Relationship between excessive daytime sleepiness and motor subtype transition in untreated prodromal Parkinson's...

The aim of this study was to explore the intrinsic relationship between excessive daytime sleepiness (EDS) and motor subtype transitions in untreated patients with prodromal Parkinson's disease (pPD).

In this study, we initially screened 65 untreated pPD patients from the Parkinson's Progression Markers Initiative (PPMI) database. Eventually, 38 pPD patients were enrolled for a three-year annual cohort follow-up. We subdivided the pPD patients into two subtype groups: tremor dominant (TD) and posterior instability/gait disturbance (PIGD). Through univariate and multivariate Cox regression analysis, we identified key factors influencing the transition of motor subtypes and assessed the temporal risk factors of motor subtype transitions using Kaplan-Meier curves.

After three years of follow-up, we found that the annual conversion rates from the TD subtype to the PIGD subtype were 38.48%, 60.00% and 69.23%, respectively. The annual rates of conversion from the PIGD subtype to the TD subtype were relatively low, at 8.00%, 32.14% and 28.00%. After adjusting for confounding factors such as gender and age, multivariate Cox regression analysis showed that EDS was an independent risk factor for the transition from TD subtype to PIGD subtype in pPD patients (HR = 14.507, 95% CI: 1.274-165.206, P = 0.031). However, the transition from PIGD to TD did not reach a statistically significant level (P > 0.05).

Our findings demonstrate that patients with the TD subtype are more likely to transition to the PIGD subtype as the disease progresses in pPD. The innovation of this study lies in the first discovery that EDS may serve as a valid predictor for the transition from the TD subtype to the PIGD subtype in untreated pPD patients. This finding addresses a current gap in the research on subtype transition in pPD. It should be noted that the observational design of this study cannot establish causality, and the limited sample size may affect statistical power. Therefore, the above findings require further validation in prospective, large-scale cohorts.