创伤输血患者预后转归及大量输血影响因素分析与预测评分方案建立

发布时间：2018-07-10 02:30

本文选题：创伤患者 + 大量输血　；参考：《南昌大学》2017年硕士论文

【摘要】：目的通过创伤输血患者临床资料的病例对照研究,探讨创伤输血患者临床预后转归的影响因素;通过创伤输血患者大量输血影响因素分析,以建立大量输血预测评分方案,并对其进行临床应用性能验证。方法收集南昌大学第一附属医院2013年1月1日至2016年12月31日所有出院创伤患者的临床病例资料,共纳入年龄≥18岁且急诊入院后24h内有红细胞(RBC)输注的创伤输血患者265例,根据患者急诊入院后24h内RBC输注量,将患者分为非大量输血组(24h内RBC输血量18u)和大量输血组(24h内RBC输注量≥18u),其中非大量输血组229例,大量输血组患者36例;(1)分析比较两组患者基本资料和临床预后转归相关指标,并采用Logistic回归分析患者院内死亡的相关影响因素,以探讨创伤输血患者临床预后转归的影响因素;(2)采用线性回归分析创伤输血患者大量输血的影响因素,并筛选出创伤输血患者大量输血的独立影响因素;(3)采用创伤输血患者大量输血独立影响因素作为大量输血预测评分指标,通过分层赋值建立大量输血预测评分方案,并利用受试者工作特征曲线(ROC曲线)对其进行临床应用性能验证。结果(1)非大量输血与大量输血组患者性别、年龄和致伤原因间差异均不具统计学意义(P0.05),两组患者创伤严重度评分(ISS)、格拉斯哥昏迷评分(GCS)、心率(HR)、收缩压(SBP)与血红蛋白浓度(Hb)、凝血功能指标间差异均具有统计学意义(P0.05);(2)大量输血组患者60天死亡率和院内总死亡率明显高于非大量输血组(P0.05),其院内感染发生率、机械通气时间、ICU住院时间、总住院时间亦均明显高于非大量输血组(P0.05),两组患者均未发生输血不良反应;(3)创伤输血患者临床预后转归影响因素分析:(1)Logistic单因素回归分析显示:ISS、GCS、RBC输注量、新鲜冰冻血浆输注量、院内感染、ICU住院时间、机械通气时间、总住院时间均为患者院内死亡的危险因素(P0.05);(2)Logistic多因素回归分析显示:ISS、RBC输注量和院内感染是创伤输血患者院内死亡的独立危险因素(P0.05);(3)其回归模型诊断ROC曲线下面积(AUC)为0.80,显示该回归模型具有较高的诊断性能;(4)创伤输血患者大量输血影响因素及预测评分:(1)单因素回归分析显示:创伤类型、ISS、HR、SBP、Hb、凝血酶原时间(PT)、国际标准化比值(INR)、活化部分凝血活酶时间(APTT)、纤维蛋白原(Fbg)、剩余碱(BE)均为创伤输血患者大量输血的影响因素(P0.05);(2)多因素回归分析显示:创伤类型、ISS、HR、Hb、PT、Fbg、BE是创伤输血患者大量输血的独立影响因素(P0.05);(3)通过对创伤输血患者大量输血独立影响因素分层赋值,建立了大量输血预测评分方案,其总分为0-8分,ROC曲线分析结果显示AUC=0.91,灵敏度和特异度分别为88.9%和79.9%,认为当评分≥4分时,需要大量输血。结论大量输血创伤患者的并发症发生率与死亡率均明显增高,ISS、RBC输注量和院内感染是影响创伤输血患者院内死亡的独立危险因素。创伤类型、ISS、HR、Hb、PT、Fbg、BE是创伤输血患者大量输血的独立影响因素,其分层赋值预测评分方案认为当评分≥4分时需要大量输血,且具备良好的临床应用性能。
[Abstract]:Objective a case-control study of the clinical data of patients with traumatic blood transfusion was studied to explore the influencing factors of the prognosis of the patients with traumatic blood transfusion, and to establish a large number of blood transfusion prediction scoring schemes through analysis of the influential factors of blood transfusion in patients with traumatic blood transfusion, and to verify the clinical application of them. Methods collect the First Affiliated Hospital of Nanchang University. From January 1, 2013 to December 31, 2016, the clinical data of all patients who were discharged from discharge were included in 265 cases of traumatic blood transfusion with red blood cell (RBC) infusion in 24h and 24h after emergency admission. The patients were divided into non large blood transfusion group (24h RBC 18u) and a large number of blood transfusion groups according to the amount of RBC infusion within 24h after emergency admission. (24h internal RBC infusion amount is more than 18u), including 229 cases of non large blood transfusion group and 36 patients in large blood transfusion group; (1) analysis and comparison of the basic data of the two groups and the related indexes of clinical prognosis, and the correlation factors of hospital mortality in patients with Logistic regression, in order to explore the influencing factors of the prognosis of the patients with trauma transfusion; (2) adopt The linear regression analysis of the influential factors of massive blood transfusion in patients with trauma blood transfusion, and screening out the independent influencing factors of massive blood transfusion in patients with traumatic blood transfusion; (3) the independent influence factors of massive blood transfusion in patients with traumatic blood transfusion were used as a large number of blood transfusion prediction scores, and a large number of blood transfusion prediction scoring schemes were established