An Analysis For The Epidemiological Characteristics, Trauma Care And Outcomes Of6889Trauma Patients In Single Trauma Center

Part I-An analysis for the epidemiological characteristics and trauma treatment of6889trauma patients admitted in Tongji HospitalObjective:A retrospective investigation was made to identify the epidemiological characteristics and trauma care of trauma patients admitted in Tongji Hospital, in order to provide basis for enacting the public health policies and improve the performance of trauma treatment.Methods:The data was from Medical Records Department of Tongji Hospital, collecting the data of trauma patients admitted from Jan.2007to Dec.2014. The data of basic information of trauma patients, mechanism of injury, trauma and ICU scores, trauma treatment and outcomes were collected. All the data was analyzed with SPSS20by t test, Chi-square test and regression analysis etc.Results:In this investigation, we collected totally6889cases of trauma patients, of which there were5331cases of male patients. The average age is (39.94+14.45). Trauma incidents mostly occurs in the age ranking from21to60years old, the most patients were peasant with low status of education. Trauma incidents often occur in the time from8o’clock to11o’clock and from13o’clock to20o’clock. The most common injury mechanisms are road traffic injuries and fallen injuries. More than50%trauma patients arrived in emergency room in less than one hour.30.67%trauma patient received emergency surgical treatment before transferred to Tongji Hospital, and most of them are debridement (48.75%) and abdominal operations (16.82%). The average ISS is (21.71±10.74), and average GCS is (12.68±3.63).69.24%of trauma patients are severity injured with ISS higher than16, and consist of the most part of traumatic death.16.03%trauma patients combined with shock when admitted in hospital.2639cases were sent into ICU directly after admission. The average APACHE-Ⅱ is (18.83±8.92), and average SAPS-Ⅱ is (33.36±18.28). The emergency operations were performed in3083cases within24hours after admission, and most of them are debridement (28.23%), abdominal operations (18.07%), craniocerebral operations (15.11%) and thoracic operations (13.33%). Among them,1441cases received blood transfusion during operation, the average PRBC is (6.64+5.11) units and FFP is (626.76±344.64)ml.1754cases (25.46%) of trauma patients were performed selective operations, and most of them are ORIF in limbs (44.42%). Complications happened in49.01%trauma patients in post-trauma period. The most common complication is SIRS, accounts for20.08%.292cases died in hospital, the mortality rate is4.24%. The pattern of death time shows a double-peak model,37.67%of death occurs in2days after trauma while39.73%of death occurs beyond1week after trauma. The main reason for leaving hospital is clinical cure and accurate rate is87.55%, and the main direction is local or nearby hospital.Conclusion:The most common kind of victims of trauma is young male, and the most common reason of injury is traffic accident, then high fall injury. More than50%trauma patients arrived in emergency room in less than one hour.2639cases were sent into ICU directly after admission.30.67%trauma patient received emergency surgical treatment before transferred to Tongji Hospital, and most of them are debridement and abdominal operations. The emergency operations were performed in3083cases within24hours after admission, and most of them are debridement, abdominal operations, craniocerebral operations and thoracic operations.25.46%of trauma patients were performed selective operations, and most of them are ORIF in limbs.69.24%of trauma patients are severity injured with ISS higher than16, and consist of the most part of traumatic death, and the mortality increases with increasing ISS. Complications happened in49.01%trauma patients in post-trauma period, and the most common complication is SIRS.292cases died in hospital, the mortality rate is4.24%. The pattern of death time shows a double-peak model. Part Ⅱ-An analysis for the epidemiological characteristics and the origins of trauma patients transferred to Tongji HospitalObjective:A retrospective investigation was made to identify the epidemiological characteristics and the origins of trauma patients transferred from non-Wuhan urban area to make certain the origins of trauma patients and the range of trauma emergency medical service. And confirm the priority and development direction of trauma emergency medical service, improve the ability of trauma treatment in this area.Methods:In this investigation, we collected the trauma patients transferred from non-Wuhan urban area from the trauma patients admitted in Tongji Hospital from Jan.2007to Dec.2014. The data we collected include the basic information, treatment in former hospital and outcomes. Referral origin is classified and analyzed statistically by county or district. All the data was analyzed with SPSS20.Results:Totally,4119trauma patients transferred from non-Wuhan urban area were collected. Among them,3283cases are male and make up79.71%, while836cases are female and count for20.29%. Male/Female ratio is3.93:1, higher than overall level (P<0.01). There are no difference between overall trauma patients and referrals in age, occupation and degree of education. The number of referrals has a trend of increasing year by year before2014. The average ISS of referrals is (24.21±10.17), and higher than overall level (P<0.001).182referrals died in hospital, and the mortality rate is4.42%. There is no statistical difference compared with total mortality rate, however higher than the mortality rate of the patients who received initial treatment in Tongji Hospital. According to the treatment in former hospital,3categories are classified. One is receiving no treatment or basic life support,701cases make up17.02%. The other one is receiving advanced life support or basic surgical treatment in emergency room of former hospital, totally2206cases (53.56%). The next is receiving treatment hospitalization, totally1212cases (29.42%). The trauma referrals admitted in our hospital come from59counties or districts in Hubei and Henan province. The