Assessment of Fluctuating Parkinson's Disease With Sensor-based Home Monitoring
试验速览
- 阶段
- 不适用
- 状态
- 已完成
- 入组人数
- 24
- 试验地点
- 1
- 主要终点
- Correlation between sensor data and MDS-UPDRS data
研究概览
简要总结
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 Parkinson's 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.
详细描述
Parkinson's 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 Parkinson's 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.
研究设计
- 研究类型
- Observational
- 观察模型
- Cohort
- 时间视角
- Prospective
入排标准
- 年龄范围
- 30 Years 至 —（Adult, Older Adult）
- 性别
- All
- 接受健康志愿者
- 否
入选标准
- •Diagnosis of idiopathic Parkinson's disease for at least 5 years
- •Males or females over the age of 30
- •Patients treated with oral levodopa (3 daily doses or more), reporting motor fluctuations and (preferably) with l-dopa-induced dyskinesia
- •UPDRS-MDS 4.4 functional impact of fluctuations (mild + severe, 2-4)
- •Hoehn &Yahr stage 1-3 while ON
- •Ability to operate smartphone technology in the household
- •Mini-Mental State Examination score >20
排除标准
- •Cognitive or psychiatric impairment that would preclude study participation as determined by the principal investigator
- •Additional major comorbidities
- •Levodopa-resistant tremor (tremor during ON)
- •Levodopa-resistant freezing (freezing during ON)
- •Previous surgical treatment for PD
结局指标
主要结局
Correlation between sensor data and MDS-UPDRS data
时间窗: 2-3 weeks study period
To correlate severity of fluctuating motor symptoms in PD patients using Intel® Pharma Analytics Platform's 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 application's based electronic symptom diary and data of tremor, off time and dyskinesia using the MDS-UPDRS.
次要结局
- Correlation between passive sensor data and electronic home diaries(2-3 weeks study period)
- Assessing compliance of PD patients using wearable devices and adherence to assessment protocol.(2-3 weeks study period)
- Correlation between passive sensor data and PDQ-39 questionnaire(2-3 weeks study period)
- Correlation between motor test results (TUG, Static postural tests and finger tapping,) and relevant MDS-UPDRS items(2-3 weeks study period)
- Correlation between medication regimen as prescribed by neurologist and patient adherence in real life(2-3 weeks study period)
研究者
Dr. Sharon Hassin
Prof. Sharon Hassin
Sheba Medical Center