Nonmotor symptom burden grading as predictor of cognitive impairment in Parkinson's disease.

Cognitive Dysfunction / diagnosis Humans Longitudinal Studies Parkinson Disease / complications Retrospective Studies Severity of Illness Index
MMSE Nonmotor symptom burden grading Nonmotor symptoms Parkinson's disease cognitive impairment

Journal

Brain and behavior
ISSN: 2162-3279
Titre abrégé: Brain Behav
Pays: United States
ID NLM: 101570837

Informations de publication

Date de publication:
05 2021
Historique:
revised: 27 12 2020
received: 21 06 2020
accepted: 31 01 2021
pubmed: 2 3 2021
medline: 1 7 2021
entrez: 1 3 2021
Statut: ppublish

Résumé

Identifying predictors of incident cognitive impairment (CI), one of the most problematic long-term outcomes, in Parkinson's disease (PD) is highly relevant for personalized medicine and prognostic counseling. The Nonmotor Symptoms Scale (NMSS) provides a global clinical assessment of a range of NMS, reflecting NMS burden (NMSB), and thus may assist in the identification of an "at-risk" CI group based on overall NMSB cutoff scores. To investigate whether specific patterns of PD NMS profiles predict incident CI, we performed a retrospective longitudinal study on a convenience sample of 541 nondemented PD patients taking part in the Nonmotor Longitudinal International Study (NILS) cohort, with Mini-Mental State Examination (MMSE), NMSS, and Scales for Outcomes in PD Motor Scale (SCOPA Motor) scores at baseline and last follow-up (mean 3.2 years) being available. PD patients with incident CI (i.e., MMSE score ≤ 25) at last follow-up (n = 107) had severe overall NMSB level, significantly worse NMSS hallucinations/perceptual problems and higher NMSS attention/memory scores at baseline. Patients with CI also were older and with more advanced disease, but with no differences in disease duration, dopamine replacement therapy, sex, and comorbid depression, anxiety, and sleep disorders. Our findings suggest that a comprehensive baseline measure of NMS and in particular hallucinations and perceptual problems assessed with a validated single instrument can be used to predict incident CI in PD. This approach provides a simple, holistic strategy to predict future CI in this population.

Sections du résumé

BACKGROUND
Identifying predictors of incident cognitive impairment (CI), one of the most problematic long-term outcomes, in Parkinson's disease (PD) is highly relevant for personalized medicine and prognostic counseling. The Nonmotor Symptoms Scale (NMSS) provides a global clinical assessment of a range of NMS, reflecting NMS burden (NMSB), and thus may assist in the identification of an "at-risk" CI group based on overall NMSB cutoff scores.
METHODS
To investigate whether specific patterns of PD NMS profiles predict incident CI, we performed a retrospective longitudinal study on a convenience sample of 541 nondemented PD patients taking part in the Nonmotor Longitudinal International Study (NILS) cohort, with Mini-Mental State Examination (MMSE), NMSS, and Scales for Outcomes in PD Motor Scale (SCOPA Motor) scores at baseline and last follow-up (mean 3.2 years) being available.
RESULTS
PD patients with incident CI (i.e., MMSE score ≤ 25) at last follow-up (n = 107) had severe overall NMSB level, significantly worse NMSS hallucinations/perceptual problems and higher NMSS attention/memory scores at baseline. Patients with CI also were older and with more advanced disease, but with no differences in disease duration, dopamine replacement therapy, sex, and comorbid depression, anxiety, and sleep disorders.
CONCLUSIONS
Our findings suggest that a comprehensive baseline measure of NMS and in particular hallucinations and perceptual problems assessed with a validated single instrument can be used to predict incident CI in PD. This approach provides a simple, holistic strategy to predict future CI in this population.

Identifiants

DOI: 10.1002/brb3.2086 PMID: 33645912 PMC: PMC8119808
pubmed: 33645912
doi: 10.1002/brb3.2086
pmc: PMC8119808
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

e02086

Informations de copyright

© 2021 The Authors. Brain and Behavior published by Wiley Periodicals LLC.

