Real-PD Trial: Development of Clinical Prognostic Models for Parkinson's Disease

NCT ID: NCT02474329

Last Updated: 2021-12-06

Study Results

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Basic Information

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Recruitment Status

COMPLETED

Total Enrollment

304 participants

Study Classification

OBSERVATIONAL

Study Start Date

2015-07-31

Study Completion Date

2016-11-30

Brief Summary

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Background: Long-term management of Parkinson's disease (PD) does not reach its full potential due to lack of knowledge about disease progression. The Real-PD study aim to evaluate the feasibility and compliance of usage of wearable sensors in PD patients in real life. Moreover, an explorative analysis concerning activity level, medication intake and mood will be done.

Methods: Overall, 1000 PD patients and 250 physiotherapist will be enrolled in this observational study. Dutch PD patients will be recruited across the country and an assessment will be performed using a short version of the Parkinson's Progression Markers Initiative (PPMI) protocol. Moreover, participants will wear a set of medical devices (Pebble Smartwatch, fall detector) and they will use a smartphone with The Fox Insight App (Android app), 24/7, during 13 weeks. Primary measures of interest are: 1) physical activity, falls and tremor, measured by the axial accelerometers embedded in the Pebble watch and fall detector; and 2) medication intake and mood reports measured by patients' self-report in the Android app. To measure motor impact, an assessment will be performed by physiotherapists who are all certified to perform the Movement Disorders Society Unified Parkinson's Disease Rating Scale (MDS-UPDRS).

Discussion: Management of PD patients is complex and appears to be a challenging task for health care professionals. The main reason is the lack of knowledge in the disease pattern. This issue could be solved by a long term follow-up of patients' during their everyday life, and wearable medical devices can act as a way to collect data about every day life activities. Therefore, the Real-PD study will be a first contribution in increasing the lack of knowledge in disease progression, developing a new medical decision system and improving PD patients' care.

Detailed Description

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Rationale: Today's management of patients with a chronic disorder like Parkinson's disease (PD) is imperfect. The understanding of clinical profiles is based on observations in small, selective populations with brief follow-up. Moreover, treatment decisions are based on averaged population results that may not apply to a specific individual context. These drawbacks will be addressed with a "big data" approach. Ambulatory sensors will be used as an objective measure of patients' performance under everyday circumstances, for longer periods of time. The researchers aim to explore the potential of using longitudinal ambulatory data to enrich a standardized clinical dataset, which reflects current clinical practice for the assessment of disease status.

Objective: The study will include a total of 250 physiotherapists and 1000 patients. The aims of this study are: (1) to perform "big data" analyses on the raw sensor data, in relation to concurrently acquired clinical data in these patients (limited version of the PPMI (Parkinson's Progression Markers Initiative) protocol) to develop patient profiles; and (2) to correlate the ambulatory sensor data to simple self-assessments made during follow-up.

Study design: Observational descriptive study.

Study population: Dutch Parkinson patients, male or female, age 30 years or older, with PD diagnosis given by a physician, and own a suitable smartphone.

lntervention: 250 ParkinsonNet physiotherapists and 1000 eligible patients will be included in this study. Patients and physiotherapists will be recruited in 5 consecutive cohorts based on geographic region. Patients will be asked to wear a smartwatch and a pendant movement sensor, both with triaxial accelerometers, during day and night, for a period of 13 weeks. Additionally, a self-monitoring App on a smartphone is used, where the patient reports when (s)he takes any PD medication. An additional, optional button allows the patient to report general feeling. During the 13 week follow-up, trained physiotherapists will perform a standardized clinical assessment, based on the PPMI protocol (www.ppmi-info.org) for every included patient. This assessment will last for 60 minutes. The smartphone is used to transmit data from the watch to a cloud-based data platform. lntel developed this dedicated data analysis platform for ambulatory data. lntel will receive coded data only.

Main study parameters/endpoints: Study endpoints include parameters registered with the smartwatch, the pendant movement sensor, the self-monitoring app and collected with the PPMI assessment. The smartwatch data provides, after data processing, a measure for the level of physical activity during the day. Falls will be registered with the pendant movement sensor. Medication intake and mood are registered using the smartphone. Finally, PPMI assessment includes assessment of motor symptoms, cognition, depression, sleep and daily activity. Correlations will be determined between the above mentioned parameters.

Nature and extent of the burden and risks associated with participation, benefit and group relatedness: First, participants are asked to wear the devices 24/7 and data will be recorded continuously, for a total duration of 13 weeks. Second, data will be transmitted to a data platform developed and managed by lntel, on behalf of the Michael J. Fox Foundation for Parkinson's Research. To access these data, researchers can grant permission for research purposes, provided by Michael J. Fox Foundation. Patients will be asked for permission to share the raw coded data for dissemination to the research community, analysis and use in future publications. Participation in the study warrants that patients provide written permission for this.

