Objective: The aim of this study was to analyze whether distinct sleep disturbance subtypes could be empirically identified in patients with Parkinson’s disease (PD) based on the data-driven latent class analysis (LCA) approach.

Background: Sleep-related problems in PD have received great attention in recent years owing to their occurrence in the early stage of the disease, as well as their clinical influence in determining the morbidity, disability, and health-related quality of life (HRQoL) of patients with advanced PD. However, few studies have aimed to empirically outline the clinical heterogeneity of sleep-related problems in patients with PD.

Methods: All of the study patients were required to be on a known and stable anti-parkinsonian medication for the 4 weeks prior to study. Patients with secondary parkinsonism, atypical parkinsonian syndrome, concomitant treatment with hypnotics and/or antipsychotics, a score of < 20 on the Korean version of Mini-Mental State Examination (K-MMSE), or aged 40 years or younger at the onset of disease were excluded. The validity, reproducibility, scale precision, and internal consistency of the K-PDSS-2 were explored in a nationwide multicenter study of 122 patients with PD. Latent class analysis (LCA) was applied to derive subtypes of patients who experienced similar patterns in sleep-related problems and nocturnal disabilities.

Results: 122 patients (60 females and 62 males) were included at baseline. Age was 66.5 +/- 8.6 years, and PD symptom duration was 45.8 +/- 46.5 months. In the LCA, the parsimonious model was a three-class solution based on fit indices and interpretability. The LCA distinguished one baseline subtype, which included 63.9% of the study patients, and two subtypes with an increased risk of disordered sleep and nocturnal disability. Group differences based on a Kruskal–Wallis test were found in age, K-PDSS2 total score (both at baseline and retest), PDQ-39 summary index, UPDRS part I, K-MADRS score, K-NMSS total score, and four K-NMSS domains (sleep/fatigue, mood, attention/memory, and urinary domains).

Conclusions: Our LCA results empirically demonstrated the presence of the clinical multitude of sleep-related problems in patients with PD and supported the proposed factor structure in the original PDSS-2 validation study. The validity of our LCA-derived subtypes was supported by distinctive demographic and clinical features between groups.

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MDS Abstracts - https://www.mdsabstracts.org/abstract/utilizing-latent-class-analysis-to-explore-the-sleep-disturbance-subtypes-in-parkinsons-disease-patients/