Ignite Creation Date:
2024-05-06 @ 5:16 PM
Last Modification Date:
2024-10-26 @ 2:25 PM
Study NCT ID:
NCT05247294
Status:
COMPLETED
Last Update Posted:
2022-02-18
First Post:
2022-01-26
Brief Title:
Assessment of Fluctuating Parkinsons Disease With Sensor-based Home Monitoring
Sponsor:
Sheba Medical Center
Organization:
Sheba Medical Center
Study Overview
Official Title:
Assessment of Fluctuating Parkinsons Disease With Sensor-based Home Monitoring
Status:
COMPLETED
Status Verified Date:
2022-02
Last Known Status:
None
Delayed Posting:
No
If Stopped, Why?:
Not Stopped
Has Expanded Access:
False
If Expanded Access, NCT#:
N/A
Has Expanded Access, NCT# Status:
N/A
Acronym:
None
Brief Summary:
The aim of this study is to implement home-based monitoring HBM using remote-capture wearable devices and patient reported outcomes PROs in a rather homogeneous subgroup of advanced Parkinsons Disease PD patients suffering from significant motor fluctuations MF and Levodopa-induced dyskinesia LID over a two-week period
The investigators aim to provide a more comprehensive picture of patient symptoms severity and fluctuations and compare these data to interview-derived clinical data
The investigators aim to provide a more comprehensive picture of patient symptoms severity and fluctuations and compare these data to interview-derived clinical data
Detailed Description:
Parkinsons Disease PD is a neuro-degenerative disorder affecting millions of people worldwide PD is associated with both motor and non-motor symptoms that affect patients functioning and Quality of life
The motor symptoms consist of tremor rigidity bradykinesia and gait impairments Additional important motor symptoms that are associated with chronic Levodopa therapy are levodopa-induced dyskinesia and motor fluctuations
Currently the accepted clinical measurement of PD symptom severity is the Movement Disorders Society-unified Parkinsons disease rating scale MDS-UPDRS which is based in part on subjective and potentially recall-based reports by the patients and on semi-objective observations by the clinician
On average PD patients see their treating neurologist for in-clinic visits twice a year These visits are limited in time and may leave some issues unattended regarding all aspects of disease and overall health This may adversely affect the decision making process and the prescribed treatment plan
In order to understand the accurate clinical status of patients particularly in the motor fluctuating stage of PD and to monitor results of intervention the treating neurologist may need a more comprehensive picture of their patients symptoms and lives during protracted periods and real life in their home environment
The HBM apparatus used in this study will consist of a smartwatch Apple watch and a smartphone Apple iPhone 8 The phone is pre-installed with an application which is part of the Intel Pharma Analytics Platform The mobile app was designed by usability experts and was tested with patients to ensure ease of use by an elderly population with PD
The Intel platform is enhanced by a compendium of algorithms to extract clinical insights from the raw sensor data Passive sensor data is transferred from the study smartwatch The data includes three measures based on the smartwatch data activity level dyskinesia and tremor
The study will be conducted at Movement Disorders Institute at Sheba Medical Center and will include two clinic visits and a 2-week HBM phase
The first clinic visit as well as the 2-week home period will include the following daily assessments once in off state and once in on state
1 3- meter Timed up and go test 3mTUG
2 Finger tapping on smartphone 10 seconds both hands
3 Hand tremor assessment postural tremor outstretched 30 sec rest tremor 30 sec
4 Pronation-supination
In addition ePROs are captured with electronic home diaries Participants will report the severity of PD symptoms they are experiencing on a 5-point scale throughout the day For the duration of waking hours participants will receive a notification on their phone to input information about their ONOFF state every 30 minutes
The primary objective is to correlate severity of fluctuating motor symptoms in PD patients using the Intel Pharma Analytics Platforms derived passive sensor data percentage of daily tremor time and percentage of daily dyskinesia time percentage of daily inactivity in an exploratory manner with concomitant assessment of motor fluctuations and dyskinesia using the applications based electronic symptom diary and data of tremor off time and dyskinesia using the MDS-UPDRS scale
The motor symptoms consist of tremor rigidity bradykinesia and gait impairments Additional important motor symptoms that are associated with chronic Levodopa therapy are levodopa-induced dyskinesia and motor fluctuations
Currently the accepted clinical measurement of PD symptom severity is the Movement Disorders Society-unified Parkinsons disease rating scale MDS-UPDRS which is based in part on subjective and potentially recall-based reports by the patients and on semi-objective observations by the clinician
On average PD patients see their treating neurologist for in-clinic visits twice a year These visits are limited in time and may leave some issues unattended regarding all aspects of disease and overall health This may adversely affect the decision making process and the prescribed treatment plan
In order to understand the accurate clinical status of patients particularly in the motor fluctuating stage of PD and to monitor results of intervention the treating neurologist may need a more comprehensive picture of their patients symptoms and lives during protracted periods and real life in their home environment
The HBM apparatus used in this study will consist of a smartwatch Apple watch and a smartphone Apple iPhone 8 The phone is pre-installed with an application which is part of the Intel Pharma Analytics Platform The mobile app was designed by usability experts and was tested with patients to ensure ease of use by an elderly population with PD
The Intel platform is enhanced by a compendium of algorithms to extract clinical insights from the raw sensor data Passive sensor data is transferred from the study smartwatch The data includes three measures based on the smartwatch data activity level dyskinesia and tremor
The study will be conducted at Movement Disorders Institute at Sheba Medical Center and will include two clinic visits and a 2-week HBM phase
The first clinic visit as well as the 2-week home period will include the following daily assessments once in off state and once in on state
1 3- meter Timed up and go test 3mTUG
2 Finger tapping on smartphone 10 seconds both hands
3 Hand tremor assessment postural tremor outstretched 30 sec rest tremor 30 sec
4 Pronation-supination
In addition ePROs are captured with electronic home diaries Participants will report the severity of PD symptoms they are experiencing on a 5-point scale throughout the day For the duration of waking hours participants will receive a notification on their phone to input information about their ONOFF state every 30 minutes
The primary objective is to correlate severity of fluctuating motor symptoms in PD patients using the Intel Pharma Analytics Platforms derived passive sensor data percentage of daily tremor time and percentage of daily dyskinesia time percentage of daily inactivity in an exploratory manner with concomitant assessment of motor fluctuations and dyskinesia using the applications based electronic symptom diary and data of tremor off time and dyskinesia using the MDS-UPDRS scale
Study Oversight
Has Oversight DMC:
None
Is a FDA Regulated Drug?:
False
Is a FDA Regulated Device?:
False
Is an Unapproved Device?:
None
Is a PPSD?:
None
Is a US Export?:
None
Is an FDA AA801 Violation?:
None