Conservative treatments for greater trochanteric pain syndrome: a systematic review

医学 物理疗法 梅德林 科克伦图书馆 奇纳 系统回顾 随机对照试验 观察研究 心理干预 矫形学 荟萃分析 循证医学 外科 内科学 替代医学 病理 法学 精神科 政治学
作者
Paul Barratt,Nathan Brookes,Annalisa Newson
出处
期刊:British Journal of Sports Medicine [BMJ]
卷期号:51 (2): 97-104 被引量:111
标识
DOI:10.1136/bjsports-2015-095858
摘要

Background Greater trochanteric pain syndrome (GTPS) can have a significant effect on quality of life. Aim To evaluate the conservative treatments for GTPS. Design This systematic review assessed risk of bias using the Cochrane Risk of Bias Tool and Cochrane Risk of Bias Tool for non-randomised studies of interventions. Data sources On 13 January 2016, a comprehensive search was conducted, with no limit on year of publication for relevant studies in the MEDLINE, CINAHL, AMED and EMBASE databases. Eligibility criteria for selecting studies English language randomised controlled trials, case–control or cohort studies reporting outcome data for conservative treatments for adults having a diagnosis of GTPS, or trochanteric bursitis, were included. Results 8 studies (n=696) were eligible for inclusion in the review; corticosteroid injections (CSI) (n=6), shockwave therapy (n=2), home training (n=1) and orthotics (n=1). Based on pain, CSI demonstrated superior outcomes for up to 3 months compared with home training, radial shockwave therapy (RSWT) and usual care, in 4 studies demonstrating either a low or moderate risk of bias. Fluoroscopy-guided injections failed to show additional benefit. RSWT and home training had limited evidence. No conclusions can be drawn regarding the use of orthotics due to the serious risk of bias and methodological flaws within that study. Conclusions This review demonstrates a paucity of high-quality research for the conservative treatments of GTPS. The risk of bias was low in only one study, demonstrating no additional benefit with fluoroscopically guided injections. Risk of bias in all remaining studies was varied. Standardisation of diagnostic criteria and outcome measures is essential to enable more powerful analysis.
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