中国全科医学 ›› 2026, Vol. 29 ›› Issue (14): 1858-1866.DOI: 10.12114/j.issn.1007-9572.2025.0045

• 论著 • 上一篇    

类风湿关节炎疼痛合并中枢敏化的临床特征分析及影响因素研究

刘龙晓1, 徐愿2, 陈艳宇1, 薛淇1, 方云龙1, 罗瑞莉1, 李彦奇1, 王金平2,*(), 陶庆文2,*()   

  1. 1.100029 北京市,北京中医药大学研究生院
    2.100029 北京市,国家中西医结合医学中心 中日友好医院中医风湿病科
  • 收稿日期:2025-02-12 修回日期:2025-03-28 出版日期:2026-05-15 发布日期:2026-04-14
  • 通讯作者: 王金平, 陶庆文

  • 作者贡献:

    刘龙晓、王金平提出研究思路、设计研究方案;徐愿、王金平进行论文修订;陈艳宇、薛淇、方云龙、罗瑞莉负责数据收集与整理;刘龙晓、李彦奇负责统计学处理、图表的绘制与展示;刘龙晓负责撰写论文;王金平、陶庆文负责论文的质量控制与审查,对文章整体负责,监督管理。

  • 基金资助:
    中日友好医院"菁英计划"人才培育工程项目(ZRJY2023-QM21); 国家自然科学基金青年科学基金项目(82204901); 中央高水平医院临床业务费专项临床研究项目(2022-NHLHCRF-LX-02-02)

Analysis of Clinical Characteristics and Influencing Factors of Rheumatoid Arthritis with Pain Combined with Central Sensitization

LIU Longxiao1, XU Yuan2, CHEN Yanyu1, XUE Qi1, FANG Yunlong1, LUO Ruili1, LI Yanqi1, WANG Jinping2,*(), TAO Qingwen2,*()   

  1. 1. Graduate School, Beijing University of Traditional Chinese Medicine, Beijing 100029, China
    2. Department of TCM Rheumatism, National Center for Integrative Medicine/China-Japan Friendship Hospital, Beijing 100029, China
  • Received:2025-02-12 Revised:2025-03-28 Published:2026-05-15 Online:2026-04-14
  • Contact: WANG Jinping, TAO Qingwen

摘要: 背景 中枢敏化(CS)是类风湿关节炎(RA)患者疼痛的重要影响因素,其临床特征及中医证候分布特点尚不清楚,在RA疼痛管理中易被忽视。 目的 探究RA疼痛与CS相关性,分析RA疼痛合并CS患者的临床特点及相关危险因素。 方法 采用横断面的研究方法,纳入2024年1—9月就诊于中日友好医院中医风湿病科的200例RA疼痛患者为研究对象,收集一般资料和实验室检查指标,采用疼痛视觉模拟评分(VAS)进行疼痛评估,并根据VAS评分结果将患者分为轻度组、中度组和重度组;采用28个关节疾病活动度评分(DAS28)进行疾病活动度评估;采用中枢敏化测评量表(CSI)进行CS评价,并根据CSI评分分为RA-CS组和RA-非CS组(简称RA-nCS组)。采用健康评估问卷残疾指数(HAQ-DI)进行健康状况评估,依据《类风湿关节炎病证结合诊疗指南》进行中医证候评估,采用疲劳严重程度视觉模拟量表(VAS-F)进行疲劳评估;采用多因素Logistic回归分析探索RA疼痛程度以及RA-CS影响因素;采用Bootstrap自助抽样进行内部验证,采用Hosmer-Lemeshow检验回归模型拟合度。 结果 纳入200例RA患者中,轻度组88例(44.0%)、中度组80例(40.0%)、重度组32例(16.0%)。3组年龄、压痛关节数(TJC28)、肿胀关节数(SJC28)、C反应蛋白(CRP)、红细胞沉降率(ESR)、DAS28-ESR、DAS28-CRP、VAS-F评分、CSI评分比较,差异均有统计学意义(P<0.05);多因素Logistic回归分析结果显示,DAS28-ESR(OR=3.948,95%CI=1.069~14.579,P=0.039)、CSI评分(OR=1.066,95%CI=1.035~1.099,P<0.001)是RA疼痛的独立影响因素。200例RA患者中,RA-CS组57例(28.5%),RA-nCS组143例(71.5%)。RA-CS组病程、晨僵时间、患者总体评估(PGA)、VAS-F评分、HAQ-DI高于RA-nCS组,ESR和肿瘤坏死因子α(TNF-α)水平低于RA-nCS组(P<0.05);RA-CS组出现屈伸不利、汗出、腰膝酸软、肝肾不足证和寒湿痹阻证患者数量高于RA-nCS组,关节发热数量低于RA-nCS组(P<0.05)。多因素Logistic分析结果显示,VAS-F评分升高(OR=1.735,95%CI=1.261~2.388,P<0.001)、汗出(OR=6.593,95%CI=1.656~26.242,P=0.007)是RA-CS的危险因素,关节发热(OR=0.242,95%CI=0.067~0.872,P=0.030)是RA-CS的保护因素。Bootstrap法验证结果显示模型具有良好一致性。Hosmer-Lemeshow检验结果显示,模型拟合度良好(χ2=9.532,P=0.299)。 结论 RA疼痛与CS密切相关,当RA患者表现出明显疲劳、汗出,而不伴关节发热时,评估CS并进行多维化疼痛管理至关重要。