Conditions

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Parkinson's Disease

Keywords

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Parkinson's disease Ambulatory monitoring Disease progression

Study Design

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Observational Model Type

COHORT

Study Time Perspective

PROSPECTIVE

Study Groups

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Cohort 1

Dutch Parkinson's patients resident in the region of Noord-Holland whose fulfill the eligibility criteria.

Interventions/Exposures to be administered:

1. PPMI (Parkinson's Progression Markers Initiative) protocol Trained physiotherapists will perform once a standardized clinical assessment to every included patient. This assessment will last for 60 minutes, and it will be done once.
2. Fox Insight self-monitoring android app and falls detector Patients will wear a smartwatch and a pendant movement sensor during day and night, for a period of 13 weeks. Additionally, a self-monitoring App on a Smartphone is used, where the patient reports when (s)he takes any PD medication. An additional, optional button allows the patient to report general feeling.

Clinical assessment

Intervention Type OTHER

During the 13 week follow-up, trained physiotherapists will perform a standardized clinical assessment, based on the PPMI protocol (www.ppmi-info.org) for every included patient. This assessment will last for 60 minutes, and it will be done once.

Fox Insight self-monitoring android app and falls detector

Intervention Type DEVICE

Patients will be asked to wear a smartwatch and a pendant movement sensor, both with triaxial accelerometers, during day and night, for a period of 13 weeks. Additionally, a self-monitoring App on a Smartphone is used, where the patient reports when (s)he takes any PD medication. An additional, optional button allows the patient to report general feeling.

Cohort 2

Dutch Parkinson's patients resident in the region of Zuid-Holland whose fulfill the eligibility criteria.

Interventions/Exposures to be administered:

1. PPMI (Parkinson's Progression Markers Initiative) protocol Trained physiotherapists will perform once a standardized clinical assessment to every included patient. This assessment will last for 60 minutes, and it will be done once.
2. Fox Insight self-monitoring android app and falls detector Patients will wear a smartwatch and a pendant movement sensor during day and night, for a period of 13 weeks. Additionally, a self-monitoring App on a Smartphone is used, where the patient reports when (s)he takes any PD medication. An additional, optional button allows the patient to report general feeling.

Clinical assessment

Intervention Type OTHER

During the 13 week follow-up, trained physiotherapists will perform a standardized clinical assessment, based on the PPMI protocol (www.ppmi-info.org) for every included patient. This assessment will last for 60 minutes, and it will be done once.

Fox Insight self-monitoring android app and falls detector

Intervention Type DEVICE

Patients will be asked to wear a smartwatch and a pendant movement sensor, both with triaxial accelerometers, during day and night, for a period of 13 weeks. Additionally, a self-monitoring App on a Smartphone is used, where the patient reports when (s)he takes any PD medication. An additional, optional button allows the patient to report general feeling.

Cohort 3

Dutch Parkinson's patients resident in the region of Gelderland and Utrecht whose fulfill the eligibility criteria.

Interventions/Exposures to be administered:

1. PPMI (Parkinson's Progression Markers Initiative) protocol Trained physiotherapists will perform once a standardized clinical assessment to every included patient. This assessment will last for 60 minutes, and it will be done once.
2. Fox Insight self-monitoring android app and falls detector Patients will wear a smartwatch and a pendant movement sensor during day and night, for a period of 13 weeks. Additionally, a self-monitoring App on a Smartphone is used, where the patient reports when (s)he takes any PD medication. An additional, optional button allows the patient to report general feeling.

Clinical assessment

Intervention Type OTHER

During the 13 week follow-up, trained physiotherapists will perform a standardized clinical assessment, based on the PPMI protocol (www.ppmi-info.org) for every included patient. This assessment will last for 60 minutes, and it will be done once.

Fox Insight self-monitoring android app and falls detector

Intervention Type DEVICE

Patients will be asked to wear a smartwatch and a pendant movement sensor, both with triaxial accelerometers, during day and night, for a period of 13 weeks. Additionally, a self-monitoring App on a Smartphone is used, where the patient reports when (s)he takes any PD medication. An additional, optional button allows the patient to report general feeling.

Cohort 4

Dutch Parkinson's patients resident in the region of Groningen, Friesland, Drenthe and Overijssel whose fulfill the eligibility criteria.

