Abstract
Purpose:This study aimed at exploring the application of trauma time axis management in the treat-ment of severe trauma patients by using the Medicalsystem trauma system.Methods:We performed a retrospective cohort study involving patients with severe trauma.Patients who were admitted before the application of the Medicalsystem trauma system were divided into before system group;patients who were admitted after the application of the system were divided into after system group.Comparison was made between the two groups.For normally distributed data,means were reported along with standard deviation,and comparisons were made using the independent samples t test.Categorical data were compared using the Chi-square test.The Mann-Whitney U test was used to compare nonparametric variables.Results:There were 528 patients admitted to the study during the study period.There was no significant statistical difference in the time from the start of trauma team to arrive at the resuscitation room be-tween the two groups.The time from arrival at hospital to endotracheal intubation,to ventilator therapy,to blood transfusion,to completion of CT scan,to completion of closed thoracic drainage,to the start of operation,as well as the length of stay in resuscitation room and hospital were significantly lower after the application of the Medicalsystem trauma system.The mortality was decreased by 8.6％in the after system group compared with that in the before system group,but there was no statistical difference.Conclusion:The Medicalsystem trauma system can optimize diagnosis and treatment process for trauma patients,and accordingly improve the treatment efficiency and shorten the treatment time.Therefore,the Medicalsystem trauma system deserves further popularization and promotion.
基金项目
This work was supported by China Scholarship Council(CSC 202006920081)
Jiangsu Provincial Medical Youth Talent,China(QNRC2016724)
Natural Science Research of Jiangsu Higher Edu-cation Institutions of China(18KJB320016)
Basic Research on Medical and Health Application of the People's Livelihood Science and Technology Project of Suzhou Science and(SYS2020102)
NETL
NSTL
维普
万方数据