AI Article Synopsis
- The study aims to assess the effectiveness of using grade classification for injury severity scores in the Shonan-area Medical Control Council based on injury data from 2016.
- A total of 11,668 injury cases were analyzed, revealing that most cases were mild/moderate, while a smaller number were severe or fatal; key variables were identified as significant risk factors.
- The findings suggest that incorporating Grade classification enhances the discrimination ability of severity assessments, particularly highlighting the significant influence of the "Load & Go adaptation."
Article Abstract
Objective: To clarify the usefulness of grade classification for injury severity scores applied in Shonan-area Medical Control Council.
Methods: The participants included 11,668 injury cases that occurred in this jurisdiction from April to September 2016. Multivariate analysis was performed using "severity at the time of the disease" a s the response variable. The AUC-ROC was also compared with and without Grade classification, and potential improvements in discrimination ability were examined.
Results: There were 11,271 subjects in the "mild/moderate" group and 397 subjects in the "severe/dead" group. Almost all explanatory variables were significant and independent risk factors in the multivariate analysis, and the "Load & Go adaptation" had a particularly high odds ratio of 20.2. Discrimination ability improved (AUC-ROC: 0.773 VS. 0.787) when Grade classification was added to the conventional pre-hospitalization evaluation items.
Conclusion: Load & Go adaptation has a great influence on severity, and discrimination ability is improved through Grade classification.
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