Interventions/Exposures to be administered:

1. PPMI (Parkinson's Progression Markers Initiative) protocol Trained physiotherapists will perform once a standardized clinical assessment to every included patient. This assessment will last for 60 minutes, and it will be done once.
2. Fox Insight self-monitoring android app and falls detector Patients will wear a smartwatch and a pendant movement sensor during day and night, for a period of 13 weeks. Additionally, a self-monitoring App on a Smartphone is used, where the patient reports when (s)he takes any PD medication. An additional, optional button allows the patient to report general feeling.

Clinical assessment

Intervention Type OTHER

During the 13 week follow-up, trained physiotherapists will perform a standardized clinical assessment, based on the PPMI protocol (www.ppmi-info.org) for every included patient. This assessment will last for 60 minutes, and it will be done once.

Fox Insight self-monitoring android app and falls detector

Intervention Type DEVICE

Patients will be asked to wear a smartwatch and a pendant movement sensor, both with triaxial accelerometers, during day and night, for a period of 13 weeks. Additionally, a self-monitoring App on a Smartphone is used, where the patient reports when (s)he takes any PD medication. An additional, optional button allows the patient to report general feeling.

Cohort 5

Dutch Parkinson's patients resident in the region of Zeeland, Noord-Brabant and Limburg whose fulfill the eligibility criteria.

Interventions/Exposures to be administered:

1. PPMI (Parkinson's Progression Markers Initiative) protocol Trained physiotherapists will perform once a standardized clinical assessment to every included patient. This assessment will last for 60 minutes, and it will be done once.
2. Fox Insight self-monitoring android app and falls detector Patients will wear a smartwatch and a pendant movement sensor during day and night, for a period of 13 weeks. Additionally, a self-monitoring App on a Smartphone is used, where the patient reports when (s)he takes any PD medication. An additional, optional button allows the patient to report general feeling.

Clinical assessment

Intervention Type OTHER

During the 13 week follow-up, trained physiotherapists will perform a standardized clinical assessment, based on the PPMI protocol (www.ppmi-info.org) for every included patient. This assessment will last for 60 minutes, and it will be done once.

Fox Insight self-monitoring android app and falls detector

Intervention Type DEVICE

Patients will be asked to wear a smartwatch and a pendant movement sensor, both with triaxial accelerometers, during day and night, for a period of 13 weeks. Additionally, a self-monitoring App on a Smartphone is used, where the patient reports when (s)he takes any PD medication. An additional, optional button allows the patient to report general feeling.

Interventions

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Clinical assessment

During the 13 week follow-up, trained physiotherapists will perform a standardized clinical assessment, based on the PPMI protocol (www.ppmi-info.org) for every included patient. This assessment will last for 60 minutes, and it will be done once.

Intervention Type OTHER

Fox Insight self-monitoring android app and falls detector

Patients will be asked to wear a smartwatch and a pendant movement sensor, both with triaxial accelerometers, during day and night, for a period of 13 weeks. Additionally, a self-monitoring App on a Smartphone is used, where the patient reports when (s)he takes any PD medication. An additional, optional button allows the patient to report general feeling.

Intervention Type DEVICE

Other Intervention Names

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PPMI (Parkinson's Progression Markers Initiative) protocol Pebble smartphone Philips falls detector

Eligibility Criteria

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Inclusion Criteria

1. Currently own and use a smartphone device with access to the Internet
2. 30 years of age or older;
3. Diagnosed with Parkinson's disease by a physician;
4. Able to walk without any assistance.
Minimum Eligible Age

30 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

No

Sponsors

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Michael J. Fox Foundation for Parkinson's Research

OTHER

Sponsor Role collaborator

Philips Electronics Nederland B.V. acting through Philips CTO organization

INDUSTRY

Sponsor Role collaborator

Intel Corporation

INDUSTRY

Sponsor Role collaborator

Radboud University Medical Center

OTHER

Sponsor Role lead

Responsible Party

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Responsibility Role SPONSOR

Principal Investigators

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Bastiaan R Bloem, Prof. Dr.

Role: PRINCIPAL_INVESTIGATOR

Radboud University Medical Center

Locations

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Cohort 1

Multiple Locations, North Holland, Netherlands

Site Status

Countries

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Netherlands

References

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Parkka J, Ermes M, Korpipaa P, Mantyjarvi J, Peltola J, Korhonen I. Activity classification using realistic data from wearable sensors. IEEE Trans Inf Technol Biomed. 2006 Jan;10(1):119-28. doi: 10.1109/titb.2005.856863.

Reference Type BACKGROUND
PMID: 16445257 (View on PubMed)

Hobert MA, Maetzler W, Aminian K, Chiari L. Technical and clinical view on ambulatory assessment in Parkinson's disease. Acta Neurol Scand. 2014 Sep;130(3):139-47. doi: 10.1111/ane.12248. Epub 2014 Apr 1.

