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Clinical Trial Summary

Disaster medical teams are formed by hospitals in response to the manpower needs of a large number of injured and sick patients. The current planning of hospitals for a large number of disaster medical manpower is too superficial. The application of today's inspection methods in the treatment of a large number of injured patients is not as good as it is. Therefore, understanding the scene situation has become the key point of manpower deployment. Today's internet transmission speed and computer artificial intelligence technology are very different from 9 years ago. The investigators adopt one more simple and easy-to-operate inspection method and use artificial intelligence technology to assist.


Clinical Trial Description

Disaster medical teams are formed by hospitals in response to the manpower needs of a large number of injured and sick patients. However, the current planning of hospitals for a large number of disaster medical manpower is too superficial. The application of today's inspection methods in the treatment of a large number of injured patients is not as good as it is. Therefore, understanding the scene situation has become the key point of manpower deployment. Today's network transmission speed and computer artificial intelligence technology are very different from 9 years ago. The image transmission of the communication software to understand the scene will help the hospital's manpower deployment or should the investigators adopt a more easy-to-operate inspection method and use artificial intelligence technology to assist Implementation method: 82 patients with a large number of injuries in the Ali mountain traffic accident over the years were included, medical records were reviewed. The photos of patients recorded at the hospital site and existing vital signs of the patients were mainly used to make grading of the traditional STAR triage and the AIS to understand the possible differences in image interpretation and injury detection. Excluding patients with incomplete clinical data of treatment, the statistical methods of the samples were Correlation analysis and Wilcoxon signed rank test, and the p value of statistical significance was 0.05 ;


Study Design


Related Conditions & MeSH terms


NCT number NCT05358418
Study type Observational
Source St. Martin De Porress Hospital
Contact
Status Completed
Phase
Start date December 1, 2022
Completion date September 30, 2023

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