03)00132-3.

  PMID: 12798449 BACKGROUND

• Brahmbhatt DH, Cowie MR. Remote Management of Heart Failure: An Overview of Telemonitoring Technologies. Card Fail Rev. 2019 May 24;5(2):86-92. doi: 10.15420/cfr.2019.5.3. eCollection 2019 May.

  PMID: 31179018 BACKGROUND

• Scherr D, Kastner P, Kollmann A, Hallas A, Auer J, Krappinger H, Schuchlenz H, Stark G, Grander W, Jakl G, Schreier G, Fruhwald FM; MOBITEL Investigators. Effect of home-based telemonitoring using mobile phone technology on the outcome of heart failure patients after an episode of acute decompensation: randomized controlled trial. J Med Internet Res. 2009 Aug 17;11(3):e34. doi: 10.2196/jmir.1252.

  PMID: 19687005 BACKGROUND

• Koulaouzidis G, Iakovidis DK, Clark AL. Telemonitoring predicts in advance heart failure admissions. Int J Cardiol. 2016 Aug 1;216:78-84. doi: 10.1016/j.ijcard.2016.04.149. Epub 2016 Apr 21.

  PMID: 27140340 BACKGROUND

• Koehler F, Winkler S, Schieber M, Sechtem U, Stangl K, Bohm 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.

  PMID: 21444883 BACKGROUND

• Lee S, Chu Y, Ryu J, Park YJ, Yang S, Koh SB. Artificial Intelligence for Detection of Cardiovascular-Related Diseases from Wearable Devices: A Systematic Review and Meta-Analysis. Yonsei Med J. 2022 Jan;63(Suppl):S93-S107. doi: 10.3349/ymj.2022.63.S93.

  PMID: 35040610 BACKGROUND

• Guidi G, Pollonini L, Dacso CC, Iadanza E. A multi-layer monitoring system for clinical management of Congestive Heart Failure. BMC Med Inform Decis Mak. 2015;15 Suppl 3(Suppl 3):S5. doi: 10.1186/1472-6947-15-S3-S5. Epub 2015 Sep 4.

  PMID: 26391638 BACKGROUND

• Muller-Nordhorn J, Roll S, Willich SN. Comparison of the short form (SF)-12 health status instrument with the SF-36 in patients with coronary heart disease. Heart. 2004 May;90(5):523-7. doi: 10.1136/hrt.2003.013995.

  PMID: 15084550 BACKGROUND

• Jaarsma T, Arestedt KF, Martensson J, Dracup K, Stromberg A. The European Heart Failure Self-care Behaviour scale revised into a nine-item scale (EHFScB-9): a reliable and valid international instrument. Eur J Heart Fail. 2009 Jan;11(1):99-105. doi: 10.1093/eurjhf/hfn007.

  PMID: 19147463 BACKGROUND

• Roque NA, Boot WR. A New Tool for Assessing Mobile Device Proficiency in Older Adults: The Mobile Device Proficiency Questionnaire. J Appl Gerontol. 2018 Feb;37(2):131-156. doi: 10.1177/0733464816642582. Epub 2016 Apr 11.

  PMID: 27255686 BACKGROUND

MeSH Terms

Conditions

Heart Failure

Condition Hierarchy (Ancestors)

Heart Diseases; Cardiovascular Diseases

Results Point of Contact

• Title: Data Scientist of vitalera
• Organization: vitalera (FollowHealth SL)

dheart@humanitcare.com

+34644499760

Study Officials

• Julio César MD Blázquez

  Hospital Universitario de Torrevieja

  PRINCIPAL INVESTIGATOR

Publication Agreements

• PI is Sponsor Employee: No
• Restrictive Agreement: No

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: PROSPECTIVE
• Sponsor Type: NETWORK
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: January 13, 2023
• First Posted: February 1, 2023
• Study Start: May 18, 2023
• Primary Completion: December 31, 2024
• Study Completion: December 31, 2024
• Last Updated: April 9, 2025
• Results First Posted: April 8, 2025

Record last verified: 2025-04

Data Sharing

• IPD Sharing: Will not share

Locations

RO (3); ES (4)