ArticlePeerJ2025
Longitudinal analysis of step counts in Parkinson's disease patients: insights from a web-based application and generalized additive model.
Article in PeerJ, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
2 citing papers in PubMed.
- Article
- Longitudinal study evaluating the role of physical activity in modifying Parkinson's disease progression.Bioinformation · 2025Article
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Parkinson's disease (PD) is a chronic neurological disorder that affects millions of people worldwide. A common motor symptom associated with PD is gait impairment, leading to reduced step count and mobility. Methods: Monitoring and analyzing step count data can provide valuable insights into the progression of the disease and the effectiveness of various treatments. In our study, the generalized additive model (GAM) was used to identify statistically significant variables for step counts. Additionally, a web application was developed as an interactive visualization tool. Results: The GAM model shows that the following variables are statistically significant for daily step counts: sex ( Conclusions: Based on the PPMI data, we find that sex, handedness, PD status of father, COVID-19 status, cohort, and the smoothing functions of age are all statistically significant for step counts. Additionally, a web application tailored specifically for step count analysis in PD patients was developed. This tool provides a user-friendly interface for patients, caregivers, and healthcare professionals to track and analyze step count data, facilitating personalized treatment plans and enhancing the management of PD.
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Registered trials
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