Maurel Sara, Giménez-Llort Lydia, Alegre-Martin Jose, Castro-Marrero Jesús
Department of Medicine, Universitat Autònoma de Barcelona, 08193 Barcelona, Spain.
Department of Psychiatry and Forensic Medicine, School of Medicine, Universitat Autònoma de Barcelona, 08193 Barcelona, Spain.
Biomedicines. 2023 Oct 23;11(10):2867. doi: 10.3390/biomedicines11102867.
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.
纤维肌痛（FM）是一种以肌肉骨骼疼痛和多种合并症为特征的疾病。我们的研究旨在根据纤维肌痛患者的核心临床症状和神经心理合并症，将其分为四类，以确定该疾病可能的治疗靶点。我们对251名根据2010年美国风湿病学会（ACR）病例标准转诊至初级保健机构的成年纤维肌痛患者进行了一项基于人群的队列研究。根据身体和情绪症状以及神经心理变量，通过K-中位数层次聚类分析将患者聚集为不同的类别。在纤维肌痛患者群体中识别出了四种不同的类别。整体聚类分析报告了一个四类特征（类别1：疼痛、疲劳、睡眠质量较差、僵硬、焦虑/抑郁以及工作能力丧失；类别2：不公正感、灾难化思维、积极情绪和消极情绪；类别3：正念和接纳；类别4：屈服）。对临床症状的第二次分析揭示了三个不同的亚组（类别1：疲劳、睡眠质量较差、僵硬以及工作困难；类别2：疼痛；类别3：焦虑和抑郁）。对神经心理变量的第三次分析提供了两个相反的亚组（类别1：在屈服、不公正感、灾难化思维和消极情绪方面得分较高的患者，类别2：在接纳、积极情绪和正念方面得分较高的患者）。这些实证结果支持了一些模型，这些模型假设在经典生物医学模型之外，神经生物学、心理和社会因素之间存在相互作用。对这些风险和保护因素进行详细评估对于区分纤维肌痛亚型至关重要，这有助于进一步确定其特定需求并设计量身定制的个性化治疗干预措施。
