Digital therapeutics-based lumbar core exercise for patients with low back pain: A prospective exploratory pilot study.

阅读:6
作者:Son Seong, Yoo Byung Rhae, Jeong Yu Mi
OBJECTIVE: This study aimed to implement a digital therapeutics-based approach based on motion detection technology and analyze the clinical results for patients with chronic low back pain (LBP). METHODS: A prospective, single-arm clinical trial was conducted with 22 patients who performed mobile app-based sitting core twist exercise for 12 weeks. Clinical outcomes were assessed using the visual analog scale (VAS) for LBP, Oswestry Disability Index-Korean version (K-ODI), and EuroQol-5 dimension 5-level version (EQ-5D-5L) every 4 weeks after the initiation of treatment. Laboratory tests for factors associated with muscle metabolism, plain X-ray for evaluating sagittal balance, and magnetic resonance imaging for calculating cross-sectional area (CSA) of back muscles were performed at pretreatment and 12 weeks post-treatment. RESULTS: The study population included 20 female patients with an average age of 45.77 ± 15.45 years. The clinical outcomes gradually improved throughout the study period in the VAS for LBP (from 6.05 ± 2.27 to 2.86 ± 1.86), K-ODI (from 16.18 ± 6.19 to 8.64 ± 5.58), and EQ-5D-5L (from 11.09 ± 3.24 to 7.23 ± 3.89) (p < 0.001, respectively). The laboratory test results did not show significant changes. Pelvic incidence (from 53.99 ± 9.70° to 50.80 ± 9.20°, p = 0.002) and the mismatch between pelvic incidence and lumbar lordosis (from 8.97± .67° to 5.28 ± 8.57°, p = 0.027) decreased significantly. Additionally, CSA of erector spinae and total back muscles increased by 5.20% (p < 0.001) and 3.08% (p = 0.013), respectively. CONCLUSIONS: The results of this study suggest that the efficacy of digital therapy-based lumbar core exercise for LBP is favorable. However, further large-scale randomized controlled studies are necessary.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。