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Accepted for/Published in: JMIR Research Protocols

Date Submitted: Feb 3, 2025
Date Accepted: Jul 7, 2025

The final, peer-reviewed published version of this preprint can be found here:

Improving Prediction of Falls and Cognitive Impairment in Parkinson Disease: Protocol for a Decentralized Observational Study

Hoyt A, Dorney C, Auinger P, Murphy K, Porto M, Schmier K, Wilson R, Beck JC, Benvengo S, Biglan K, Dorsey ER, Espay A, Macklin EA, Monje MH, Novak D, Oakes D, Omberg L, Schwarzschild MA, Sieberts S, Simuni T, Tanner CM, Weintraub D, Schneider R

Improving Prediction of Falls and Cognitive Impairment in Parkinson Disease: Protocol for a Decentralized Observational Study

JMIR Res Protoc 2025;14:e71955

DOI: 10.2196/71955

PMID: 40864497

PMCID: 12423612

Improving Prediction of Falls and Cognitive Impairment in Parkinson’s Disease: Protocol for a Decentralized Observational Study

  • Audrey Hoyt; 
  • Casey Dorney; 
  • Peggy Auinger; 
  • Kathryn Murphy; 
  • Michelle Porto; 
  • Katrina Schmier; 
  • Renee Wilson; 
  • Jim C Beck; 
  • Stephanie Benvengo; 
  • Kevin Biglan; 
  • E. Ray Dorsey; 
  • Alberto Espay; 
  • Eric A Macklin; 
  • Mariana HG Monje; 
  • Dan Novak; 
  • David Oakes; 
  • Larsson Omberg; 
  • Michael A Schwarzschild; 
  • Solly Sieberts; 
  • Tanya Simuni; 
  • Caroline M Tanner; 
  • Daniel Weintraub; 
  • Ruth Schneider

ABSTRACT

Background:

Falls and cognitive impairment are major sources of disability in Parkinson’s disease (PD). The ability to accurately identify individuals with PD at high risk for falls and cognitive impairment would provide an opportunity for intervention and potentially improve long-term outcomes. In a previous study, AT-HOME PD (Assessing Tele-Health Outcomes in Multiyear Extensions of Parkinson’s Disease trials), we remotely characterized participants with early PD who had participated in one of two PD clinical trials over two years of follow-up. These participants with advancing disease provide a unique opportunity to examine whether the capture of objective, in-home measures via digital tools and of bothersome symptoms via direct participant report improves the prediction of disease milestones.

Objective:

AT-HOME PD2 (Assessing Tele-Health Outcomes in Multiyear Extensions of Parkinson’s Disease trials – 2) examines whether digital tools and remote participant reporting can improve the prediction of falls and cognitive impairment, quantify changes in physical activity over time, and explore the relationship between physical activity and clinical progression over time.

Methods:

This is a decentralized observational study of up to 200 individuals with PD with clinical and digital phenotyping over up to 3 years of follow-up. Participants are those who participated in STEADY-PD III (NCT02168842), SURE-PD3 (NCT02642393), AT-HOME PD (NCT03538262), and/or PD GENEration (NCT04057794). All participants complete two video visits per year, wear two wrist-worn sensors (Fitbit Charge 5 and ActiGraph Centrepoint Insight Watch) for one week each month, complete smartphone-based motor tasks (using the mPower 2.0 application) for ten days each quarter, and complete online surveys (within the companion Fox Insight study) each quarter. Falls are assessed via a weekly automated telephone call. Cognitive diagnosis is determined by a consensus committee that considers scores on a global cognitive measure, detailed neuropsychological tests, and a cognitive-related disability measure as well as clinical information. Prediction models will be constructed, and prediction accuracy will be compared across the models.

Results:

Recruitment for the study was initiated in September 2023. Enrollment is on-going, with 142 participants enrolled as of January 2025. Within the cohort, the average age is 69.2 years (SD 8.7), 85 (59.9%) male, 137 (96.5%) Caucasian, 2 (1.4%) Hispanic or Latino, and the average disease duration is 8.9 years (SD 1.3).

Conclusions:

AT-HOME PD2 is remotely clinically and digitally phenotyping participants with mid-stage PD to predict falls and cognitive impairment and provide insights into long-term progression.


 Citation

Please cite as:

Hoyt A, Dorney C, Auinger P, Murphy K, Porto M, Schmier K, Wilson R, Beck JC, Benvengo S, Biglan K, Dorsey ER, Espay A, Macklin EA, Monje MH, Novak D, Oakes D, Omberg L, Schwarzschild MA, Sieberts S, Simuni T, Tanner CM, Weintraub D, Schneider R

Improving Prediction of Falls and Cognitive Impairment in Parkinson Disease: Protocol for a Decentralized Observational Study

JMIR Res Protoc 2025;14:e71955

DOI: 10.2196/71955

PMID: 40864497

PMCID: 12423612

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