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The Parkinson disease pain classification system: results from an international mechanism-based classification approach
Pain is a common nonmotor symptom in patients with Parkinson disease (PD) but the correct diagnosis of the respective cause remains difficult because suitable tools are lacking, so far. We developed a framework to differentiate PD- from non-PD-related pain and classify PD-related pain into 3 groups...
Autores principales: | , , , , , , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Wolters Kluwer
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7977616/ https://www.ncbi.nlm.nih.gov/pubmed/33044395 http://dx.doi.org/10.1097/j.pain.0000000000002107 |
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author | Mylius, Veit Perez Lloret, Santiago Cury, Rubens G. Teixeira, Manoel J. Barbosa, Victor R. Barbosa, Egberto R. Moreira, Larissa I. Listik, Clarice Fernandes, Ana M. de Lacerda Veiga, Diogo Barbour, Julio Hollenstein, Nathalie Oechsner, Matthias Walch, Julia Brugger, Florian Hägele-Link, Stefan Beer, Serafin Rizos, Alexandra Chaudhuri, Kallol Ray Bouhassira, Didier Lefaucheur, Jean-Pascal Timmermann, Lars Gonzenbach, Roman Kägi, Georg Möller, Jens Carsten Ciampi de Andrade, Daniel |
author_facet | Mylius, Veit Perez Lloret, Santiago Cury, Rubens G. Teixeira, Manoel J. Barbosa, Victor R. Barbosa, Egberto R. Moreira, Larissa I. Listik, Clarice Fernandes, Ana M. de Lacerda Veiga, Diogo Barbour, Julio Hollenstein, Nathalie Oechsner, Matthias Walch, Julia Brugger, Florian Hägele-Link, Stefan Beer, Serafin Rizos, Alexandra Chaudhuri, Kallol Ray Bouhassira, Didier Lefaucheur, Jean-Pascal Timmermann, Lars Gonzenbach, Roman Kägi, Georg Möller, Jens Carsten Ciampi de Andrade, Daniel |
author_sort | Mylius, Veit |
collection | PubMed |
description | Pain is a common nonmotor symptom in patients with Parkinson disease (PD) but the correct diagnosis of the respective cause remains difficult because suitable tools are lacking, so far. We developed a framework to differentiate PD- from non-PD-related pain and classify PD-related pain into 3 groups based on validated mechanistic pain descriptors (nociceptive, neuropathic, or nociplastic), which encompass all the previously described PD pain types. Severity of PD-related pain syndromes was scored by ratings of intensity, frequency, and interference with daily living activities. The PD-Pain Classification System (PD-PCS) was compared with classic pain measures (ie, brief pain inventory and McGill pain questionnaire [MPQ], PDQ-8 quality of life score, MDS-UPDRS scores, and nonmotor symptoms). 159 nondemented PD patients (disease duration 10.2 ± 7.6 years) and 37 healthy controls were recruited in 4 centers. PD-related pain was present in 122 patients (77%), with 24 (15%) suffering one or more syndromes at the same time. PD-related nociceptive, neuropathic, or nociplastic pain was diagnosed in 87 (55%), 25 (16%), or 35 (22%), respectively. Pain unrelated to PD was present in 35 (22%) patients. Overall, PD-PCS severity score significantly correlated with pain's Brief Pain Inventory and MPQ ratings, presence of dyskinesia and motor fluctuations, PDQ-8 scores, depression, and anxiety measures. Moderate intrarater and interrater reliability was observed. The PD-PCS is a valid and reliable tool for differentiating PD-related pain from PD-unrelated pain. It detects and scores mechanistic pain subtypes in a pragmatic and treatment-oriented approach, unifying previous classifications of PD-pain. |
format | Online Article Text |
id | pubmed-7977616 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Wolters Kluwer |
record_format | MEDLINE/PubMed |