关键词: 类风湿关节炎, 疼痛, 中枢敏化, 影响因素分析, Logistic回归

Abstract:

Background

Central sensitization (CS) is a significant factor influencing pain in patients with rheumatoid arthritis (RA). However, the clinical characteristics and distribution of traditional Chinese medicine (TCM) syndromes related to CS remain unclear, which is frequently neglected in the management of RA pain.

Objective

To investigate the correlation between RA pain and CS, and to explore the clinical characteristics and influencing factors of RA combined with CS.

Methods

The study included 200 RA patients who visited the Department of TCM Rheumatism at China-Japan Friendship Hospital from January to September 2024. General information and laboratory test indices were collected. Pain was assessed using the Visual Analogue Score (VAS), and patients were divided into mild, moderate, and severe groups based on their VAS scores. Disease activity was assessed using Disease Activity Score derivative for 28 joints (DAS28). The Central Sensitization Inventory (CSI) was employed for scoring CS and patients were divided into two groups based on CSI scores: the RA-CS group and the RA-non-CS group (referred to as the RA-nCS group). The Health Assessment Questionnaire-Disability Index (HAQ-DI) was utilized to assess health functioning status, while TCM syndromes were evaluated according to the Guidelines of Diagnosis and Treatment of Rheumatoid Arthritis Disease and Syndrome Combination. Fatigue was measured using the Validity and Reliability of A Scale to Assess Fatigue (VAS-F). Multivariate Logistic regression analysis were used to investigate the factors influencing RA pain levels and RA-CS. Using Bootstrap internal verification concordance index (C-index) and the Hosmer-Lemeshow goodness-of-fit test, the stability and accuracy of the regression model were verified and evaluated.

Results

Among the 200 RA patients included, 88 (44.0%) were classified in the mild pain group, 80 (40.0%) in the moderate pain group, and 32 (16.0%) in the severe pain group. There were significant differences in age, TJC28, SJC28, erythrocyte sedimentation rate (ESR), C-reactive protein (CRP), DAS28-ESR, DAS28-CRP, VAS-F, CSI scores among the three groups (P<0.05). Multivariate Logistic regressio analysis showed that DAS28-ESR (OR=3.948, 95%CI=1.069-14.579, P=0.039) and CSI score (OR=1.066, 95%CI=1.035-1.099, P<0.001) were independent influecing factors for RA pain. Among the 200 RA patients, 57 (28.5%) were in the RA-CS group and 143 (71.5%) in the RA-nCS group. Compared with the RA-nCS group, RA-CS group had higher disease duration, duration of morning stiffness, patients' global assessment (PGA), VAS-F score and HAQ-DI, and lower serum ESR and tumor necrosis factor α (TNF-α) levels (P<0.05). RA-CS patients had more adverse flexion and extension, sweating, lumbar and knee weakness, liver and kidney deficiency syndrome and cold-dampness obstruction syndrome, while joint fever was less (P<0.05). Multivariate Logistic regressio analysis showed that VAS-F score increasing (OR=1.735, 95%CI=1.261-2.388, P<0.001) and sweating (OR=6.593, 95%CI=1.656-26.242, P=0.007) were risk factors of RA-CS, and joint fever (OR=0.242, 95%CI=0.067-0.872, P=0.030) was protective factors of RA-CS. The bootstrap method validation demonstrated good model consistency, while the Hosmer-Lemeshow goodness-of-fit test confirmed adequate model fit (χ2=9.532, P=0.299).

Conclusion

The pain of RA patients is closely related to CS. When patients show obvious fatigue and sweating without joint fever, it is essential to evaluate CS and implement a multidimensional pain management approach.

Key words: Rheumatoid arthritis, Pain, Central sensitization, Analysis of influencing factors, Logistic regression

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