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| ID | Type | Description | Link |
|---|---|---|---|
| PI 152/22 | Other Identifier | HOSPITAL PUERTA DE HIERRO |
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| Name | Class |
|---|---|
| Hannover Medical School | OTHER |
| Attikon Hospital | OTHER |
| IRCCS Azienda Ospedaliero-Universitaria di Bologna | OTHER |
| Onassis Cardiac Surgery Centre |
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The goal of this study is to create a digital platform for managing patients with chronic heart failure, those with long-term ventricular assistance, or heart transplant recipients. This platform aims to help doctors make clinical decisions and change treatments based on continuous monitoring and the collection of medical, clinical, physiological, behavioral, psychosocial, and real-world data from these patients.
The ultimate goal is to reduce mortality and hospitalization rates for this group of patients while improving their quality of life, safety, and well-being.
To do this, participants will be divided into two groups:
All participating patients will receive a set of devices and sensors to collect data such as vital signs, physical activity, sleep quality, psychological and nutritional status, and environmental data. All this information will be gathered through a mobile app designed for the study.
The follow-up will last for 18 months, during which there will be 4 in-person medical visits (spaced 4 months apart). Participation in the study won't affect patients' scheduled medical visits related to their illness or their usual treatment.
Specifically, the devices that will be given to the patients and their required use will be as follows:
A Smartphone: This will have the app with the platform designed for the study. The patient must interact with it daily to enter data.
A Blood Pressure Monitor: The patient will need to take their blood pressure every day and send it via Bluetooth to the mobile platform (the connection setup will be done by the study team before giving it to the patients).
An Oxygen Saturation Monitor: The patient will need to check their oxygen levels daily and send the data via Bluetooth to the mobile platform (the connection setup will be done by the study team before giving it to the patients).
A Scale: The patient will need to weigh themselves daily and transmit the data via Bluetooth to the mobile platform (the connection setup will be done by the study team before giving it to the patients).
A Smartwatch: The patient must send data on their physical activity and sleep daily via Bluetooth to the mobile platform (the connection setup will be done by the study team before giving it to the patients).
Home Humidity and Temperature Sensors and a Home Gateway Device (Raspberry Pi): The patient will need to connect this last device to their home internet network. The connection setup will be done by the study team before giving it to the patients.
There are other data and information that the patient must manually enter into the app, such as daily body temperature, symptoms they experience (like increased fatigue or shortness of breath), or data on the functioning of the long-term ventricular assistance (controller parameters or alarm presence). Additionally, the app will show the patient's current medication, which they need to confirm they have taken correctly.
The scheduled visits during the study will take place at the Baseline and every four months. These visits will include an in-person medical visit, an electrocardiogram, a blood test, and a 6-minute walk test. Also, at each visit, a series of questionnaires will be given to assess the patient's cognitive, nutritional, and psychological state, as well as their quality of life and that of their primary caregivers. Some visits will also include more specific cardiac tests, like an echocardiogram or a cardiopulmonary exercise test.
If during the study follow-up, the treating doctors unexpectedly discover any information that affects the patient's health or quality of life, the patient will be informed immediately, even if it is unrelated to the study's purpose.
All data recorded throughout the study will be stored anonymously by the study platform.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Intervention group | Experimental | The RETENTION platform will offer to the clinician in the experimental arm all the data gathered by the devices (smart watch, scale, oximeter, blood pressure monitor, temperature, medication adherence, weather and pollution indexes). along with artificial intelligence recommendations. |
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| Control group | Placebo Comparator | Patients in the control group will be monitored but the data will not be available to the clinicians nor the artificial intelligence recommendations. |
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| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Heart monitoring tools (data revision) | Device | data collected by the devices will be reviewed by the treating physician in the intervention group |
|
| Measure | Description | Time Frame |
|---|---|---|
| Difference in days lost due to unplanned cardiovascular hospitalizations or all-cause death between groups | Comparison of days lost due to unplanned cardiovascular hospitalizations or all-cause death between groups | From the enrollment to the end of the follow up (18 months) |
| Differences in the rates of occurrence of death or unplanned hospitalization/ambulatory administration of intravenous (iv) diuretics, iv antibiotics or iv steroids | Comparison of the rates of the occurrence of death or unplanned hospitalization/ambulatory administration of intravenous (iv) diuretics, iv antibiotics or iv steroids between groups | From the enrollment to the end of the follow up (18 months) |
| Measure | Description | Time Frame |
|---|---|---|
| Rates of all-cause mortality | From the enrollment to the end of the follow up (18 months) | |
| Rates of cardiovascular mortality | From the enrollment to the end of the follow up (18 months)] | |
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Inclusion Criteria:
Exclusion Criteria:
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| Name | Affiliation | Role |
|---|---|---|
