Ignite Creation Date:
2025-12-24 @ 9:28 PM
Ignite Modification Date:
2025-12-25 @ 7:14 PM
Study NCT ID:
NCT04467632
Status:
WITHDRAWN
Last Update Posted:
2020-07-13
First Post:
2019-10-14
Is NOT Gene Therapy:
False
Has Adverse Events:
False
Brief Title:
Circadian & Homeostatic Synchronization Effect on Waking Mobility in Parkinson's Disease
Sponsor:
University Hospital Center of Martinique
Organization:
Study Overview
Official Title:
Circadian & Homeostatic Synchronization Effect on Waking Mobility in Parkinson's Disease: a Feasibility Study
Status:
WITHDRAWN
Status Verified Date:
2019-10
Last Known Status:
None
Delayed Posting:
No
If Stopped, Why?:
The principal investigator left the hospital
Has Expanded Access:
False
If Expanded Access, NCT#:
N/A
Has Expanded Access, NCT# Status:
N/A
Acronym:
Synch Fit
Brief Summary:
Sleep benefit (SB) consists of a spontaneous, transient and inconsistent improvement of the mobility occurring on morning awakening in approximately 40% of Parkinson's disease (PD) patients, before taking the first morning dose of dopaminergic drugs.
The SB could represent a pathway for the development of new therapeutic strategies for motor symptoms in PD.
Being a seemingly unpredictable phenomenon and a great variability daily, inter- and intra-subject, the SB study requires multiple and repeated assessments of mobility for several days. An experimental home setting would be optimal for this purpose in terms of cost-effectiveness and patient acceptability.
In addition, since the extent and nature of SB have not been well characterized so far, and the magnitude of its variability is unknown, a reliable assessment method, independent of observers and situation, the SB is a requirement of further research in this area.
A recently developed technique combining machine learning algorithms with wireless portable sensors (accelerometers and gyroscopes) and software applications could be particularly promising for characterizing the complexity and multiplicity of SBs in. With this technique, repeated and multiple assessments of mobility can be performed in the homes of patients without the constant presence of a researcher.
This approach offers several advantages in terms of cost-effectiveness, feasibility and acceptability of study protocols by patients. It also improves the ecological validity of subjective and objective estimates of mobility in these patients.
The investigators chose to conduct this preliminary study on patients with PD rather than on healthy subjects, because SB is a phenomenon that has been described so far only in this population. Investigators also consider that the feasibility of the study will depend mainly on the patients' ability to move and the context of their own illness.
SB is a phenomenon induced by sleep. The propensity and timing of sleep depend on the coordinated interaction of the duration of the previous awakening (homeostatic process) and a circadian signal (circadian process). In order to better understand SB, it is necessary to study the reciprocal influences of the circadian and homeostatic process.
Investigators have devised a new paradigm to "shift" the circadian process phase around the homeostatic process, maintained under constant conditions, in order to observe the effect of the synchronism or desynchronization of these two processes on the awakening mobility of patients with an MP. This experimental approach was approved by Professor Aleksandar Videnovic (Harvard University School of Medicine, USA), opinion leader on circadian rhythmicity in the MP and scientific collaborator of this study.
As a first step, the investigators plan to implement a technology-assisted home-based methodology, to validate it in PD patients and to verify the logistic feasibility of this method-assisted approach in a small group of patients, in order to to be able to apply this paradigm in larger scientific projects.
The SB could represent a pathway for the development of new therapeutic strategies for motor symptoms in PD.
Being a seemingly unpredictable phenomenon and a great variability daily, inter- and intra-subject, the SB study requires multiple and repeated assessments of mobility for several days. An experimental home setting would be optimal for this purpose in terms of cost-effectiveness and patient acceptability.
In addition, since the extent and nature of SB have not been well characterized so far, and the magnitude of its variability is unknown, a reliable assessment method, independent of observers and situation, the SB is a requirement of further research in this area.
A recently developed technique combining machine learning algorithms with wireless portable sensors (accelerometers and gyroscopes) and software applications could be particularly promising for characterizing the complexity and multiplicity of SBs in. With this technique, repeated and multiple assessments of mobility can be performed in the homes of patients without the constant presence of a researcher.
This approach offers several advantages in terms of cost-effectiveness, feasibility and acceptability of study protocols by patients. It also improves the ecological validity of subjective and objective estimates of mobility in these patients.
The investigators chose to conduct this preliminary study on patients with PD rather than on healthy subjects, because SB is a phenomenon that has been described so far only in this population. Investigators also consider that the feasibility of the study will depend mainly on the patients' ability to move and the context of their own illness.
SB is a phenomenon induced by sleep. The propensity and timing of sleep depend on the coordinated interaction of the duration of the previous awakening (homeostatic process) and a circadian signal (circadian process). In order to better understand SB, it is necessary to study the reciprocal influences of the circadian and homeostatic process.
Investigators have devised a new paradigm to "shift" the circadian process phase around the homeostatic process, maintained under constant conditions, in order to observe the effect of the synchronism or desynchronization of these two processes on the awakening mobility of patients with an MP. This experimental approach was approved by Professor Aleksandar Videnovic (Harvard University School of Medicine, USA), opinion leader on circadian rhythmicity in the MP and scientific collaborator of this study.