Reference Type BACKGROUND
PMID: 24689772 (View on PubMed)

Maetzler W, Domingos J, Srulijes K, Ferreira JJ, Bloem BR. Quantitative wearable sensors for objective assessment of Parkinson's disease. Mov Disord. 2013 Oct;28(12):1628-37. doi: 10.1002/mds.25628. Epub 2013 Sep 12.

Reference Type BACKGROUND
PMID: 24030855 (View on PubMed)

Patel S, Lorincz K, Hughes R, Huggins N, Growdon J, Standaert D, Akay M, Dy J, Welsh M, Bonato P. Monitoring motor fluctuations in patients with Parkinson's disease using wearable sensors. IEEE Trans Inf Technol Biomed. 2009 Nov;13(6):864-73. doi: 10.1109/TITB.2009.2033471. Epub 2009 Oct 20.

Reference Type BACKGROUND
PMID: 19846382 (View on PubMed)

Patel S, Chen BR, Mancinelli C, Paganoni S, Shih L, Welsh M, Dy J, Bonato P. Longitudinal monitoring of patients with Parkinson's disease via wearable sensor technology in the home setting. Annu Int Conf IEEE Eng Med Biol Soc. 2011;2011:1552-5. doi: 10.1109/IEMBS.2011.6090452.

Reference Type BACKGROUND
PMID: 22254617 (View on PubMed)

Tsanas A, Little MA, McSharry PE, Ramig L. Using the cellular mobile telephone network to remotely monitor parkinsons disease symptom severity. IEEE Transactions on Biomedical Engineering. 2012.

Reference Type BACKGROUND

Arora S, Venkataraman V, Donohue S, Biglan KM, Dorsey ER, Little MA, editors. High accuracy discrimination of Parkinson's disease participants from healthy controls using smartphones. Acoustics, Speech and Signal Processing (ICASSP), 2014 IEEE International Conference on; 2014: IEEE.

Reference Type BACKGROUND

Pastorino M, Arredondo M, Cancela J, Guillen S, editors. Wearable sensor network for health monitoring: the case of Parkinson disease. Journal of Physics: Conference Series; 2013: IOP Publishing.

Reference Type BACKGROUND

Sharma V, Mankodiya K, De La Torre F, Zhang A, Ryan N, Ton TG, et al. SPARK: Personalized Parkinson Disease Interventions through Synergy between a Smartphone and a Smartwatch. Design, User Experience, and Usability User Experience Design for Everyday Life Applications and Services: Springer; 2014. p. 103-14.

Reference Type BACKGROUND

Tzallas AT, Tsipouras MG, Rigas G, Tsalikakis DG, Karvounis EC, Chondrogiorgi M, Psomadellis F, Cancela J, Pastorino M, Waldmeyer MT, Konitsiotis S, Fotiadis DI. PERFORM: a system for monitoring, assessment and management of patients with Parkinson's disease. Sensors (Basel). 2014 Nov 11;14(11):21329-57. doi: 10.3390/s141121329.

Reference Type BACKGROUND
PMID: 25393786 (View on PubMed)

Lakshminarayana R, Wang D, Burn D, Chaudhuri KR, Cummins G, Galtrey C, Hellman B, Pal S, Stamford J, Steiger M, Williams A; SMART-PD Investigators. Smartphone- and internet-assisted self-management and adherence tools to manage Parkinson's disease (SMART-PD): study protocol for a randomised controlled trial (v7; 15 August 2014). Trials. 2014 Sep 25;15:374. doi: 10.1186/1745-6215-15-374.

Reference Type BACKGROUND
PMID: 25257518 (View on PubMed)

Gschwind YJ, Eichberg S, Marston HR, Ejupi A, Rosario Hd, Kroll M, Drobics M, Annegarn J, Wieching R, Lord SR, Aal K, Delbaere K. ICT-based system to predict and prevent falls (iStoppFalls): study protocol for an international multicenter randomized controlled trial. BMC Geriatr. 2014 Aug 20;14:91. doi: 10.1186/1471-2318-14-91.

Reference Type BACKGROUND
PMID: 25141850 (View on PubMed)

Silva de Lima AL, Hahn T, de Vries NM, Cohen E, Bataille L, Little MA, Baldus H, Bloem BR, Faber MJ. Large-Scale Wearable Sensor Deployment in Parkinson's Patients: The Parkinson@Home Study Protocol. JMIR Res Protoc. 2016 Aug 26;5(3):e172. doi: 10.2196/resprot.5990.

Reference Type DERIVED
PMID: 27565186 (View on PubMed)

Other Identifiers

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NL53034.091.41

Identifier Type: -

Identifier Source: org_study_id