Hierarchical Cluster Analysis Based on Clinical and Neuropsychological Symptoms Reveals Distinct Subgroups in Fibromyalgia

Fibromyalgia (FM) is a condition characterized by musculoskeletal pain and multiple comorbidities. Our study aimed to identify four clusters of FM patients according to their core clinical symptoms and neuropsychological comorbidities to identify possible therapeutic targets in the condition. We per...

Descripción completa

Detalles Bibliográficos
Autores: Maurel, Sara, Gimenez-Llort, Lydia|||0000-0002-4091-489X, Alegre Martín, José|||0000-0002-7582-7585, Castro-Marrero, Jesús|||0000-0002-2481-3052
Tipo de recurso: artículo
Fecha de publicación:2023
País:España
Institución:Universitat Autònoma de Barcelona
Repositorio:Dipòsit Digital de Documents de la UAB
Idioma:inglés
OAI Identifier:oai:ddd.uab.cat:288283
Acceso en línea:https://ddd.uab.cat/record/288283
https://dx.doi.org/urn:doi:10.3390/biomedicines11102867
Access Level:acceso abierto
Palabra clave:Chronic pain
Fibromyalgia
Cluster analysis
Neuropsychological symptoms
Fatigue
Mindfulness
id ES_3078e18558c99a728f3a4fc896917618
oai_identifier_str oai:ddd.uab.cat:288283
network_acronym_str ES
network_name_str España
repository_id_str
spelling Hierarchical Cluster Analysis Based on Clinical and Neuropsychological Symptoms Reveals Distinct Subgroups in FibromyalgiaA Population-Based Cohort StudyMaurel, SaraGimenez-Llort, Lydia|||0000-0002-4091-489XAlegre Martín, José|||0000-0002-7582-7585Castro-Marrero, Jesús|||0000-0002-2481-3052Chronic painFibromyalgiaCluster analysisNeuropsychological symptomsFatigueMindfulnessFibromyalgia (FM) is a condition characterized by musculoskeletal pain and multiple comorbidities. Our study aimed to identify four clusters of FM patients according to their core clinical symptoms and neuropsychological comorbidities to identify possible therapeutic targets in the condition. We performed a population-based cohort study on 251 adult FM patients referred to primary care according to the 2010 ACR case criteria. Patients were aggregated in clusters by a K-medians hierarchical cluster analysis based on physical and emotional symptoms and neuropsychological variables. Four different clusters were identified in the FM population. Global cluster analysis reported a four-cluster profile (cluster 1: pain, fatigue, poorer sleep quality, stiffness, anxiety/depression and disability at work; cluster 2: injustice, catastrophizing, positive affect and negative affect; cluster 3: mindfulness and acceptance; and cluster 4: surrender). The second analysis on clinical symptoms revealed three distinct subgroups (cluster 1: fatigue, poorer sleep quality, stiffness and difficulties at work; cluster 2: pain; and cluster 3: anxiety and depression). The third analysis of neuropsychological variables provided two opposed subgroups (cluster 1: those with high scores in surrender, injustice, catastrophizing and negative affect, and cluster 2: those with high scores in acceptance, positive affect and mindfulness). These empirical results support models that assume an interaction between neurobiological, psychological and social factors beyond the classical biomedical model. A detailed assessment of such risk and protective factors is critical to differentiate FM subtypes, allowing for further identification of their specific needs and designing tailored personalized therapeutic interventions. 22023-01-0120232023-01-01Articlehttp://purl.org/coar/resource_type/c_6501VoRhttp://purl.org/coar/version/c_970fb48d4fbd8a85info:eu-repo/semantics/articleapplication/pdfhttps://ddd.uab.cat/record/288283https://dx.doi.org/urn:doi:10.3390/biomedicines11102867reponame:Dipòsit Digital de Documents de la UABinstname:Universitat Autònoma de BarcelonaInglésengInstituto de Salud Carlos III https://doi.org/10.13039/501100004587 PI09/90301open accesshttp://purl.org/coar/access_right/c_abf2Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial, la distribució, la comunicació pública de l'obra i la creació d'obres derivades, fins i tot amb finalitats comercials, sempre i quan es reconegui l'autoria de l'obra original.https://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccessoai:ddd.uab.cat:2882832026-06-06T12:50:31Z
dc.title.none.fl_str_mv Hierarchical Cluster Analysis Based on Clinical and Neuropsychological Symptoms Reveals Distinct Subgroups in Fibromyalgia
A Population-Based Cohort Study
title Hierarchical Cluster Analysis Based on Clinical and Neuropsychological Symptoms Reveals Distinct Subgroups in Fibromyalgia
spellingShingle Hierarchical Cluster Analysis Based on Clinical and Neuropsychological Symptoms Reveals Distinct Subgroups in Fibromyalgia