spelling | pubmed-79776162021-03-29 The Parkinson disease pain classification system: results from an international mechanism-based classification approach Mylius, Veit Perez Lloret, Santiago Cury, Rubens G. Teixeira, Manoel J. Barbosa, Victor R. Barbosa, Egberto R. Moreira, Larissa I. Listik, Clarice Fernandes, Ana M. de Lacerda Veiga, Diogo Barbour, Julio Hollenstein, Nathalie Oechsner, Matthias Walch, Julia Brugger, Florian Hägele-Link, Stefan Beer, Serafin Rizos, Alexandra Chaudhuri, Kallol Ray Bouhassira, Didier Lefaucheur, Jean-Pascal Timmermann, Lars Gonzenbach, Roman Kägi, Georg Möller, Jens Carsten Ciampi de Andrade, Daniel Pain Research Paper Pain is a common nonmotor symptom in patients with Parkinson disease (PD) but the correct diagnosis of the respective cause remains difficult because suitable tools are lacking, so far. We developed a framework to differentiate PD- from non-PD-related pain and classify PD-related pain into 3 groups based on validated mechanistic pain descriptors (nociceptive, neuropathic, or nociplastic), which encompass all the previously described PD pain types. Severity of PD-related pain syndromes was scored by ratings of intensity, frequency, and interference with daily living activities. The PD-Pain Classification System (PD-PCS) was compared with classic pain measures (ie, brief pain inventory and McGill pain questionnaire [MPQ], PDQ-8 quality of life score, MDS-UPDRS scores, and nonmotor symptoms). 159 nondemented PD patients (disease duration 10.2 ± 7.6 years) and 37 healthy controls were recruited in 4 centers. PD-related pain was present in 122 patients (77%), with 24 (15%) suffering one or more syndromes at the same time. PD-related nociceptive, neuropathic, or nociplastic pain was diagnosed in 87 (55%), 25 (16%), or 35 (22%), respectively. Pain unrelated to PD was present in 35 (22%) patients. Overall, PD-PCS severity score significantly correlated with pain's Brief Pain Inventory and MPQ ratings, presence of dyskinesia and motor fluctuations, PDQ-8 scores, depression, and anxiety measures. Moderate intrarater and interrater reliability was observed. The PD-PCS is a valid and reliable tool for differentiating PD-related pain from PD-unrelated pain. It detects and scores mechanistic pain subtypes in a pragmatic and treatment-oriented approach, unifying previous classifications of PD-pain. Wolters Kluwer 2021-04 2020-10-08 /pmc/articles/PMC7977616/ /pubmed/33044395 http://dx.doi.org/10.1097/j.pain.0000000000002107 Text en Copyright © 2020 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of the International Association for the Study of Pain. This is an open access article distributed under the terms of the Creative Commons Attribution-Non Commercial-No Derivatives License 4.0 (CCBY-NC-ND) (http://creativecommons.org/licenses/by-nc-nd/4.0/) , where it is permissible to download and share the work provided it is properly cited. The work cannot be changed in any way or used commercially without permission from the journal. |
spellingShingle | Research Paper Mylius, Veit Perez Lloret, Santiago Cury, Rubens G. Teixeira, Manoel J. Barbosa, Victor R. Barbosa, Egberto R. Moreira, Larissa I. Listik, Clarice Fernandes, Ana M. de Lacerda Veiga, Diogo Barbour, Julio Hollenstein, Nathalie Oechsner, Matthias Walch, Julia Brugger, Florian Hägele-Link, Stefan Beer, Serafin Rizos, Alexandra Chaudhuri, Kallol Ray Bouhassira, Didier Lefaucheur, Jean-Pascal Timmermann, Lars Gonzenbach, Roman Kägi, Georg Möller, Jens Carsten Ciampi de Andrade, Daniel The Parkinson disease pain classification system: results from an international mechanism-based classification approach |
title | The Parkinson disease pain classification system: results from an international mechanism-based classification approach |
title_full | The Parkinson disease pain classification system: results from an international mechanism-based classification approach |
title_fullStr | The Parkinson disease pain classification system: results from an international mechanism-based classification approach |
title_full_unstemmed | The Parkinson disease pain classification system: results from an international mechanism-based classification approach |
title_short | The Parkinson disease pain classification system: results from an international mechanism-based classification approach |
title_sort | parkinson disease pain classification system: results from an international mechanism-based classification approach |
topic | Research Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7977616/ https://www.ncbi.nlm.nih.gov/pubmed/33044395 http://dx.doi.org/10.1097/j.pain.0000000000002107 |
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