医学
物理疗法
骨关节炎
康复
随机对照试验
物理医学与康复
膝关节痛
内科学
病理
替代医学
作者
Brian Østergaard Sørensen,Per Aagaard,Mikkel H. Hjortshoej,S Hansen,Charlotte Suetta,Christian Couppé,S. Peter Magnusson,Finn Elkjær Johannsen
出处
期刊:PLOS ONE
[Public Library of Science]
日期:2023-12-14
卷期号:18 (12): e0295666-e0295666
标识
DOI:10.1371/journal.pone.0295666
摘要
Osteoarthritis (OA) is a common disease with high socioeconomical costs. In Denmark, standard rehabilitation (SR) consists of a combination of patient education and supervised physical exercise involving a standardized neuromuscular training program. As an evidence-based alternative, high-load (>70% 1RM) resistance training (HIRT) has shown positive rehabilitation effects in knee-OA but may not be tolerated in all patients (~25%) due to knee joint pain. However, low-load resistance training (20-40% 1RM) with concurrent partial blood-flow restriction (BFR) appears to produce effects similar to HIRT yet involving reduced joint pain during and after exercise. The aim is to examine the effect of low-load BFR training compared to SR on pain, thigh muscle mass and muscle function in adults with knee-OA. We hypothesize that 12 weeks of BFR will lead to superior improvements in pain, muscle mass and mechanical muscle function compared to SR.90 participants diagnosed with radiographic knee-OA will be randomized to either BFR or SR twice a week for 12 weeks. BFR will consist of two selected lower limb strength exercises performed with an inflated pneumatic occlusion cuff. Intervention procedures in SR consist of a full 8 weeks GLA:D course followed by 4 weeks of team group training. Primary outcome variable is the change in KOOS-Pain subscale from baseline to 12 weeks. Secondary outcome variables are changes in pain sensitivity, functional performance, muscle mass and mechanical muscle function. Intention-to-treat and per-protocol analyses will be conducted. One-way analysis of variance will be performed to evaluate between-group changes. Pre-to-post intervention comparisons will be analyzed using a mixed linear model. Regression analysis will be performed to evaluate potential associations between selected outcome variables.
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