Maurel, Sara
Chronic pain
Fibromyalgia
Cluster analysis
Neuropsychological symptoms
Fatigue
Mindfulness
title_short Hierarchical Cluster Analysis Based on Clinical and Neuropsychological Symptoms Reveals Distinct Subgroups in Fibromyalgia
title_full Hierarchical Cluster Analysis Based on Clinical and Neuropsychological Symptoms Reveals Distinct Subgroups in Fibromyalgia
title_fullStr Hierarchical Cluster Analysis Based on Clinical and Neuropsychological Symptoms Reveals Distinct Subgroups in Fibromyalgia
title_full_unstemmed Hierarchical Cluster Analysis Based on Clinical and Neuropsychological Symptoms Reveals Distinct Subgroups in Fibromyalgia
title_sort Hierarchical Cluster Analysis Based on Clinical and Neuropsychological Symptoms Reveals Distinct Subgroups in Fibromyalgia
dc.creator.none.fl_str_mv Maurel, Sara
Gimenez-Llort, Lydia|||0000-0002-4091-489X
Alegre Martín, José|||0000-0002-7582-7585
Castro-Marrero, Jesús|||0000-0002-2481-3052
author Maurel, Sara
author_facet Maurel, Sara
Gimenez-Llort, Lydia|||0000-0002-4091-489X
Alegre Martín, José|||0000-0002-7582-7585
Castro-Marrero, Jesús|||0000-0002-2481-3052
author_role author
author2 Gimenez-Llort, Lydia|||0000-0002-4091-489X
Alegre Martín, José|||0000-0002-7582-7585
Castro-Marrero, Jesús|||0000-0002-2481-3052
author2_role author
author
author
dc.subject.none.fl_str_mv Chronic pain
Fibromyalgia
Cluster analysis
Neuropsychological symptoms
Fatigue
Mindfulness
topic Chronic pain
Fibromyalgia
Cluster analysis
Neuropsychological symptoms
Fatigue
Mindfulness
description Fibromyalgia (FM) is a condition characterized by musculoskeletal pain and multiple comorbidities. Our study aimed to identify four clusters of FM patients according to their core clinical symptoms and neuropsychological comorbidities to identify possible therapeutic targets in the condition. We performed a population-based cohort study on 251 adult FM patients referred to primary care according to the 2010 ACR case criteria. Patients were aggregated in clusters by a K-medians hierarchical cluster analysis based on physical and emotional symptoms and neuropsychological variables. Four different clusters were identified in the FM population. Global cluster analysis reported a four-cluster profile (cluster 1: pain, fatigue, poorer sleep quality, stiffness, anxiety/depression and disability at work; cluster 2: injustice, catastrophizing, positive affect and negative affect; cluster 3: mindfulness and acceptance; and cluster 4: surrender). The second analysis on clinical symptoms revealed three distinct subgroups (cluster 1: fatigue, poorer sleep quality, stiffness and difficulties at work; cluster 2: pain; and cluster 3: anxiety and depression). The third analysis of neuropsychological variables provided two opposed subgroups (cluster 1: those with high scores in surrender, injustice, catastrophizing and negative affect, and cluster 2: those with high scores in acceptance, positive affect and mindfulness). These empirical results support models that assume an interaction between neurobiological, psychological and social factors beyond the classical biomedical model. A detailed assessment of such risk and protective factors is critical to differentiate FM subtypes, allowing for further identification of their specific needs and designing tailored personalized therapeutic interventions.
publishDate 2023
dc.date.none.fl_str_mv 2
2023-01-01
2023
2023-01-01
dc.type.none.fl_str_mv Article
http://purl.org/coar/resource_type/c_6501
VoR
http://purl.org/coar/version/c_970fb48d4fbd8a85
dc.type.openaire.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv https://ddd.uab.cat/record/288283
https://dx.doi.org/urn:doi:10.3390/biomedicines11102867
url https://ddd.uab.cat/record/288283
https://dx.doi.org/urn:doi:10.3390/biomedicines11102867
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.relation.none.fl_str_mv Instituto de Salud Carlos III https://doi.org/10.13039/501100004587 PI09/90301
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2
https://creativecommons.org/licenses/by/4.0/
dc.rights.openaire.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv open access
http://purl.org/coar/access_right/c_abf2
https://creativecommons.org/licenses/by/4.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.source.none.fl_str_mv reponame:Dipòsit Digital de Documents de la UAB
instname:Universitat Autònoma de Barcelona
instname_str Universitat Autònoma de Barcelona
reponame_str Dipòsit Digital de Documents de la UAB
collection Dipòsit Digital de Documents de la UAB
repository.name.fl_str_mv
repository.mail.fl_str_mv
_version_ 1869405547684429824
score 15,300719

Similares en LA Referencia