Predictive modeling to uncover Parkinson's disease characteristics that delay diagnosis

Research output: Contribution to journalResearch articleContributedpeer-review

Contributors

  • Tom Hähnel - , Department of Neurology, Fraunhofer Institute for Algorithms and Scientific Computing (Author)
  • Tamara Raschka - , University of Bonn (Author)
  • Jochen Klucken - , Center Hospitalier de Luxembourg (Author)
  • Enrico Glaab - , University of Luxembourg (Author)
  • Jean-Christophe Corvol - , Sorbonne Université, Paris Brain Institute (ICM), Public Assistance - Paris Hospitals, Pitié-Salpêtrière Hospital (Author)
  • Björn H. Falkenburger - , Department of Neurology, German Center for Neurodegenerative Diseases (DZNE) - Partner Site Dresden (Author)
  • Holger Fröhlich - , University of Bonn (Author)

Abstract

PD patients present with diverse symptoms, complicating timely diagnosis. We analyzed 1124 PD trajectories using a novel model-based approach to estimate whether diagnosis was early or late compared to cohort averages. Higher age, specific non-motor symptoms, and fast disease progression were linked to later diagnosis, while gait impairment led to earlier diagnosis. Our findings are in line with a biological definition of PD that extends beyond classical motor symptoms.

Details

Original languageEnglish
Article number64
Number of pages7
JournalNPJ Parkinson's disease
Volume11 (2025)
Issue number1
Publication statusPublished - 2 Apr 2025
Peer-reviewedYes

External IDs

ORCID /0000-0002-2387-526X/work/181860662
Scopus 105001644947

Keywords

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