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Clinical Trial Details — Status: Completed

Administrative data

NCT number NCT05538455
Other study ID # PC4L-Pilot3
Secondary ID
Status Completed
Phase N/A
First received
Last updated
Start date September 30, 2022
Est. completion date April 30, 2023

Study information

Verified date August 2023
Source Casa di Cura Privata del Policlinico SpA
Contact n/a
Is FDA regulated No
Health authority
Study type Interventional

Clinical Trial Summary

Personalized Integrated Care Promoting Quality of Life for Elderly People (ProCare4Life, PC4L) project was created to finalize a digital platform with integrated sensors , for monitoring the health status of the elderly subjects with neurodegenerative diseases and comorbidities. In fact, an integrated care platform - able to establish correlations between comorbidities, investigate the intake of different drugs, mitigate potential health risks, study the social variables and promote unified therapeutic procedures or social services - could help patients, caregivers, healthcare professionals and social health workers to monitor various diseases parameters. The main contribution of the PC4L project is to propose an integrated, scalable and interactive care system that can be easily adapted to the reality of various chronic diseases, care institutions and end-user needs, for the benefit of all the actors involved. The main expected results are to improve patients' quality of life, enable an active life and better disease management, support professionals in decision making, facilitate efficient communication between all stakeholders and ensure reliable and secure access to data at the within Europe.


Description:

There is an urgent need to increase the efficiency and sustainability of health and social care systems across Europe, as there is a growing trend in public spending, which is expected to reach 14% of GDP by 2030. The main causes are the aging of the population, and the increase of chronic diseases, including cardiovascular diseases, diabetes, asthma, mental and physical disorders and neurodegenerative conditions. Comorbidities and the confluence of various chronic diseases is increasingly common in the elderly, which increases the need to develop models and tools to improve integrated health systems. Population aging has also led to major reforms in long-term care policies and systems in many European countries, increasing the need for alternatives. This implies the need for help with housework or other practical errands, transportation by doctors or social visits, social companionship, emotional guidance, or help in organizing professional care. In most European countries, much of the care people over 60 receive is informal care. Among the most common chronic diseases in the elderly population, neurocognitive deterioration in the stages of dementia associated with Alzheimer's and Parkinson's are the most disabling. Today, more than 10 million Europeans live with neurocognitive disorders in stages of dementia. This situation can be improved through the creation of an integrated care platform, able to establish correlations between co-morbidities, investigate the use of the intake of different drugs, mitigate potential health risks, study the social variables involved and promote unified therapeutic procedures or social services. This solution could help patients, health professionals and social health workers to monitor various diseases, also considering the social context. In addition, people with chronic diseases face difficulties in their daily life and need specialized care services and care. This situation imposes high burdens on the public budget, which require particular attention to adequately address the sustainability of the social and health system in Europe. The main contribution of the PC4L project is to propose an integrated, scalable and interactive care system that can be easily adapted to the reality of various chronic diseases, care institutions and end-user needs, for the benefit of all the actors involved (e.g. patients, caregivers and health experts). The main expected results are to improve patients' quality of life, enable an active life and better disease management, support professionals in decision making, facilitate efficient communication between all stakeholders and ensure reliable and secure access to data at the within Europe.This study is part of the European multicenter project Horizon 2020, called Personalized Integrated Care Promoting Quality of Life for Elderly People (ProCare4Life, PC4L), which involves several European partners and was created with the aim of finalizing a digital platform with integrated sensors, aimed at home monitoring of health status and treatment of the elderly patient with Parkinson's disease or Alzheimer's disease and other dementias.The PC4L Project was funded by the European Community Horizon 2020 innovation and research program (grant agreement No 875221), for the development of an international research project aimed at exploring the potential of assistive technologies in monitoring the behavior of elderly subjects. The project involves in fact the elderly population suffering from chronic neurological diseases and other comorbidities such as diabetes mellitus and arthritis. This project also aims to provide home support to the caregivers of subjects affected by these diseases. PC4L-Pilot3 represents the third and last large-scale pilot study within the project, where the first one was aimed to explore feasibility and usability of the solution, and the second one investigated the characteristics of the metrics generated by the PC4L platform in real-life conditions. In this pilot study, six clinical centers are involved, in five different European countries (Italy, Spain, Portugal, Romania, Germany), operating in the neurological context both at hospital and home care, as well as daycare centers. An interventional, multicenter, randomized controlled trial will be conducted. The duration of the study per patient at home will be 3 months. Participants admitted to rehabilitation and daycare centers will use the PC4L platform for the entire duration of their stay in the center (not exceeding the 3 months). Patients will be randomized into two groups: experimental group, which will use the PC4L platform for the duration envisaged by the study and will receive notifications and recommendations from the system; and the control group, which will follow the recommendations in paper form for the period envisaged by the study. Caregivers and health professionals will also be involved. In-person assessments will take place at baseline and at the end of the study (3-month follow-up or at discharge from the rehabilitation/daycare program). Demographic and clinical data (age, gender, level of education, professional activity, social support, previous use of technology) will be assesed at baseline. In-person assessments thorugh clinical evaluation will take place at baseline and at the end of the study (3-month follow-up or at discharge from the rehabilitation/daycare program). Clinical assessments are the following: MDS Unified Parkinson's Disease Rating Scale (MDS-UPDRS) and Clinical Dementia Rating Scale (CDRS); Falls Self-Efficacy Scale (FES-I); Berg Balance test; Pittsburgh Sleep quality index score: State-Trait-Anxiety-Inventory (STAI); presence of festination, dysphasia, wandering episodes (last month); EuroQol5D3L; Barthel Index; patient satisfaction and empowerment (PACIC, SAPS); non-programmed medical resources used (last month); Cumulative Illness Rating Scale-Geriatric (CIRS-G) ; adverse events reporting; System Usability Scale (SUS) ; end-of-study survey (Global satisfaction with a 5-point Likert scale; What do you like most/least? Suggestions); end-of-study open questions (Which type of recommendations have you been using? How did you find the recommendations? how it helped in improving your wellbeing? What did you like the most/least?). The PROCare4Life ecosystem consists of: - Wearable sensors - to be used by the patient for monitoring disease-related parameters, in passive and interactive paradigms (e.g., simple bio-measurements as heart rate, complex bio-measurements as motor behavior, passive measurement if initiated automatically, interactive measurement if initiated by patient). The wearable sensor used is the smartwatch Fitbit Versa 2. Patients will use the sensor in the dominant arm. - Fixed sensors (binary sensors) placed on strategic places and rooms in the home environment for assessing motor behaviors and the interaction with the environment (e.g. number of times the patient visits the bathroom, number of times the patient leaves the house). The selected location sensors are the "Xiaomi Aqara Door and Window Sensor (MCCGQ11LM)". - PROCare4Life app for mobile smartphones to process data directly from smartphone (Samsung A20 or other similar model) IMU sensors and GPS and directly from users (e.g., anthropometric data and symptoms / complaints to be provided directly by the patient or by caregiver or social/healthcare professionals, via questionnaires). In particular, the data collected will be: anthropometric data and symptoms, and data related to medication uptake, to be provided directly by the patient or by caregiver, via short questionnaires and annotations. Data related to motor behaviors through GPS and inertial sensors. - A local computer- to collect data from the patients via the sensorial ecosystem which includes several fixed and dynamic sensors such as wearables, binary sensors and/or cameras. (wearable and fixed sensors, and cameras). - PROCare4Life integrated care platform (accessible via Internet browsers) to provide an electronic health record/personal information sheet (fed with data provided by the PROCare4Life ecosystem) and complex interface for personalized interaction/communication between the patients and healthcare professionals. - Tablet or computer to collect data from the patients related to the cognitive abilities, with the use of the cognitive games application that includes six different games about the short-term memory, the visual recognition, understanding, semantic memory, vocabulary, mathematics, among others. This application collects not only the results of the games, but also information related to the user interaction with the application.


