4 research outputs found

    Using Smartphones and Machine Learning to Quantify Parkinson Disease Severity:The Mobile Parkinson Disease Score

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    IMPORTANCE: Current Parkinson disease (PD) measures are subjective, rater-dependent, and assessed in clinic. Smartphones can measure PD features, yet no smartphone-derived rating score exists to assess motor symptom severity in real-world settings. OBJECTIVES: To develop an objective measure of PD severity and test construct validity by evaluating the ability of the measure to capture intraday symptom fluctuations, correlate with current standard PD outcome measures, and respond to dopaminergic therapy. DESIGN, SETTING, AND PARTICIPANTS: This observational study assessed individuals with PD who remotely completed 5 tasks (voice, finger tapping, gait, balance, and reaction time) on the smartphone application. We used a novel machine-learning-based approach to generate a mobile Parkinson disease score (mPDS) that objectively weighs features derived from each smartphone activity (eg, stride length from the gait activity) and is scaled from 0 to 100 (where higher scores indicate greater severity). Individuals with and without PD additionally completed standard in-person assessments of PD with smartphone assessments during a period of 6 months. MAIN OUTCOMES AND MEASURES: Ability of the mPDS to detect intraday symptom fluctuations, the correlation between the mPDS and standard measures, and the ability of the mPDS to respond to dopaminergic medication. RESULTS: The mPDS was derived from 6148 smartphone activity assessments from 129 individuals (mean [SD] age, 58.7 [8.6] years; 56 [43.4%] women). Gait features contributed most to the total mPDS (33.4%). In addition, 23 individuals with PD (mean [SD] age, 64.6 [11.5] years; 11 [48%] women) and 17 without PD (mean [SD] age 54.2 [16.5] years; 12 [71%] women) completed in-clinic assessments. The mPDS detected symptom fluctuations with a mean (SD) intraday change of 13.9 (10.3) points on a scale of 0 to 100. The measure correlated well with the Movement Disorder Society Unified Parkinson Disease's Rating Scale total (r = 0.81; P < .001) and part III only (r = 0.88; P < .001), the Timed Up and Go assessment (r = 0.72; P = .002), and the Hoehn and Yahr stage (r = 0.91; P < .001). The mPDS improved by a mean (SD) of 16.3 (5.6) points in response to dopaminergic therapy. CONCLUSIONS AND RELEVANCE: Using a novel machine-learning approach, we created and demonstrated construct validity of an objective PD severity score derived from smartphone assessments. This score complements standard PD measures by providing frequent, objective, real-world assessments that could enhance clinical care and evaluation of novel therapeutics

    National randomized controlled trial of virtual house calls for Parkinson disease

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    To determine whether providing remote neurologic care into the homes of people with Parkinson disease (PD) is feasible, beneficial, and valuable. In a 1-year randomized controlled trial, we compared usual care to usual care supplemented by 4 virtual visits via video conferencing from a remote specialist into patients' homes. Primary outcome measures were feasibility, as measured by the proportion who completed at least one virtual visit and the proportion of virtual visits completed on time; and efficacy, as measured by the change in the Parkinson's Disease Questionnaire-39, a quality of life scale. Secondary outcomes included quality of care, caregiver burden, and time and travel savings. A total of 927 individuals indicated interest, 210 were enrolled, and 195 were randomized. Participants had recently seen a specialist (73%) and were largely college-educated (73%) and white (96%). Ninety-five (98% of the intervention group) completed at least one virtual visit, and 91% of 388 virtual visits were completed. Quality of life did not improve in those receiving virtual house calls (0.3 points worse on a 100-point scale; 95% confidence interval [CI] -2.0 to 2.7 points; = 0.78) nor did quality of care or caregiver burden. Each virtual house call saved patients a median of 88 minutes (95% CI 70-120; < 0.0001) and 38 miles per visit (95% CI 36-56; < 0.0001). Providing remote neurologic care directly into the homes of people with PD was feasible and was neither more nor less efficacious than usual in-person care. Virtual house calls generated great interest and provided substantial convenience. NCT02038959. This study provides Class III evidence that for patients with PD, virtual house calls from a neurologist are feasible and do not significantly change quality of life compared to in-person visits. The study is rated Class III because it was not possible to mask patients to visit type
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