As a first step, the investigators plan to implement a technology-assisted home-based methodology, to validate it in PD patients and to verify the logistic feasibility of this method-assisted approach in a small group of patients, in order to to be able to apply this paradigm in larger scientific projects.
Detailed Description:
Parkinson's disease is a common neurodegenerative disorder touching 1.5% of the general population over 60 year-old and featuring impaired mobility with high impact on daily living and quality of life of the patients and their caregivers. Fourty percent of the patients with Parkinson's disease (PD) report inconstant, prominent, spontaneous, transitory improvement in mobility occurring on morning awakening, before taking their first morning dose of dopaminergic medications. This apparently unpredictable, highly variable, sleep-related phenomenon has been named "Sleep Benefit" (SB) by the scientists.
SB is a promising track to follow to develop novel therapeutic strategies for motor symptoms in PD. An innovative approach could be to induce modifications of mobility by influencing sleep regulation in PD patients in experimental settings.
Sleep propensity and timing depend on the coordinated interaction of the duration of preceding wakefulness (homeostatic component) and on a circadian signal (circadian component). Reciprocal interactions between homeostatic and circadian processes preside to internal synchrony of many physiological processes. We hypothesize SB to depend on serendipitous optimal synchronization between circadian and homeostatic process on morning awakening. As SB shows high day-to-day, inter- and intra-subject variability, studying SB requires multiple, repeated assessment of mobility during several days. A home-based experimental setting would be optimal for this purpose in terms of cost-effectiveness and acceptability by the patients. Moreover, considering that the range and nature of SB has not been well characterized so far, and that the amplitude of its variability is unknown, a reliable, observer- and situation-independent, reproducible assessment method of SB is a pivotal requirement for further research in this area.
A recently developed technique associating machine-learning algorithms with wireless wearable sensors (accelerometers and gyroscopes) and software applications might be particularly promising to characterize the complexity and multiplicity of SB in PD. Thanks to this technique, repeated, multiple assessments of mobility can be performed at patients' home without the constant presence of an investigator.
The working hypothesis of this study is that motor performance in PD patients improves on morning awakening when optimal synchrony between circadian and homeostatic regulation of sleep occurs. As first step, we envision to set up a home-based and technology-assisted methodology and to verify its scientific, technological and logistic feasibility.
The study will involve four work packages, for each of which specific endpoints are defined:
WP1: Definition of the logistics, setting, practices of the study procedures for home assessment;
WP2: Technological setup of:
* IMU wearable sensors
* SleepFit software application development
* light therapy (included sham light therapy)
* home polysomnography
* chronobiological assessments (distal-proximal skin body temperature gradient; Dim Light Melatonin Onset (DLMO) from salivary specimens;
Two work packages (3 and 4) will require patients inclusion and interventions on patients:
WP3: Validation of mobility assessment by wearable sensors: accuracy of machine learning algorithm to predict patients' motor status based on the MDS-UPDRS-III total score and on the 3.14 item (global clinical impression of mobility);
WP4: Testing in real-life conditions at patients' home in a small group of subjects.
SB is a promising track to follow to develop novel therapeutic strategies for motor symptoms in PD. An innovative approach could be to induce modifications of mobility by influencing sleep regulation in PD patients in experimental settings.
Sleep propensity and timing depend on the coordinated interaction of the duration of preceding wakefulness (homeostatic component) and on a circadian signal (circadian component). Reciprocal interactions between homeostatic and circadian processes preside to internal synchrony of many physiological processes. We hypothesize SB to depend on serendipitous optimal synchronization between circadian and homeostatic process on morning awakening. As SB shows high day-to-day, inter- and intra-subject variability, studying SB requires multiple, repeated assessment of mobility during several days. A home-based experimental setting would be optimal for this purpose in terms of cost-effectiveness and acceptability by the patients. Moreover, considering that the range and nature of SB has not been well characterized so far, and that the amplitude of its variability is unknown, a reliable, observer- and situation-independent, reproducible assessment method of SB is a pivotal requirement for further research in this area.
A recently developed technique associating machine-learning algorithms with wireless wearable sensors (accelerometers and gyroscopes) and software applications might be particularly promising to characterize the complexity and multiplicity of SB in PD. Thanks to this technique, repeated, multiple assessments of mobility can be performed at patients' home without the constant presence of an investigator.
The working hypothesis of this study is that motor performance in PD patients improves on morning awakening when optimal synchrony between circadian and homeostatic regulation of sleep occurs. As first step, we envision to set up a home-based and technology-assisted methodology and to verify its scientific, technological and logistic feasibility.
The study will involve four work packages, for each of which specific endpoints are defined:
WP1: Definition of the logistics, setting, practices of the study procedures for home assessment;
WP2: Technological setup of:
* IMU wearable sensors
* SleepFit software application development
* light therapy (included sham light therapy)
* home polysomnography
* chronobiological assessments (distal-proximal skin body temperature gradient; Dim Light Melatonin Onset (DLMO) from salivary specimens;
Two work packages (3 and 4) will require patients inclusion and interventions on patients:
WP3: Validation of mobility assessment by wearable sensors: accuracy of machine learning algorithm to predict patients' motor status based on the MDS-UPDRS-III total score and on the 3.14 item (global clinical impression of mobility);
WP4: Testing in real-life conditions at patients' home in a small group of subjects.
Study Oversight
Has Oversight DMC:
False
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?: