Evaluation of smartphone-based testing to generate exploratory outcome measures in a phase 1 Parkinson's disease clinical trial
| Autor: | Timothy Kilchenmann, Lynne Verselis, Liping Jin, Christian Gossens, Michael Lindemann, Andreas U. Monsch, Detlef Wolf, Ronald B. Postuma, Jay Soto, Wei-Yi Cheng, Anirvan Ghosh, Frank G. Boess, Michael Grundman, Martin Koller, Alf Scotland, Florian Lipsmeier, Thomas Kremer, Kirsten I. Taylor, Juliane Siebourg-Polster, Ignacio Fernandez‐Garcia, Jens Schjodt-Eriksen, Christian Czech |
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| Rok vydání: | 2018 |
| Předmět: |
0301 basic medicine
medicine.medical_specialty Movement disorders Parkinson's disease Intraclass correlation business.industry Gait Disturbance Postural tremor medicine.disease Gait 3. Good health Clinical trial 03 medical and health sciences 030104 developmental biology 0302 clinical medicine Physical medicine and rehabilitation Neurology medicine Neurology (clinical) medicine.symptom business 030217 neurology & neurosurgery Balance (ability) |
| Zdroj: | Movement Disorders. 33:1287-1297 |
| ISSN: | 0885-3185 |
| DOI: | 10.1002/mds.27376 |
| Popis: | Background: Ubiquitous digital technologies such as smartphone sensors promise to fundamentally change biomedical research and treatment monitoring in neurological diseases such as PD, creating a new domain of digital biomarkers. Objectives: The present study assessed the feasibility, reliability, and validity of smartphone‐based digital biomarkers of PD in a clinical trial setting. Methods: During a 6‐month, phase 1b clinical trial with 44 Parkinson participants, and an independent, 45‐day study in 35 age‐matched healthy controls, participants completed six daily motor active tests (sustained phonation, rest tremor, postural tremor, finger‐tapping, balance, and gait), then carried the smartphone during the day (passive monitoring), enabling assessment of, for example, time spent walking and sit‐to‐stand transitions by gyroscopic and accelerometer data. Results: Adherence was acceptable: Patients completed active testing on average 3.5 of 7 times/week. Sensor‐based features showed moderate‐to‐excellent test‐retest reliability (average intraclass correlation coefficient = 0.84). All active and passive features significantly differentiated PD from controls with P |
| Databáze: | OpenAIRE |
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