Usefulness of the STarT Back Screening Tool to Predict the Effect of Acupuncture Treatment: Evaluation of Its Risk Classification Focusing on the Changes in the Lumbar Pain Visual Analog Scale
- VernacularTitle:Usefulness of the STarT Back Screening Tool to Predict the Effect of Acupuncture Treatment: Evaluation of Its Risk Classification Focusing on the Changes in the Lumbar Pain Visual Analog Scale
- Author:
Erika MATSUDA
1
;
Hiroshi KONDO
2
Author Information
- Keywords: acupuncture; hierarchical multiple regression analysis; low back pain; prognosis prediction; STarT Back Screening Tool
- From:The Journal of The Japanese Society of Balneology, Climatology and Physical Medicine 2024;87(2):56-65
- CountryJapan
- Language:English
- Abstract: Background: The STarT (Subgrouping for Targeted Treatment) Back Screening Tool (SBST) is an established clinical evaluation tool that easily assesses the risk of chronic or refractory low back pain. This study aimed to examine the usefulness of acupuncture in patients with low back pain. Methods: A total of 71 outpatients with low back pain who underwent acupuncture and moxibustion at the Center for Integrative Medicine, Tsukuba University of Technology, between 2019 and 2022 were included in this study, regardless of the specific medical condition causing the pain. Survey items included the SBST and lumbar pain intensity visual analog scale (VAS). Demographic factors and contents of acupuncture treatment were collected from the medical charts. The VAS score 4 weeks after the start of treatment was used as an index of clinical outcome and was analyzed using repeated measures analysis of variance (ANOVA) and hierarchical multiple regression analysis. Results: Classification using the SBST at the first visit resulted in 36, 30, and 15 patients in the low-, medium-, and high-risk groups, respectively. Repeated-measures ANOVA showed statistically significant differences in the mean VAS values with respect to differences in time point (P < 0.01), group (P < 0.01), and interaction (P < 0.05). The VAS values after 4 weeks in the high-risk group were significantly higher than those in the other two groups (both P < 0.01). In the hierarchical multiple regression analysis, with VAS as the dependent variable, the relationship between SBST classification and VAS maintained a significant positive relationship in all models, including adjustments for interaction terms and patients’ background items. A simple slope analysis indicated that this relationship was more evident in patients with lower limb symptoms than in those without symptoms. Conclusion: The SBST could be a simple and useful tool for predicting the clinical outcomes of acupuncture.
