Progression in Parkinson's Disease: Variation in Motor and Non‐motor Symptoms Severity and Predictors of Decline in Cognition, Motor Function, Disability, and Health‐Related Quality of Life as Assessed by Two Different Methods

Abstract

Background Parkinson's disease (PD) is multi‐symptom disease with variable progression. Objectives We performed a longitudinal study to address the evolution of motor symptoms (MS) and non‐motor symptoms (NMS), predictors of motor‐, cognitive‐, disability‐, and health‐related quality of life (HRQL) status and the relative usefullness of a battery of separate NMS scales (BSS) versus the Non‐Motor Symptom Scale (NMSS). Methods Seventy‐two patients were assessed at baseline and 4 years later with the NMSS and BSS. We assessed the following outcomes: cognition (Montreal Cognitive Assessment scale [MoCA]), disability (Unified Parkinson's Disease Rating Scale Part II [UPDRS II], Schwab and England [S&E]), motor dysfunction (Unified Parkinson's Disease Rating Scale Part III [UPDRS III], Hoehn and Yahr [HY]), and HRQL (EuroQol [EQ] EQ‐vertical visual analogue scale [VAS] and EQ‐Index). Statistical analysis included a comparison between scales scores at both time points and multivariate regression analysis to calculate the impact of each baseline symptom in outcomes. NMSS and BSS were introduced in separate models. Results NMSS Domain 4: perception/hallucinations, Parkinson's Psychosis Questionnaire, Apathy Scale, NMSS Domain 7: urinary, S&E, UPDRS II, HY, and MoCA scores worsened significantly. Dementia increased to a 4‐year prevalence of 39.8%. In the multivariate model using BSS, cognitive state variation was significantly predicted by baseline HY, EQ‐Index, and S&E. Using the NMSS, MoCA change was significantly associated with NMSS Domain 4: perceptions/hallucination score, cognitive status with UPDRS III score, HRQL with NMSS Domain 4: perception/hallucinations score, and S&E. Conclusion Our study suggests that NMS progress heterogeneously, BSS approach being more sensitive to change than NMSS. The multivariate analysis has shown that S&E and NMSS Domain 4: perception/hallucinations scores are the stronger predictors of HRQL and cognitive dysfunction variation, favoring NMSS over the BSS approach.

Cognitive-Driven Activities of Daily Living Impairment as a Predictor for Dementia in Parkinson Disease

“…However, other longitudinal studies examining cognitive decline have reported similar attrition rates: 50% after 5 years, 45 and 46% after 4 years. 46 Patients in our sample lost to follow-up were older and had more severe motor and cognitive impairments, similar to previous reports. 46 The number of patients with cognitive IADL impairment was not different between patients who dropped out compared to those who were included, suggesting presence of cognitive IADL impairment did not impact attrition.…”

“…46 Patients in our sample lost to follow-up were older and had more severe motor and cognitive impairments, similar to previous reports. 46 The number of patients with cognitive IADL impairment was not different between patients who dropped out compared to those who were included, suggesting presence of cognitive IADL impairment did not impact attrition. There was also a variable length in time to follow-up; however, as the FAQ Q groups had similar mean intervals, we infer that time to follow-up did not have a significant effect on our results.…”

Dream Content Predicts Motor and Cognitive Decline in Parkinson's Disease

“…Despite these efforts, few variables have been shown to be strong predictors of motor or cognitive decline in PD, and even fewer have been shown to predict both. [41][42][43] The current study suggests that in patients with PD, a simple screening question from the diagnosing clinician at the initial visit, asking about their nightly dream experiences, could identify patients at substantially higher risk for motor and cognitive deterioration in the near future. Furthermore, dream content alterations are easily recognized by the patient, unlike RBD, in which half of the affected patients are unaware of their DEBs.…”

“…In line with this, several studies have aimed to predict motor and cognitive progression in PD using complex machine‐learning algorithms 41 or clinical and nonclinical tests that can cumulatively take hours to administer 42 or may be invasive. Despite these efforts, few variables have been shown to be strong predictors of motor or cognitive decline in PD, and even fewer have been shown to predict both 41–43 …”

Prevalence and Incidence of Nonmotor Symptoms in Individuals with and Without Parkinson's Disease

“…Therefore, we cannot determine which NMS contributed most to disease burden and when they are actually most impactful, as previously reported. [28][29][30][31] This report provides a comprehensive summary of the differences in the occurrence of NMS between people with and without PD. We show that the prevalence and emergence of many NMS in PD are greater than expected from aging alone.…”