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Auteurs

Panteleimon Oikonomou (P)

Department of Neurosciences, King's College London, Institute of Psychiatry, Psychology & Neuroscience, London, UK.
Parkinson Foundation Centre of Excellence at King's College Hospital, London, UK.
Department of Neurology and Neurophysiology, Medical Center-University of Freiburg, Freiburg, Germany.
ORCID: 0000-0002-3973-2861

Daniel J van Wamelen (DJ)

Department of Neurosciences, King's College London, Institute of Psychiatry, Psychology & Neuroscience, London, UK.
Parkinson Foundation Centre of Excellence at King's College Hospital, London, UK.
Department of Neurology, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Centre, Nijmegen, the Netherlands.

Daniel Weintraub (D)

Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
Parkinson's Disease Research, Education and Clinical Center (PADRECC), Philadelphia Veterans Affairs Medical Center, Philadelphia, PA, USA.

Dag Aarsland (D)

Department of Old Age Psychiatry, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, United Kingdom.

Dominic Ffytche (D)

Department of Old Age Psychiatry, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, United Kingdom.

Pablo Martinez-Martin (P)

Center for Networked Biomedical Research in Neurodegenerative Diseases (CIBERNED), Carlos III Institute of Health, Madrid, Spain.

Carmen Rodriguez-Blazquez (C)

Center for Networked Biomedical Research in Neurodegenerative Diseases (CIBERNED), Carlos III Institute of Health, Madrid, Spain.
National Centre of Epidemiology and CIBERNED, Carlos III Institute of Health, Madrid, Spain.

Valentina Leta (V)

Department of Neurosciences, King's College London, Institute of Psychiatry, Psychology & Neuroscience, London, UK.
Parkinson Foundation Centre of Excellence at King's College Hospital, London, UK.

Corinne Borley (C)

Department of Neurosciences, King's College London, Institute of Psychiatry, Psychology & Neuroscience, London, UK.
Parkinson Foundation Centre of Excellence at King's College Hospital, London, UK.

Carolina Sportelli (C)

Department of Neurosciences, King's College London, Institute of Psychiatry, Psychology & Neuroscience, London, UK.
Parkinson Foundation Centre of Excellence at King's College Hospital, London, UK.

Dhaval Trivedi (D)

Department of Neurosciences, King's College London, Institute of Psychiatry, Psychology & Neuroscience, London, UK.
Parkinson Foundation Centre of Excellence at King's College Hospital, London, UK.

Aleksandra M Podlewska (AM)

Department of Neurosciences, King's College London, Institute of Psychiatry, Psychology & Neuroscience, London, UK.
Parkinson Foundation Centre of Excellence at King's College Hospital, London, UK.

Katarina Rukavina (K)

Department of Neurosciences, King's College London, Institute of Psychiatry, Psychology & Neuroscience, London, UK.
Parkinson Foundation Centre of Excellence at King's College Hospital, London, UK.

Alexandra Rizos (A)

Department of Neurosciences, King's College London, Institute of Psychiatry, Psychology & Neuroscience, London, UK.
Parkinson Foundation Centre of Excellence at King's College Hospital, London, UK.

Claudia Lazcano-Ocampo (C)

Department of Neurosciences, King's College London, Institute of Psychiatry, Psychology & Neuroscience, London, UK.
Parkinson Foundation Centre of Excellence at King's College Hospital, London, UK.
Department of Neurology, Hospital Sotero del Río, Santiago de Chile, Chile.

Kallol Ray Chaudhuri (K)

Department of Neurosciences, King's College London, Institute of Psychiatry, Psychology & Neuroscience, London, UK.
Parkinson Foundation Centre of Excellence at King's College Hospital, London, UK.

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questionsmedicales.fr › Troubles mentaux › Troubles neurocognitifs › Troubles de la cognition › Dysfonctionnement cognitif › Nonmotor symptom burden grading as predictor...
questionsmedicales.fr › Eucaryotes › Animaux › Chordés › Vertébrés › Mammifères › Eutheria › Primates › Haplorhini › Catarrhini › Hominidae › Humains › Nonmotor symptom burden grading as predictor...
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questionsmedicales.fr › Maladies du système nerveux › Maladies neurodégénératives › Maladie de Parkinson › Nonmotor symptom burden grading as predictor...
questionsmedicales.fr › Environnement et santé publique › Santé publique › Méthodes épidémiologiques › Caractéristiques des études épidémiologiques › Études épidémiologiques › Études de cohortes › Études rétrospectives › Nonmotor symptom burden grading as predictor...
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