ArticleMovement disorders clinical practice2025
Identifying Common Disease Trajectories of Progressive Supranuclear Palsy with Electronic Health Records.
Article in Movement disorders clinical practice, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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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.
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Who cites it
1 citing paper in PubMed.
- Causal Discovery in Observational Medical Research: Scoping Review.JMIR medical informatics · 2026Article
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Authors and funding
4 authors.
Funding
Abstract
backgroundProgressive supranuclear palsy (PSP) is a rare neurodegenerative disorder characterized by parkinsonism and impairments in balance, language, and cognition. As an atypical parkinsonism, PSP progresses rapidly, lacks effective treatments, and poses significant caregiving burdens. While prior studies have identified risk factors, they often fail to capture the complex temporal dynamics of co-occurring conditions.
objectivesTo identify common PSP disease trajectories using a computational framework combining machine learning and network analysis.
methodsWe analyzed ICD-10 codes from the University of California Health Data Warehouse to identify significant temporal risk factors and determine diagnostic trajectories. Multi-step trajectories were clustered using dynamic time warping and clustering. Network analysis identified common trajectory clusters, which were compared for patient demographics, symptoms, and PSP progression. Causal relationships were inferred through association tests and compared to control groups.
resultsFrom an initial cohort of 1205 PSP patients, 247 with multi-step trajectories were included. The final dataset yielded 258 unique multi-step trajectories. A total of 258 unique trajectories were identified, grouped into three clusters: binocular movement disorder (N = 29), Parkinson's disease (N = 72), and other neurodegenerative diseases (N = 168). Demographics, symptoms, and disease progression differed significantly across clusters. Causal analysis revealed that 36.8% of trajectory connections were significant. Patients with multi-step risk factor trajectories exhibited higher PSP risk compared to those with single or no risk factors.
conclusionsDistinct PSP trajectories were identified, offering insights into temporal and causal relationships. These findings can improve PSP risk assessment, early diagnosis, and personalized management, enhancing patient care and guiding future research.
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