app to monitor parkinson's disease

The SleepFit App allows Parkinson’s patients to report their motor symptoms throughout the day, creating a better way for physicians to monitor and prescribe medications at a minimal efficient dose.

Parkinson’s Disease (PD) is characterized by tremor, muscular rigidity and slowness in initiating and repeating voluntary movements. These features of the disease are typical motor symptoms found in patients with PD, in addition to cognitive dysfunction that can affect memory. Monitoring these symptoms is difficult for physicians, as most symptoms are reported during a doctor’s visit and not at the time the symptoms occurred. This is important because Parkinson’s medications are prescribed at their minimal efficient dose so that mobility is optimized, while side effects are minimized. As such, tools that can monitor the experiences of symptoms as they occur or on a daily basis would be a valuable resource for physicians to better treat patients with Parkinson’s disease.

In a recent study published by the Journal of Parkinson’s Disease, researchers conducted a study that included 42 patients with mild-to-moderate Parkinson’s disease to determine the effectiveness of using a home-based tablet app, SleepFit. The app is used to record motor symptoms of PD throughout the day versus, allowing accurate reporting of symptoms during doctor’s visits.

The SleepFit app integrates the motor portion of the Scales for Outcome in Parkinson Assessment Diary Card (m-SCOPA-DC) and the Visual Analogue Scale (m-VAS) and is a tool for recording patient mobility in regards to objective, subjective, and repetitive symptoms. This app also allows the reported information to be accessed remotely by physicians and researchers.

During the study, participants used the app four times a day for 14 days, to report their experience of hand dexterity, walking, changing position, involuntary movement, and overall mobility, while at home and completing their daily tasks. After the 14-day period, patients had to recall and report their past two-week experiences of motor symptoms during an office consultation with a neurologist, where the Movement Disorders Society Unified Parkinson’s Disease Rating Scale (MDS-UPDRS) was used to quantify their levels of mobility. Once the study was completed, the questions and scales used from the SleepFit App and the office consultation were matched, and differences were scored by using the Root Mean Square Difference (RMSD); a difference of 0% indicating perfect agreement, and a difference of at least 20% indicating a change in the agreement between the scales utilized.

The researchers found differences in real-time reporting via the app compared to patient reporting during doctor’s visits in a significant number of Parkinson’s disease patients. This was found to be especially true when patients had more advanced disease, suggesting that the app would have a greater impact for patients with advanced stages of Parkinson’s disease.

Overall this study demonstrated significant benefits of using home-based, real-time reporting of symptoms,  which seemed to be especially important for patients with greater cognitive difficulty, and for those who tended to over- or underestimate their symptom severity during appointments with their physicians. which can overall alter their reporting of symptoms accurately. The results of the study suggest that the accurate reporting allowed by utilizing this tool means that it could enable physicians to better prescribe medications for Parkinson’s patients, optimizing dosage while minimizing undesirable side-effects.

 

Written by P. Sukumar

 

Reference(s):

  1. Ratti, P., et al. (2019). Journal of Parkinson’s Disease. A New Prospective, Home-Based Monitoring of Motor Symptoms in Parkinson’s Disease.
  2. Murray, D. (2019). EurekAlert! Researchers develop a new home-based app to better monitor Parkinson’s Disease.
  3. Edwards, C, et al. (2019). Davidson’s Principles and Practice of Medicine. 17th London, England: Pearson Professional Limited, 1996.

Image by Jan Vašek from Pixabay

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