Transition phase towards psoriatic arthritis: clinical and ultrasonographic characterisation of psoriatic arthralgia.

来自 PUBMED

摘要:

Non-specific musculoskeletal pain is common in subjects destined to develop psoriatic arthritis (PsA). We evaluated psoriatic patients with arthralgia (PsOAr) compared with psoriasis alone (PsO) and healthy controls (HCs) using ultrasonography (US) to investigate the anatomical basis for joint symptoms in PsOAr and the link between these imaging findings and subsequent PsA transition. A cross-sectional prevalence analysis of clinical and US abnormalities (including inflammatory and structural lesions) in PsOAr (n=61), PsO (n=57) and HCs (n=57) was performed, with subsequent prospective follow-up for PsA development. Tenosynovitis was the only significant sonographic feature that differed between PsOAr and PsO (29.5% vs 5.3%, p<0.001), although synovitis and enthesitis were numerically more frequent in PsOAr. Five patients in PsOAr and one in PsO group developed PsA, with an incidence rate of 109.2/1000 person-years in PsOAr vs 13.4/1000 person-years in PsO (p=0.03). Visual Analogue Scale pain, Health Assessment Questionnaire, joint tenderness and US active enthesitis were baseline variables associated with PsA development. Tenosynovitis was associated with arthralgia in subjects with psoriasis. Baseline US evidence of enthesitis was associated with clinical PsA development in the longitudinal analysis. These findings are relevant for enriching for subjects at risk of imminent PsA development.

收起

展开

DOI:

10.1136/rmdopen-2019-001067

被引量:

29

年份:

1970

SCI-Hub (全网免费下载) 发表链接

通过 文献互助 平台发起求助,成功后即可免费获取论文全文。

查看求助

求助方法1:

知识发现用户

每天可免费求助50篇

求助

求助方法1:

关注微信公众号

每天可免费求助2篇

求助方法2:

求助需要支付5个财富值

您现在财富值不足

您可以通过 应助全文 获取财富值

求助方法2:

完成求助需要支付5财富值

您目前有 1000 财富值

求助

我们已与文献出版商建立了直接购买合作。

你可以通过身份认证进行实名认证,认证成功后本次下载的费用将由您所在的图书馆支付

您可以直接购买此文献,1~5分钟即可下载全文,部分资源由于网络原因可能需要更长时间,请您耐心等待哦~

身份认证 全文购买

相似文献(267)

参考文献(35)

引证文献(29)

来源期刊

-

影响因子:暂无数据

JCR分区: 暂无

中科院分区:暂无

研究点推荐

关于我们

zlive学术集成海量学术资源,融合人工智能、深度学习、大数据分析等技术,为科研工作者提供全面快捷的学术服务。在这里我们不忘初心,砥砺前行。

友情链接

联系我们

合作与服务

©2024 zlive学术声明使用前必读