Recruitment information / eligibility

Status Completed
Enrollment 558
Est. completion date April 30, 2023
Est. primary completion date April 30, 2023
Accepts healthy volunteers No
Gender All
Age group 65 Years and older
Eligibility Inclusion Criteria: - Patients with a clinical diagnosis of Parkinson's (Hoehn and Yahr between II and IV) or another parkinsonian syndrome, Alzheimer's disease, or another dementia - 65 years of age or more - Willingness to participate in the study - Able and willing to provide informed consent or have a legal representative responsible for the signature Exclusion Criteria: - Presence of fever and / or acute infection such as COVID19 / flu

Study Design


Intervention

Device:
PC4L solutions
Two different versions of the PC4L system will be tested. A fully equipped version and a cloud-based system that requires only a smartphone and a wearable sensor (Fitbit Versa 2). 25% of participants will use the full system, the remaining 75% will use the cloud-based system. As part of the decision support system, the PC4L platform includes a recommendation component. This component collects information from different sources available (directly from sensors, cognitive games, questionnaires, and the multimodal fusion engine), and under clinical and professional guidance, after evaluating the potential improvement or worsening of patients' conditions, issues personalized recommendations to address identified problems. The recommendations relate to the following areas: physical activities; sleep; cognitive; nutrition. These recommendations will generally be sent to the PC4L application on the patients' smartphone, where they will appear as pop-up notifications.

