Application of single wrist-wearable accelerometry for objective motor diary assessment in fluctuating Parkinson's disease
(2023) In npj Digital Medicine 6(1).- Abstract
Advanced Parkinson's disease (PD) is characterized by motor fluctuations including unpredictable oscillations remarkably impairing quality of life. Effective management and development of novel therapies for these response fluctuations largely depend on clinical rating instruments such as the widely-used PD home diary, which are associated with biases and errors. Recent advancements in digital health technologies provide user-friendly wearables that can be tailored for continuous monitoring of motor fluctuations. Their criterion validity under real-world conditions using clinical examination as the gold standard remains to be determined. We prospectively examined this validity of a wearable accelerometer-based digital Parkinson's Motor... (More)
Advanced Parkinson's disease (PD) is characterized by motor fluctuations including unpredictable oscillations remarkably impairing quality of life. Effective management and development of novel therapies for these response fluctuations largely depend on clinical rating instruments such as the widely-used PD home diary, which are associated with biases and errors. Recent advancements in digital health technologies provide user-friendly wearables that can be tailored for continuous monitoring of motor fluctuations. Their criterion validity under real-world conditions using clinical examination as the gold standard remains to be determined. We prospectively examined this validity of a wearable accelerometer-based digital Parkinson's Motor Diary (adPMD) using the Parkinson's Kinetigraph (PKG
(Less)
®) in an alternative application by converting its continuous data into one of the three motor categories of the PD home diary (Off, On and Dyskinetic state). Sixty-three out of 91 eligible participants with fluctuating PD (46% men, average age 66) had predefined sufficient adPMD datasets (>70% of half-hour periods) from 2 consecutive days. 92% of per-protocol assessments were completed. adPMD monitoring of daily times in motor states showed moderate validity for Off and Dyskinetic state (ICC = 0.43-0.51), while inter-rating methods agreements on half-hour-level can be characterized as poor (median Cohen's κ = 0.13-0.21). Individualization of adPMD thresholds for transferring accelerometer data into diary categories improved temporal agreements up to moderate level for Dyskinetic state detection (median Cohen's κ = 0.25-0.41). Here we report that adPMD real-world-monitoring captures daily times in Off and Dyskinetic state in advanced PD with moderate validities, while temporal agreement of adPMD and clinical observer diary data is limited.
- author
- Löhle, Matthias ; Timpka, Jonathan LU ; Bremer, Alexander ; Khodakarami, Hamid ; Gandor, Florin ; Horne, Malcom ; Ebersbach, Georg ; Odin, Per LU and Storch, Alexander
- organization
- publishing date
- 2023-10-17
- type
- Contribution to journal
- publication status
- published
- subject
- in
- npj Digital Medicine
- volume
- 6
- issue
- 1
- article number
- 194
- publisher
- Nature Publishing Group
- external identifiers
-
- scopus:85174449491
- pmid:37848531
- ISSN
- 2398-6352
- DOI
- 10.1038/s41746-023-00937-1
- language
- English
- LU publication?
- yes
- additional info
- © 2023. Springer Nature Limited.
- id
- 631bd605-0a1a-4bab-b4c2-ad340a68b170
- date added to LUP
- 2023-11-25 07:36:15
- date last changed
- 2024-04-23 06:18:01
@article{631bd605-0a1a-4bab-b4c2-ad340a68b170, abstract = {{<p>Advanced Parkinson's disease (PD) is characterized by motor fluctuations including unpredictable oscillations remarkably impairing quality of life. Effective management and development of novel therapies for these response fluctuations largely depend on clinical rating instruments such as the widely-used PD home diary, which are associated with biases and errors. Recent advancements in digital health technologies provide user-friendly wearables that can be tailored for continuous monitoring of motor fluctuations. Their criterion validity under real-world conditions using clinical examination as the gold standard remains to be determined. We prospectively examined this validity of a wearable accelerometer-based digital Parkinson's Motor Diary (adPMD) using the Parkinson's Kinetigraph (PKG<br> ®) in an alternative application by converting its continuous data into one of the three motor categories of the PD home diary (Off, On and Dyskinetic state). Sixty-three out of 91 eligible participants with fluctuating PD (46% men, average age 66) had predefined sufficient adPMD datasets (>70% of half-hour periods) from 2 consecutive days. 92% of per-protocol assessments were completed. adPMD monitoring of daily times in motor states showed moderate validity for Off and Dyskinetic state (ICC = 0.43-0.51), while inter-rating methods agreements on half-hour-level can be characterized as poor (median Cohen's κ = 0.13-0.21). Individualization of adPMD thresholds for transferring accelerometer data into diary categories improved temporal agreements up to moderate level for Dyskinetic state detection (median Cohen's κ = 0.25-0.41). Here we report that adPMD real-world-monitoring captures daily times in Off and Dyskinetic state in advanced PD with moderate validities, while temporal agreement of adPMD and clinical observer diary data is limited.<br> </p>}}, author = {{Löhle, Matthias and Timpka, Jonathan and Bremer, Alexander and Khodakarami, Hamid and Gandor, Florin and Horne, Malcom and Ebersbach, Georg and Odin, Per and Storch, Alexander}}, issn = {{2398-6352}}, language = {{eng}}, month = {{10}}, number = {{1}}, publisher = {{Nature Publishing Group}}, series = {{npj Digital Medicine}}, title = {{Application of single wrist-wearable accelerometry for objective motor diary assessment in fluctuating Parkinson's disease}}, url = {{http://dx.doi.org/10.1038/s41746-023-00937-1}}, doi = {{10.1038/s41746-023-00937-1}}, volume = {{6}}, year = {{2023}}, }