Machine-Learning-Based Targeted Plasma Proteomic Analysis for Predicting Motor Progression in Parkinson's Disease: An Interpretable Approach to Personalized Disease Management.

Bioengineering (Basel) · 2026 · PMC13113626 · PMID 42072174

Europe PMC DOI

hedged sentence

0.0680

closest p · 1.4× alpha

0.0680

boldest claim

The sentences

showed a trendp = 0.068so close (0.05 < p ≤ 0.1)

BDNF showed a trend toward a greater decline in rapid progressors (−0.12 vs. −0.05; p = 0.068), while VEGF-A trajectories did not differ significantly between groups.

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