Chrome Extension
WeChat Mini Program
Use on ChatGLM

The Japanese version of the STarT Back Tool predicts 6-month clinical outcomes of low back pain.

Journal of orthopaedic science : official journal of the Japanese Orthopaedic Association(2016)

Cited 12|Views11
No score
Abstract
BACKGROUND:The STarT Back Tool classifies patients into low-, medium-, or high-risk groups according to risk for chronic low back pain. The Japanese version of the STarT Back Tool (STarT-J) has been translated and psychometrically validated. The present analysis investigated the predictive ability of the STarT-J. METHODS:Baseline data were collected through an online survey conducted with Japanese patients with low back pain. Long-term outcomes were assessed in a 6-month follow-up survey. Clinical outcomes at 6 months were evaluated with a pain numerical rating scale, the Roland-Morris Disability Questionnaire, and the EuroQol 5 Dimension. Differences in these scores among the three STarT-J risk groups were analyzed. Participants' perceived changes in low back pain and overall health status were examined to determine associations between the chronicity of low back pain at 6 months and STarT-J risk groups. RESULTS:Data of 1228 volunteers who responded to the baseline and follow-up surveys were included in this analysis. Mean ± standard deviation (SD) scores for the pain numerical rating scale and the Roland-Morris Disability Questionnaire were highest in the high-risk group (5.6 ± 1.9 and 9.6 ± 7.5) and lowest in the low-risk group (3.9 ± 1.6 and 2.1 ± 3.5). Mean ± SD EuroQol 5 Dimension index scores were lowest in the high-risk group (0.66 ± 0.20) and highest in the low-risk group (0.86 ± 0.14). A small percentage of high-risk patients (5.3%) perceived improvement in low back pain at the 6-month follow-up. CONCLUSIONS:The STarT-J predicted 6-month pain and disability outcomes. The STarT-J is an easy-to-use tool to screen for patients who are more likely to have chronic low back pain, and may be useful to initiate stratified care in primary care settings.
More
Translated text
AI Read Science
Must-Reading Tree
Example
Generate MRT to find the research sequence of this paper
Chat Paper
Summary is being generated by the instructions you defined