first three counties (districts) of the largest number are Hanchuan, Caidan, Xinzhou. The trauma referral generally follows the principle of proximity and the principle of selection. With the increase of the distance from Wuhan City, referral number of trauma patients also gradually reduced. What influence the number of trauma referrals is the ability of trauma treatment in local hospital, among the counties of which the distances from Wuhan City are similar. The origins which have the largest number of trauma referrals mainly distribute in the range within100km from Wuhan.Conclusion:Trauma patients who need to transfer to the superior hospital are always serious injured, therefore it is necessary to improve the capacity of every parts of trauma care to benefit the outcomes of these trauma patients. The referrals have a higher male ratio, and higher average ISS and mortality rate than the initial trauma patients. Most of referrals received advanced life support or basic surgical treatment in former hospital. The trauma referral generally follows the principle of proximity and the principle of selection. The referrals mainly come from the counties or districts around Wuhan City within100km. Part III-An evaluation for risk factors of death and trauma and ICU scoring systemsObjective:Epidemiological characteristics and death risk factors were retrospectively analyzed by collecting the data292traumatic death patients, while evaluate the predictive effect of common trauma and ICU scoring systems for outcomes, in order to improve trauma treatment and reduce mortality rate.Methods:Classify the trauma patients admitted in Tongj Hospital from Jan.2007to Dec.2014into death group and survival group according to the trauma outcome. Choose and collect13variables related to the mortality of trauma patients based on the stage of trauma care, and trauma and ICU scoring systems including ISS, RTS, GCS, GOS, APACHE Ⅱ, SAPS Ⅱ. Find out the independent risk factors of death through univariate and multivariate analysis. Evaluate the predictive effect for trauma outcome through drawing ROC curve and calculating AUC. All the data was analyzed with SPSS20.Results:A total of6889trauma patients were enrolled in this study.292cases died and the mortality rate is4.24%. Among them,234cases are male, makes up80.14%, while58cases are female, make up19.86%. The average age of traumatic death patients is (44.80±15.39). According to injury mechanism, blunt injury has284cases(97.26%) and penetrating injury has8cases(2.74%). The most common injury mechanisms of traumatic death are road traffic injuries and fallen injuries. CNS injury and traumatic/hemorrhage shock consist of the main reason of acute death (P<0.001), and MOF consist of the main reason of late death (P<0.01). The following factors were related to mortality significantly after the univariate analysis:age, injury mechanism, time in emergency room, the treatment in former hospital, SBP, SI, ISS, RTS, GCS, APACHE Ⅱ, SAPS Ⅱ, emergency operation, transfusion and mechanical ventilation. Multivariate Logistic analysis showed that trauma and ICU scoring systems and mechanical ventilation are the independent risk factors. There is no significant difference on predictive effect of ISS, RTS, GCS, APACHE Ⅱ, SAPS Ⅱ for traumatic death. The cut-off of ISS, RTS, GCS, APACHE Ⅱ and SAPS Ⅱ is24,6.86,11,17,25, respectively.Conclusion:The pattern of death time shows a double-peak model. CNS injury and traumatic/hemorrhage shock consist of the main reason of acute death, and MOF consist of the main reason of late death. Trauma severity as well as mechanical ventilation is the independent risk factor of trauma death. Currently, common trauma and ICU scoring systems such as ISS, GCS, RTS, APACHE Ⅱ and SAPS Ⅱ have an excellent predictive effect. Using different scoring systems to make a comprehensive and objective assessment for severe trauma patients may improve trauma treatment and benefit trauma outcome. Part Ⅳ-A study of emergent severe trauma outcomes predicted with ASCOTObjective:To establish a new trauma outcome prediction model and calculate the weight coefficients based on ASCOT method, according to the data of severe trauma patients admitted in our department. And then contrast with the trauma outcome prediction models which based on the weight coefficients of ASCOT-MTOS and ASCOT-Huaxi models, in order to explore the model fit for the characteristics of trauma patients in this area.Methods:Retrospectively collected the data of trauma patients admitted in our department from Jan.2007to Dec.2014, screening standards are pre-hospital time within24hours and mAIS more than3. Two groups were divided by injury mechanism, they are blunt injury group and penetrate injury group. Determine the weight of related parameters based on the univariate analysis, and then calculate regression coefficients. Calculate the probability of survival (Ps) based on the weight coefficients of ASCOT-Tj, ASCOT-MTOS and ASCOT-Huaxi. Ps≥0.5predicts more likely to survive, while Ps<0.5predicts more likely to die. Compare the predictive effects of three kinds of weight coefficients for trauma outcome, through drawing the ROC curves and calculating accuracy, sensitivity, specificity, death misjudgment rate, survival misjudgment rate. All the data was analyzed with SPSS20.Results:Parameters were determined by univariate analysis:GCS, SBP, RR, AP-A, AP-B, AP-C, age and pre-hospital time, and then weight coefficients of ASCOT-Tj were obtained by calculating. Compare with the MTOS and Huaxi weight coefficients, the weight coefficients in this study add the weight of SBP and AP-B in penetrate injury group, also constant, AP-A and AP-B are increased while AP-C is reduced in both groups. This model has higher accuracy, specificity and lower survival misjudgment rate for predicting the outcome in both groups.Conclusion:ASCOT-Tj model has the largest AUC in ROC curve, and a better comprehensive prediction effect. This model fits for the characteristics of severe trauma patients in this area, may be more suitable for the region’s severe, especially blunt trauma outcome prediction, and should be verified and promoted in further clinical practice.