Polysomnographic predictors of sleep, motor and cognitive dysfunction progression in Parkinson's disease: a longitudinal study

Abstract

ObjectiveTo assess the predictive value of polysomnographic (PSG) data in the prospective assessment of cognitive, motor, daytime and nighttime sleep dysfunction in Parkinson's Disease (PD) patients. MethodsPD patients were assessed at baseline with video-PSG and with cognitive (MoCA), Sleep (SCOPA-Sleep Nighttime and Daytime scores) and Motor (UPDRSIII) function scales at both baseline and four years later. Linear regression analysis was used to assess the relation between PSG variables at baseline and change in symptoms scores. ResultsWe included a total of 25 patients, 12 with rapid eye movement (REM) sleep behavior disorder (RBD) (in 8 PSG was inconclusive, due to lack of REM sleep). MoCA scores decreased significantly at follow-up, while SCOPA-Sleep Daytime and SCOPA-Sleep Nighttime and UPDRSIII did not vary. Lower N3 percentage at baseline was significantly associated with MoCA decrease. Higher Periodic Limb Movements in Sleep index (PLMS) and the presence of RBD were significantly associated with SCOPA daytime score increase. Higher global severity of RBD, tonic RSWA and total number of motor events during REM sleep were associated with SCOPA Nighttime score increase. ConclusionsThe present work suggests that PSG data could be useful for predicting PD cognitive and sleep dysfunction progression. Reduced SWS could predict deterioration of cognitive function, while baseline PLMS could be useful to predict worsening of daytime sleep dysfunction. Severity of RBD could be used for estimating nighttime sleep symptoms progression.