| Maria Haritou, PhD | ICCS | Study Chair |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Medizinische Hochschule Hannover ('Mhh') | Hanover | Germany | ||||
| National and Kapodistrian University of Athens |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 30419185 | Background | Scott IA, Scuffham P, Gupta D, Harch TM, Borchi J, Richards B. Going digital: a narrative overview of the effects, quality and utility of mobile apps in chronic disease self-management. Aust Health Rev. 2020 Feb;44(1):62-82. doi: 10.1071/AH18064. | |
| 32558251 | Background | Ski CF, Thompson DR, Brunner-La Rocca HP. Putting AI at the centre of heart failure care. ESC Heart Fail. 2020 Oct;7(5):3257-3258. doi: 10.1002/ehf2.12813. Epub 2020 Jun 17. No abstract available. |
| Label | URL |
|---|---|
| Oficial project's web site. It provides information about the project to every user. | View source |
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| OTHER |
| Hospital Universitario Ramon y Cajal | OTHER |
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The care providers will be masked to the data collected by the control group
| Control (Standard treatment) | Other | Patients in the control group will be monitored but the information will not be available for the clinicians nor the artificial intelligence recommendations |
|
| Differences in time to first unplanned HF hospitalization |
| From the enrollment to the end of the follow up (18 months)] |
| Differences in time to first unplanned cardiovascular hospitalization | From the enrollment to the end of the follow up (18 months)] |
| Rate of total unplanned HF hospitalizations | From the enrollment to the end of the follow up (18 months) |
| Rate of total unplanned cardiovascular hospitalizations | From the enrollment to the end of the follow up (18 months) |
| Differences in days lost due to HF hospitalizations | From the enrollment to the end of the follow up (18 months)] |
| Differences in the number of Smart device alarm notifications | From the enrollment to the end of the follow up (18 months) |
| Change in Kansas City Cardiomyopathy Questionnaire (KCCQ) score | between Baseline and last visit. KCCQ ranges from 0 to 100, higher scores indicating higher quality of life | From the enrollment to the end of the follow up (18 months) |
| Change in the levels of NT-proBNP | Between Baseline and last visit | From the enrollment to the end of the follow up (18 months) |
| Change in the Depression Score Patient Health Questionnaire 9 (PHQ-9) | Between baseline and last visit | From the enrollment to the end of the follow up (18 months) |
| Change in the Heart Failure Caregiver Questionnaire (HF-CQ version 5.0) | Between baseline and last visit | From the enrollment to the end of the follow up (18 months)] |
| Difference in the rate of rejection needing treatment in heart transplant patients | From the enrollment to the end of the follow up (18 months) |
| Driveline infection needing antibiotic in left ventricular assist device (LVAD) patients | From the enrollment to the end of the follow up (18 months) |
| Differences in the rate of unplanned visit for heart failure requiring intravenous diuretics | From the enrollment to the end of the follow up (18 months) |
| Difference in the number of visits outside the protocol | From the enrollment to the end of the follow up (18 months) |
| Athens |
| Greece |
| Onassis Cardiac Surgery Center | Athens | Greece |
| Alma Mater Studiorum - Universita Di Bologna | Bologna | Italy |
| Hospital Universitario Puerta de Hierro | Majadahonda | Madrid | 28222 | Spain |
| Hospital Universitario Ramón Y Cajal | Madrid | Spain |
| 29880130 | Background | McConnell MV, Turakhia MP, Harrington RA, King AC, Ashley EA. Mobile Health Advances in Physical Activity, Fitness, and Atrial Fibrillation: Moving Hearts. J Am Coll Cardiol. 2018 Jun 12;71(23):2691-2701. doi: 10.1016/j.jacc.2018.04.030. |
| 27119325 | Background | Dorsey ER, Yvonne Chan YF, McConnell MV, Shaw SY, Trister AD, Friend SH. The Use of Smartphones for Health Research. Acad Med. 2017 Feb;92(2):157-160. doi: 10.1097/ACM.0000000000001205. |
| 27185508 | Background | Liu L, Stroulia E, Nikolaidis I, Miguel-Cruz A, Rios Rincon A. Smart homes and home health monitoring technologies for older adults: A systematic review. Int J Med Inform. 2016 Jul;91:44-59. doi: 10.1016/j.ijmedinf.2016.04.007. Epub 2016 Apr 19. |
| 33938466 | Background | Goswami R. The current state of artificial intelligence in cardiac transplantation. Curr Opin Organ Transplant. 2021 Jun 1;26(3):296-301. doi: 10.1097/MOT.0000000000000875. |
| 26344584 | Background | Shahbazi F, Asl BM. Generalized discriminant analysis for congestive heart failure risk assessment based on long-term heart rate variability. Comput Methods Programs Biomed. 2015 Nov;122(2):191-8. doi: 10.1016/j.cmpb.2015.08.007. Epub 2015 Aug 24. |
| 27942354 | Background | 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. |
| 26670209 | Background | Bennett MK, Shao M, Gorodeski EZ. Home monitoring of heart failure patients at risk for hospital readmission using a novel under-the-mattress piezoelectric sensor: A preliminary single centre experience. J Telemed Telecare. 2017 Jan;23(1):60-67. doi: 10.1177/1357633X15618810. Epub 2016 Jul 9. |
| 28939459 | Background | Yun JE, Park JE, Park HY, Lee HY, Park DA. Comparative Effectiveness of Telemonitoring Versus Usual Care for Heart Failure: A Systematic Review and Meta-analysis. J Card Fail. 2018 Jan;24(1):19-28. doi: 10.1016/j.cardfail.2017.09.006. Epub 2017 Sep 20. |
| 28785469 | Background | Savarese G, Lund LH. Global Public Health Burden of Heart Failure. Card Fail Rev. 2017 Apr;3(1):7-11. doi: 10.15420/cfr.2016:25:2. |
| 26857383 | Background | Ong MK, Romano PS, Edgington S, Aronow HU, Auerbach AD, Black JT, De Marco T, Escarce JJ, Evangelista LS, Hanna B, Ganiats TG, Greenberg BH, Greenfield S, Kaplan SH, Kimchi A, Liu H, Lombardo D, Mangione CM, Sadeghi B, Sadeghi B, Sarrafzadeh M, Tong K, Fonarow GC; Better Effectiveness After Transition-Heart Failure (BEAT-HF) Research Group. Effectiveness of Remote Patient Monitoring After Discharge of Hospitalized Patients With Heart Failure: The Better Effectiveness After Transition -- Heart Failure (BEAT-HF) Randomized Clinical Trial. JAMA Intern Med. 2016 Mar;176(3):310-8. doi: 10.1001/jamainternmed.2015.7712. |