by stratified assignment, and the subjects were employed. The characteristic curve (ROC curve) was used to verify its clinical application. Results (1) there was no significant difference in gender, age and cause of injury (P0.05), two groups of trauma severity score (ISS), Glasgow coma score (GCS), heart rate (HR), systolic blood pressure (SBP) and hemoglobin concentration (Hb). The difference of the blood coagulation function was statistically significant (P0.05). (2) the 60 day mortality rate and total hospital mortality in the large blood transfusion group were significantly higher than that of non large blood transfusion group (P0.05). The incidence of nosocomial infection, the time of mechanical ventilation, the time of ICU hospitalization, and the total hospitalization were also significantly higher than those of non large blood transfusion group (P0.05), and all the two groups were not sent. Adverse reaction of blood transfusion; (3) analysis of factors affecting the prognosis of clinical prognosis in patients with trauma transfusion: (1) Logistic single factor regression analysis showed that ISS, GCS, RBC infusion, fresh frozen plasma infusion, hospital infection, ICU hospitalization time, mechanical ventilation time, total hospitalization time were all risk factors for patients' hospital death (P0.05); (2) Logistic multiple factors Regression analysis showed that ISS, RBC infusion and nosocomial infection were independent risk factors (P0.05) for hospital death in patients with traumatic blood transfusion (P0.05); (3) the area under the ROC curve (AUC) was 0.80, indicating that the regression model had a high diagnostic performance; (4) the influence factors and prediction scores of massive blood transfusion in patients with trauma blood transfusion: (1) single factor regression. Analysis showed that the type of trauma, ISS, HR, SBP, Hb, prothrombin time (PT), international normalized ratio (INR), activated partial thromboplastin time (APTT), fibrinogen (Fbg), and residual alkali (BE) were all the factors affecting massive blood transfusion in patients with traumatic blood transfusion (P0.05). (2) multiple regression analysis showed that the type of trauma, ISS, HR, insufficiency, and blood transfusion The independent influence factor of large blood transfusion (P0.05); (3) through the stratified assignment of the independent influence factors of blood transfusion in patients with traumatic blood transfusion, a large number of blood transfusion prediction scores were set up, the total score was 0-8, the results of ROC curve analysis showed AUC=0.91, the sensitivity and specificity were 88.9% and 79.9%. It was considered that when the score was more than 4, it was necessary to lose a lot. Conclusion the incidence of complications and mortality in patients with massive blood transfusion were significantly higher. ISS, RBC infusion and nosocomial infection were independent risk factors affecting hospital death in patients with traumatic transfusion. The type of trauma, ISS, HR, Hb, PT, Fbg, BE were independent factors affecting the massive transfusion of blood transfusion in patients with traumatic blood transfusion, and their stratified assignment prediction scoring scheme was recognized. A large amount of blood transfusion is needed when the score is more than 4 points, and has good clinical application performance.
【学位授予单位】：南昌大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：R641;R457.1

【参考文献】