Development and Validation of a Prognostic Model for Cognitive Impairment in Parkinson’s Disease With REM Sleep Behavior Disorder

Abstract

The presentation and progression of Parkinson’s disease (PD) are not uniform, but the presence of rapid eye movement sleep behavior disorder (RBD) in PD patients may indicate a worse prognosis than isolated PD. Increasing evidence suggests that patients with comorbid PD and RBD (PD-RBD) are more likely to develop cognitive impairment (CI) than those with isolated PD; however, the predictors of CI in PD-RBD patients are not well understood. This study aimed to develop a prognostic model for predicting mild cognitive impairment (MCI) in PD-RBD patients. The data of PD-RBD patients were extracted from the Parkinson’s Progression Markers Initiative study (PPMI), and the sample was randomly divided into a training set (n = 96) and a validation set (n = 24). PD-MCI as defined by the level II Movement Disorder Society (MDS) diagnostic criteria was the outcome of interest. The demographic features, clinical assessments, dopamine transporter (DAT) imaging data, cerebrospinal fluid (CSF) analyses and genetic data of PD patients were considered candidate predictors. We found that performance on the University of Pennsylvania Smell Identification Test (UPSIT), the mean signal and asymmetry index of the putamen on DAT imaging, p-tau/α-syn and p-tau in CSF, and rs55785911 genotype were predictors of PD-MCI in PD-RBD patients. A C-index of 0.81 was obtained with this model, and a C-index of 0.73 was obtained in the validation set. Favorable results of calibrations and decision curve analysis demonstrated the efficacy and feasibility of this model. In conclusion, we developed a prognostic model for predicting MCI in PD-RBD patients; the model displayed good discrimination and calibration and may be a convenient tool for clinical application. Larger samples and external validation sets are needed to validate this model.

Acute Effects of Different Exercise Intensities on Executive Function and Oculomotor Performance in Middle-Aged and Older Adults: Moderate-Intensity Continuous Exercise vs. High-Intensity Interval Exercise

“…Nevertheless, the HIIE relative to the MICE mode appears to be a more effective alternative to the alteration of oculomotor control (i.e., saccadic peak velocity) in late middle-aged and older adults, possibly due to acute-exercise-induced in brain neurotransmitters (e.g., norepinephrine). In addition, it is worth noting that, given the deficits in executive functions and saccadic eye movement shown in the patients with neurodegenerative diseases (e.g., Alzheimer’s disease and Parkinson’s disease) ( Tsai et al, 2018 , 2019a ; Chen et al, 2021 ; Lage et al, 2021 ), HIIE could be one of safe and preventive intervention strategies in lowering their declining cognitive functions and oculomotor control in clinical and medical settings.…”

A nomogram based on neuron-specific enolase and substantia nigra hyperechogenicity for identifying cognitive impairment in Parkinson’s disease

“…The predictive model for clinical diagnosis and prognosis is a valuable tool and has been partially applied in clinical practice ( 22 , 23 ). In a previous study, a nomogram was constructed by combining dopamine transporter (DAT) imaging, CSF biomarkers (p-tau/α-syn and p-tau), and the rs55785911 genotype to predict mild CI in patients with PD and rapid-eye-movement sleep behavior disorder ( 24 ). However, the high costs associated with both DAT imaging and genotypic sequencing, as well as the unsuitability of lumbar puncture for certain individuals, limit the broad application of this model in clinical settings.…”

Predictors of cognitive impairment in newly diagnosed Parkinson’s disease with normal cognition at baseline: A 5-year cohort study

“…PD patients with MCI (PD-MCI) were defined as scores on two or more of the HVLT total recall, HVLT recognition discrimination, JOLO, LNS, SFT, and SDMT were more than 1.5 standard deviations below normal, with no functional impairment due to CI. These criteria have been applied and validated in several studies (Schrag et al, 2017;Chen et al, 2021).…”