Objective To investigate the risk factors of secondary traumatic coagulopathy in patients with traffic trauma.Methods A total of 122 patients with traffic trauma in Department of Emergency Surgery,the First Affiliated Hospital of Anhui Medical University(Dongcheng Hospital)from April 2022 to March 2023 were retrospectively collected.Patients were divided into the occurrence group(n=30)and the non-occurrence group(n=92).Body temperature,acidosis,hematoma enlargement after head CT examination,Glasgow coma score(GCS),trauma severity score(ISS),platelet count(PLT)and hemoglobin(Hb)at admission were collected and compared between the two groups.Multivariate Logistic regression was used to analyze risk factors of secondary traumatic coagulopathy in traffic trauma patients,and receiver operating characteristic(ROC)curve was used to analyze the predictive value of related factors for secondary traumatic coagulopathy.Results The body temperature,GCS,PLT and Hb in the occurrence group were lower than those in the non-occurrence group,while the ISS,incidence of acidosis and the incidence of increased hematoma after CT examination were higher than those in the non-occurrence group(all P<0.05).Multivariate Logistic regression analysis showed that low GCS,low Hb level,high ISS,acidosis and increased hematoma after head CT examination were risk factors at admission(P<0.05).The area under ROC curve(AUC)of the five factors combined for secondary traumatic coagulopathy in traffic trauma patients was 0.963,sensitivity was 83.3%and specificity was 96.7%.Conclusion Decreased GCS and Hb on admission,high ISS,acidosis and increased hematoma during head CT review are risk factors for secondary traumatic cotting disorder in traffic trauma patients,and the combination of these factors has high predictive value.

Objective To investigate the risk factors of secondary traumatic coagulopathy in patients with traffic trauma.Methods A total of 122 patients with traffic trauma in Department of Emergency Surgery,the First Affiliated Hospital of Anhui Medical University(Dongcheng Hospital)from April 2022 to March 2023 were retrospectively collected.Patients were divided into the occurrence group(n=30)and the non-occurrence group(n=92).Body temperature,acidosis,hematoma enlargement after head CT examination,Glasgow coma score(GCS),trauma severity score(ISS),platelet count(PLT)and hemoglobin(Hb)at admission were collected and compared between the two groups.Multivariate Logistic regression was used to analyze risk factors of secondary traumatic coagulopathy in traffic trauma patients,and receiver operating characteristic(ROC)curve was used to analyze the predictive value of related factors for secondary traumatic coagulopathy.Results The body temperature,GCS,PLT and Hb in the occurrence group were lower than those in the non-occurrence group,while the ISS,incidence of acidosis and the incidence of increased hematoma after CT examination were higher than those in the non-occurrence group(all P<0.05).Multivariate Logistic regression analysis showed that low GCS,low Hb level,high ISS,acidosis and increased hematoma after head CT examination were risk factors at admission(P<0.05).The area under ROC curve(AUC)of the five factors combined for secondary traumatic coagulopathy in traffic trauma patients was 0.963,sensitivity was 83.3%and specificity was 96.7%.Conclusion Decreased GCS and Hb on admission,high ISS,acidosis and increased hematoma during head CT review are risk factors for secondary traumatic cotting disorder in traffic trauma patients,and the combination of these factors has high predictive value.

A newly developed topological vector of atom Y_C, equilibrium electro-negativity of atom q_e, molecular structural information parameter[N_H~i(i=α, β)] and γ calibration parameter were used to describe the local chemical microenvironment of 63 acyclic alcoholic compounds. Quantitative structural spectrum relationships (QSSR) was systematically made on relationship between ~(13)C NMR chemical shifts of 353 carbon atoms and their molecular structure descriptors. By partial least square regression(PLS), the statistical results indicated that the model correlation coefficient and standard error were 0.9915 and 2.4827, respectively. And the average absolute error was only 2.01×10~(-6) between the calculated and experimental chemical shifts for 353 carbon atoms. To validate the estimation stability for internal samples and the predictive capability for external samples of resulting models, leave-molecule-out(LMO) cross validation(CV) and external validation were performed. Compared with the reported result, not only the number of descriptors employed in this study was much fewer, but also the calculation was much easier.