Evidence map›Paper›PMID 41180816›Full record

ArticleFrontiers in aging neuroscience2025

Characterizing sleep-related phenotypes with patient-reported outcomes in Parkinson's disease.

Sandeep Grover, Celina Chand, Mollie McKenzie Acuff, Joshua Farahnik, Laurie K Mischley

Abstract read
In one paragraph

Article in Frontiers in aging neuroscience, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Sandeep GroverInstitute of Human Genetics, University of Marburg, Marburg, Germany.
Celina ChandBastyr University Research Institute, Kenmore, WA, United States.
Mollie McKenzie AcuffBastyr University Research Institute, Kenmore, WA, United States.
Joshua FarahnikBastyr University Research Institute, Kenmore, WA, United States.
Laurie K MischleyBastyr University Research Institute, Kenmore, WA, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: Sleep disturbances are common in Parkinson's disease (PD) and significantly impact patients' quality of life. However, the clinical symptoms associated with poor sleep remain underexplored. The Patient-Reported Outcomes in PD (PRO-PD) is a remote patient monitoring tool enabling symptom-level resolution. The goal of this study was to use the PRO-PD to describe symptomatic differences associated with sleep quality. Methods: A cross-sectional analysis was conducted using baseline data of an ongoing prospective cohort study of patients with idiopathic PD (IPD). Sleep quality was assessed using the Pittsburgh Sleep Quality Index (PSQI), while disease severity was evaluated using the PRO-PD. Multivariable regression analysis was performed to judge the association between PSQI and PRO-PD, adjusting for age, gender, income, and years since diagnosis. Results: Among 331 participants, 70.2% of patients with IPD reported poor sleep quality (PSQI>5). Furthermore, a significant positive correlation was observed between PSQI scores and PRO-PD scores ( Conclusion: Poor sleepers showed uniformly higher PRO-PD burden, with a non-motor phenotype consisting of insomnia, fatigue, anxiety, and depression consistent with prior reports. The PRO-PD further identified additional equally-correlated symptoms, such as poor balance, lacking motivation, and social withdrawal providing expanded perspective. These findings highlight the need for routine sleep assessments in PD management and suggest that interventions targeting sleep disturbances may alleviate symptom burden and improve QoL. Future longitudinal studies could help establish causality and explore therapeutic strategies to improve sleep quality in PD.

Indexed as

fatigueinsomnianon-motor symptomspatient-reported outcomessleep disorderssleep quality

Identifiers

PMID41180816
PMCPMC12571807

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.