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目的:探讨影响江门地区严重创伤结局的各种因素,建立适合本地区使用的严重创伤结局预测模型(AASCOT),为提高创伤救治水平及合理分配医疗资源提供依据。方法:回顾性分析本地区1092例严重创伤患者的资料,以严重创伤生存率为反应变量,对解剖损伤评分、SIRS评分、生理评分等进行Logistic回归分析,并计算各种因素的权重系数。结果:GCS、SIRS和收缩压(SBP)进入Logistic回归方程,解剖损伤评分及年龄因素并未进入回归方程。AASCOT模型的非线性回归方程为Ps=1/(1+e~(-b)),e=2.718282;其中钝伤b=-5.964+1.548×GCS+1.199×Sbp+(-0.510)×SIRS;穿透伤b=-4.057+1.283×GCS+1.020×Sbp+(-0.946)×SIRS。结论:GCS、SIRS和SBP是影响本地区严重创伤结局的重要因素;AASCOT模型适合本地区国人的创伤结局预测,建议在本地区推广使用。
OBJECTIVE: To explore various factors that affect the severity of traumatic outcome in Jiangmen region and to establish a model of severe traumatic outcome prediction (AASCOT) suitable for the region to provide the basis for improving the level of trauma and rational distribution of medical resources. Methods: The data of 1092 severe trauma patients in our area were retrospectively analyzed. Logistic regression analysis was used to analyze the anatomical injury score, SIRS score and physiology score with serious trauma survival rate as the response variable. The weight coefficients of various factors were calculated. Results: GCS, SIRS and systolic blood pressure (SBP) entered the logistic regression equation. The anatomical damage scores and age factors did not enter the regression equation. The non-linear regression equation of AASCOT model is Ps = 1 / (1 + e ~ (-b)), e = 2.718282; the blunt injury is b = -5.964 + 1.548 × GCS + 1.199 × Sbp + Penetrating injury b = -4.057 + 1.283 × GCS + 1.020 × Sbp + (- 0.946) × SIRS. Conclusions: GCS, SIRS and SBP are the important factors affecting the serious trauma outcome in this area. The AASCOT model is suitable for predicting the traumatic outcome of Chinese people in this area and is recommended to be used in this area.