Locations

Country Name City State
Italy Casa di Cura del Policlinico Milan MI

Sponsors (9)

Lead Sponsor Collaborator
Casa di Cura Privata del Policlinico SpA Asociación Parkinson Madrid, Campus Neurológico Sénior, Carol Davila University of Medicine and Pharmacy, International Foundation for Integrated Care, Kineticos, Spitalul Universitar de Urgen?a Bucure?ti, Westfälische Wilhelms-Universität Münster, Wohlfahrtswerk für Baden-Württemberg

Country where clinical trial is conducted

Italy, 

References & Publications (20)

Block VA, Pitsch E, Tahir P, Cree BA, Allen DD, Gelfand JM. Remote Physical Activity Monitoring in Neurological Disease: A Systematic Review. PLoS One. 2016 Apr 28;11(4):e0154335. doi: 10.1371/journal.pone.0154335. eCollection 2016. — View Citation

Broese van Groenou MI, De Boer A. Providing informal care in a changing society. Eur J Ageing. 2016;13(3):271-279. doi: 10.1007/s10433-016-0370-7. Epub 2016 Apr 15. — View Citation

Caspersen CJ, Powell KE, Christenson GM. Physical activity, exercise, and physical fitness: definitions and distinctions for health-related research. Public Health Rep. 1985 Mar-Apr;100(2):126-31. — View Citation

Chastin SF, Baker K, Jones D, Burn D, Granat MH, Rochester L. The pattern of habitual sedentary behavior is different in advanced Parkinson's disease. Mov Disord. 2010 Oct 15;25(13):2114-20. doi: 10.1002/mds.23146. — View Citation

Clarke A. Qualitative research: data analysis techniques. Prof Nurse. 1999 May;14(8):531-3. — View Citation

Crizzle AM, Newhouse IJ. Is physical exercise beneficial for persons with Parkinson's disease? Clin J Sport Med. 2006 Sep;16(5):422-5. doi: 10.1097/01.jsm.0000244612.55550.7d. — View Citation

da Silva PG, Domingues DD, de Carvalho LA, Allodi S, Correa CL. Neurotrophic factors in Parkinson's disease are regulated by exercise: Evidence-based practice. J Neurol Sci. 2016 Apr 15;363:5-15. doi: 10.1016/j.jns.2016.02.017. Epub 2016 Feb 10. — View Citation

Fan X, Wang D, Hellman B, Janssen MF, Bakker G, Coghlan R, Hursey A, Matthews H, Whetstone I. Assessment of Health-Related Quality of Life between People with Parkinson's Disease and Non-Parkinson's: Using Data Drawn from the '100 for Parkinson's' Smartphone-Based Prospective Study. Int J Environ Res Public Health. 2018 Nov 13;15(11):2538. doi: 10.3390/ijerph15112538. — View Citation

Ferri CP, Prince M, Brayne C, Brodaty H, Fratiglioni L, Ganguli M, Hall K, Hasegawa K, Hendrie H, Huang Y, Jorm A, Mathers C, Menezes PR, Rimmer E, Scazufca M; Alzheimer's Disease International. Global prevalence of dementia: a Delphi consensus study. Lancet. 2005 Dec 17;366(9503):2112-7. doi: 10.1016/S0140-6736(05)67889-0. — View Citation

GBD 2016 Parkinson's Disease Collaborators. Global, regional, and national burden of Parkinson's disease, 1990-2016: a systematic analysis for the Global Burden of Disease Study 2016. Lancet Neurol. 2018 Nov;17(11):939-953. doi: 10.1016/S1474-4422(18)30295-3. Epub 2018 Oct 1. Erratum In: Lancet Neurol. 2021 Dec;20(12):e7. — View Citation

Hillman CH, Erickson KI, Kramer AF. Be smart, exercise your heart: exercise effects on brain and cognition. Nat Rev Neurosci. 2008 Jan;9(1):58-65. doi: 10.1038/nrn2298. — View Citation

Hou L, Chen W, Liu X, Qiao D, Zhou FM. Exercise-Induced Neuroprotection of the Nigrostriatal Dopamine System in Parkinson's Disease. Front Aging Neurosci. 2017 Nov 3;9:358. doi: 10.3389/fnagi.2017.00358. eCollection 2017. — View Citation

Keus SH, Bloem BR, Hendriks EJ, Bredero-Cohen AB, Munneke M; Practice Recommendations Development Group. Evidence-based analysis of physical therapy in Parkinson's disease with recommendations for practice and research. Mov Disord. 2007 Mar 15;22(4):451-60; quiz 600. doi: 10.1002/mds.21244. — View Citation

Kwakkel G, de Goede CJ, van Wegen EE. Impact of physical therapy for Parkinson's disease: a critical review of the literature. Parkinsonism Relat Disord. 2007;13 Suppl 3:S478-87. doi: 10.1016/S1353-8020(08)70053-1. — View Citation

