Chronic pain patients can be classified into four groups: Clustering-based discriminant analysis of psychometric data from 4665 patients referred to a multidisciplinary pain centre (a SQRP study)
To subgroup chronic pain patients using psychometric data and regress the variables most responsible for subgroup discrimination. Cross-sectional, registry-based study. Chronic pain patients assessed at a multidisciplinary pain centre between 2008 and 2015. Data from the Swedish quality registry for...
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Published in | PloS one Vol. 13; no. 2; p. e0192623 |
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Main Authors | , , , , |
Format | Journal Article |
Language | English |
Published |
United States
Public Library of Science
08.02.2018
Public Library of Science (PLoS) |
Subjects | |
Online Access | Get full text |
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Summary: | To subgroup chronic pain patients using psychometric data and regress the variables most responsible for subgroup discrimination.
Cross-sectional, registry-based study.
Chronic pain patients assessed at a multidisciplinary pain centre between 2008 and 2015.
Data from the Swedish quality registry for pain rehabilitation (SQRP) were retrieved and analysed by principal component analysis, hierarchical clustering analysis, and partial least squares-discriminant analysis.
Four subgroups were identified. Group 1 was characterized by low "psychological strain", the best relative situation concerning pain characteristics (intensity and spreading), the lowest frequency of fibromyalgia, as well as by a slightly older age. Group 2 was characterized by high "psychological strain" and by the most negative situation with respect to pain characteristics (intensity and spreading). Group 3 was characterized by high "social distress", the longest pain durations, and a statistically higher frequency of females. The frequency of three neuropathic pain conditions was generally lower in this group. Group 4 was characterized by high psychological strain, low "social distress", and high pain intensity.
The identification of these four clusters of chronic pain patients could be useful for the development of personalized rehabilitation programs. For example, the identification of a subgroup characterized mainly by high perceived "social distress" raises the question of how to best design interventions for such patients. Differentiating between clinically important subgroups and comparing how these subgroups respond to interventions is arguably an important area for further research. |
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 Competing Interests: One of the authors (AIL) is a statistician who owns a small company (Quality Stat AB) that sells consultancy services mainly to different quality registers and research groups in Sweden. For several years, SQRP (with funding from SALAR) has purchased her services to handle practical tasks around the registry including various statistical summaries to the participating clinics. This was also done for this study, requiring more demanding statistical analyses. However, in this specific study, EB performed the statistical analyses and the role of AIL was of a supervisory nature (hence the contributions statement in the manuscript and in the online submission form). In conclusion, her company did not sponsor the project and her commercial affiliation did not play a role in the project. AFA Insurance and research-ALF (Linköping University hospital) provided support in the form of salaries for authors EB and BG. SALAR provided support in the form of salaries for authors ALI. This does not alter our adherence to PLOS ONE policies on sharing data and materials. There are no patents, products in development or marketed products to declare. The specific roles of these authors are articulated in the ‘author contributions’ section. |
ISSN: | 1932-6203 1932-6203 |
DOI: | 10.1371/journal.pone.0192623 |