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使用纤维肌痛影响问卷修订版对美国大型纤维肌痛患者样本进行分组。

Subgrouping a Large U.S. Sample of Patients with Fibromyalgia Using the Fibromyalgia Impact Questionnaire-Revised.

机构信息

Department of Basic, Evolutive and Educational Psychology, Faculty of Psychology, Universitat Autònoma de Barcelona, 08193 Cerdanyola del Vallés, Spain.

AGORA Research Group, Teaching, Research & Innovation Unit, Parc Sanitari Sant Joan de Déu, 08830 St. Boi de Llobregat, Spain.

出版信息

Int J Environ Res Public Health. 2020 Dec 31;18(1):247. doi: 10.3390/ijerph18010247.

Abstract

Fibromyalgia (FM) is a heterogeneous and complex syndrome; different studies have tried to describe subgroups of FM patients, and a 4-cluster classification based on the Fibromyalgia Impact Questionnaire-Revised (FIQR) has been recently validated. This study aims to cross-validate this classification in a large US sample of FM patients. A pooled sample of 6280 patients was used. First, we computed a hierarchical cluster analysis (HCA) using FIQR scores at item level. Then, a latent profile analysis (LPA) served to confirm the accuracy of the taxonomy. Additionally, a cluster calculator was developed to estimate the predicted subgroup using an ordinal regression analysis. Self-reported clinical measures were used to examine the external validity of the subgroups in part of the sample. The HCA yielded a 4-subgroup distribution, which was confirmed by the LPA. Each cluster represented a different level of severity: "Mild-moderate", "moderate", "moderate-severe", and "severe". Significant differences between clusters were observed in most of the clinical measures (e.g., fatigue, sleep problems, anxiety). Interestingly, lower levels of education were associated with higher FM severity. This study corroborates a 4-cluster distribution based on FIQR scores to classify US adults with FM. The classification may have relevant clinical implications for diagnosis and treatment response.

摘要

纤维肌痛症 (FM) 是一种异质性和复杂的综合征;不同的研究试图描述 FM 患者的亚组,最近基于修订后的纤维肌痛影响问卷 (FIQR) 已经验证了一种 4 聚类分类。本研究旨在在美国 FM 患者的大样本中交叉验证这种分类。使用了一个由 6280 名患者组成的混合样本。首先,我们使用 FIQR 项目水平得分进行了层次聚类分析 (HCA)。然后,潜在剖面分析 (LPA) 用于确认分类法的准确性。此外,开发了一个聚类计算器,通过有序回归分析来估计使用预测亚组。部分样本中的自我报告临床指标用于检验亚组的外部有效性。HCA 产生了 4 个亚组分布,LPA 证实了这一点。每个聚类代表不同的严重程度:“轻度-中度”、“中度”、“中度-重度”和“重度”。在大多数临床指标(例如,疲劳、睡眠问题、焦虑)中观察到集群之间存在显著差异。有趣的是,较低的教育水平与较高的 FM 严重程度相关。这项研究证实了基于 FIQR 评分的 4 聚类分布,以对美国成年人进行纤维肌痛症分类。这种分类可能对诊断和治疗反应具有重要的临床意义。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b58e/7796452/dd87d3e1dfc8/ijerph-18-00247-g001.jpg

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