Lauze M, Daneault JF, Duval C. The Effects of Physical Activity in Parkinson's Disease: A Review. J Parkinsons Dis. 2016 Oct 19;6(4):685-698. doi: 10.3233/JPD-160790. — View Citation

Lorenz K, Freddolino PP, Comas-Herrera A, Knapp M, Damant J. Technology-based tools and services for people with dementia and carers: Mapping technology onto the dementia care pathway. Dementia (London). 2019 Feb;18(2):725-741. doi: 10.1177/1471301217691617. Epub 2017 Feb 8. — View Citation

Melin J, Bonn SE, Pendrill L, Trolle Lagerros Y. A Questionnaire for Assessing User Satisfaction With Mobile Health Apps: Development Using Rasch Measurement Theory. JMIR Mhealth Uhealth. 2020 May 26;8(5):e15909. doi: 10.2196/15909. — View Citation

Petzinger GM, Fisher BE, McEwen S, Beeler JA, Walsh JP, Jakowec MW. Exercise-enhanced neuroplasticity targeting motor and cognitive circuitry in Parkinson's disease. Lancet Neurol. 2013 Jul;12(7):716-26. doi: 10.1016/S1474-4422(13)70123-6. — View Citation

Rabiee F. Focus-group interview and data analysis. Proc Nutr Soc. 2004 Nov;63(4):655-60. doi: 10.1079/pns2004399. — View Citation

Warburton DE, Nicol CW, Bredin SS. Health benefits of physical activity: the evidence. CMAJ. 2006 Mar 14;174(6):801-9. doi: 10.1503/cmaj.051351. — View Citation

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

Outcome

Type Measure Description Time frame Safety issue
Primary EuroQol5D3L Improvement of the quality of life in the 'experimental' group of patients who use the PC4L platform for a period of three months, compared to the control group, equal to 10% according to the scale EuroQol5D3L: the primary outcome of the study will be the difference in quality of life between groups, measured by the EuroQol5D3L scale at the end of the study.
Sample size calculation was based on a previous study (Fan X, et al. Assessment of Health-Related Quality of Life between People with Parkinson's Disease and Non-Parkinson's: Using Data Drawn from the '100 for Parkinson's' Smartphone-Based Prospective Study. Int J Environ Res Public Health. 2018) that compared the quality of life of two groups of patients. It was estimated that a total of 558 patients, 279 per study group, will be necessary to achieve an improvement of 10% in EuroQol5D3L, with 95% power.
up to three months
Secondary MDS-Unified Parkinson's Disease Rating Scale (MDS-UPDRS) Change in the score of MDS-UPDRS measured at baseline and at the end of the study. Higher scores mean worse outcome. up to three months
Secondary CLINICAL DEMENTIA RATING SCALE (CDRS) Change in the score of CDRS measured at baseline and at the end of the study. It yields a single score on a scale of 0-5, where higher scores mean worse outcome. up to three months
Secondary Falls Efficacy Scale International (FES-I) Change in the score of FES-I measured at baseline and at the end of the study. It yields a single score on a scale of 16-64, where higher scores mean worse outcome. up to three months
Secondary Pittsburgh Sleep quality index (PSQI) Change in the score of PSQI measured at baseline and at the end of the study. It yields a single score on a scale of 0-21, where higher scores mean worse outcome. up to three months
Secondary State-Trait-Anxiety-Inventory (STAI) Change in the score of STAI measured at baseline and at the end of the study. It yields a single score on a scale of 20-80, where higher scores mean worse outcome. up to three months
Secondary Barthel Index (BI) Change in the score of BI measured at baseline and at the end of the study. It yields a single score on a scale of 0-100, where higher scores mean better outcome. up to three months
Secondary Patient assessment of chronic illness care (PACIC) Change in the score of PACIC measured at baseline and at the end of the study. It yields a single score on a scale of 0-5, where higher scores mean better outcome. up to three months
Secondary Short Assessment of Patient Satisfaction (SAPS) Change in the score of SAPS measured at baseline and at the end of the study. It yields a single score on a scale of 0-28, where higher scores mean better outcome. up to three months
Secondary Cumulative Illness Rating Scale-Geriatric (CIRS-G) Change in the score of CIRS-G measured at baseline and at the end of the study .
It yields a single score on a scale of 0-56, where higher scores mean worse outcome.
up to three months
Secondary System Usability Scale (SUS) SUS is used to measure how easy or difficult the proposed system is to use. We will compare the usability of two different versions of the PC4L system (fully equipped and cloud-based solution).
It yields a single score on a scale of 0-100, where higher scores mean better outcome.
up to three months
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