Layered classification in Parkinson's disease: a content analysis of clinical, prodromal, and biological criteria evolution.

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BackgroundParkinson's disease (PD) is no longer described through a single diagnostic vocabulary. Clinical criteria, prodromal probability models, and biological research classifications now operate in parallel after the 2024 NSD-ISS and SynNeurGe proposals.ObjectiveTo clarify how major PD criteria and research frameworks have justified diagnostic change and redistributed the roles of clinical signs, biomarkers, genetics, and prodromal markers.MethodsWe conducted a targeted document-based qualitative content analysis of eight purposively selected landmark PD criteria or criteria-adjacent framework documents, with the 1988 UK Brain Bank/Lewy body source retained as a historical lineage anchor. Document-declared aims and perceived diagnostic problems were coded with a prespecified framework, and twelve diagnostic elements were assigned interpretative ordinal scores according to their document-specific textual roles.ResultsWithin the selected corpus, stated priorities shifted from clinicopathological specificity, standardization, and differential diagnosis toward early identification, biomarker integration, staging/subtyping, and trial readiness. Diagnostic-element roles moved from motor signs, exclusions, and dopaminergic response toward RBD/olfaction in prodromal probability frameworks and toward α-synuclein SAA, dopaminergic imaging, and genetics in 2024 biological research frameworks. The analyzed documents indicated materially different 2024 architectures: NSD-ISS emphasized biological definition and integrated staging, whereas SynNeurGe used a multidimensional S/N/G structure.ConclusionOur analysis suggests that contemporary PD classification can be understood as a layered architecture rather than a simple replacement sequence. Clinical criteria remain necessary for care, prodromal criteria support early-risk research, and biological frameworks require longitudinal, pathological, technical, ethical, and global-access validation before clinical translation.

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