Abstract

As psychosis is associated with decreased quality of life, increased institutionalization, and mortality in Parkinson disease (PD), it is essential to identify individuals at risk for future psychosis. This longitudinal study aimed to investigate whether diffusion tensor imaging (DTI) metrics of white matter hold independent utility for predicting future psychosis in PD, and whether they could be combined with clinical predictors to improve the prognostication of PD psychosis. This study included 123 newly diagnosed PD patients collected in the Parkinson's Progression Markers Initiative. Tract-based spatial statistics were used to compare baseline DTI metrics between PD patients who developed psychosis and those who did not during follow-up. Binary logistic regression analyses were performed to identify the clinical and white matter markers predictive of psychosis. Among DTI measures, both higher baseline whole brain (odds ratio [OR] = 1.711, p= 0.016) free water (FW) and visual processing system (OR=1.680, p< 0.001) FW were associated with an increased risk of future psychosis. Baseline FW remained a significant indicator of future psychosis in PD after controlling for clinical predictors. Moreover, the accuracy of prediction of psychosis using clinical predictors alone (area under the curve [AUC] = 0.742, 95% confidence interval [CI] = 0.655-0.816) was significantly improved by the addition of the visual processing system FW (AUC=0.856, 95% CI=0.781-0.912; Delong method, p= 0.022). Baseline FW of the visual processing system incurs an independent risk of future psychosis in PD, thus providing an opportunity for multiple-modality marker models to include a white matter marker.

Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call