Circadian & Homeostatic Synchronization Effect on Waking Mobility in Parkinson's Disease: a Feasibility Study
试验速览
- 阶段
- 不适用
- 状态
- 撤回
- 发起方
- 试验地点
- 2
- 主要终点
- Objective and subjective mobility
研究概览
简要总结
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.
详细描述
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.
研究设计
- 研究类型
- Interventional
- 分配方式
- Na
- 干预模型
- Single Group
- 主要目的
- Other
- 盲法
- None
入排标准
- 年龄范围
- 18 Years 至 —（Adult, Older Adult）
- 性别
- All
- 接受健康志愿者
- 否
入选标准
- •Patients > 18 years old;
- •Patients affected with idiopathic PD, of both sexes;
- •Hoehn and Yahr stage of 2 to 4 in the "on" state;
- •Stable antiparkinsonian and/or psychotropic medications for at least 4 weeks prior to study screening;
- •Reliable partner/caregiver to assist the patient during the study procedures;
- •Affiliated person or beneficiary of a social security scheme;
- •Free, informed and written consent signed by the participant and the investigator (at the latest on the day of inclusion and before any examination required by the research).
排除标准
- •Patients < 18 years old;
- •Atypical parkinsonian syndromes;
- •Dementia;
- •Treatment with extended-release dopaminergic drugs (excluding extended release levodopa given no later than 6 hours before the habitual bedtime);
- •Use of hypno-sedative drugs or stimulants;
- •Use of antidepressants unless on a stable dose for at least 3 months;
- •Travel through 2 time zones within 90 days prior to study screening;
- •Visual abnormalities that may interfere with light therapy, such as significant cataracts, narrow angle glaucoma or blindness;
- •Any other medical condition potentially interfering with the assessment of mobility (e.g. limb amputation, post-stroke paralysis, severe osteo-articular condition);
- •Any condition limiting the capability of the subject to understand the task to be performed at home by the patient himself (e.g. aphasia, oligophrenia);
- •Severely altered physical and/or psychological health which, according to, the investigator, could affect the participant's compliance of the study;
- •Inadequate housing conditions to perform home assessments;
- •Patients refusing to participate in the study;
- •Patients under legal guardianship or curatorship, pregnant and breastfeeding women, women of child-bearing age, persons in emergency situations;
- •Persons participating in another research including a period of exclusion still in course and at any case < 1 month.
结局指标
主要结局
Objective and subjective mobility
时间窗: 12 months
Prediction of mobility by machine learning based on data from IMU wearable sensors; finger tapping test; VAS motor
Emotional state
时间窗: 12 months
Measured by Visual Analog Scale(VAS) mood/anxiety
Fatigue
时间窗: 12 months
Measured by VAS fatigue
Validation of the objective metrics of mobility
时间窗: 12 months
The validity of the mobility assessment by Inertial Measurement Unit (IMU) wearable sensors will be verified. It will be defined as the accuracy of the machine learning algorithm to predict patients' motor status compared to the motor status assessed at clinical examination by means of the MDSUPDRS- III scale and the Fit test. Prediction by machine learning will be compared with the MDS-UPDRS-III total score and with the 3.14 item (global clinical impression of mobility) of the same scale. The patients will be asked to perform all the motor tasks of the MDS-UPDRS-III scale and the finger tapping test (Fit test) with both hands wearing the IMU system.
Sleep homeostasis (SWA)
时间窗: 12 months
Calculated based on the EEG recording acquired by means of nocturnal portable polysomnography.
Sleep and sleepiness
时间窗: 12 months
Measured by sleep diary, SSS
Circadian phase
时间窗: 12 months
Continuously for skin body temperature and repeated samples (every 30' for a total of 9 samples, in the evening around the bed time, for salivary DLMO
Cognition (electronic Stroop test)
时间窗: 12 months
次要结局
- Chronotype(12 months)
- Sleep habits, sleep and wake-related symptoms, sleep quality(12 months)
- PD-specific sleep and wake-associated symptoms(12 months)
- Daytime symptoms of bad or insufficient sleep(12 months)
- Modification of mobility on morning awakening(12 months)
- Neuropsychological battery useful in idiopathic PD(12 months)
- Motor and non-motor symptoms of PD in daily living(12 months)
- Mood(12 months)