Paulo Bugalho1, Filipa Ladeira2, Raquel Barbosa3, João Pedro Marto2, Cláudia Borbinha2, Laurete da Conceição2, Manuel Salavisa2, Marlene Saraiva2, Bruna Meira2, Marco Fernandes2. 1. Department of Neurology, Hospital de Egas Moniz, Centro Hospitalar de Lisboa Ocidental, Lisboa, Portugal; CEDOC, Chronic Diseases Research Center, NOVA Medical School, Portugal. Electronic address: paulobugalho@sapo.pt. 2. Department of Neurology, Hospital de Egas Moniz, Centro Hospitalar de Lisboa Ocidental, Lisboa, Portugal. 3. Department of Neurology, Hospital de Egas Moniz, Centro Hospitalar de Lisboa Ocidental, Lisboa, Portugal; CEDOC, Chronic Diseases Research Center, NOVA Medical School, Portugal.
Abstract
OBJECTIVE: To 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. METHODS: PD 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. RESULTS: We 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. CONCLUSIONS: The 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.
OBJECTIVE: To 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. METHODS:PDpatients 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. RESULTS: We 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. CONCLUSIONS: The 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.
Authors: Kimberly H Wood; Adeel A Memon; Raima A Memon; Allen Joop; Jennifer Pilkington; Corina Catiul; Adam Gerstenecker; Kristen Triebel; Gary Cutter; Marcas M Bamman; Svjetlana Miocinovic; Amy W Amara Journal: J Parkinsons Dis Date: 2021 Impact factor: 5.568