基于多中心的儿童颅脑创伤患者临床输血影响因素分析及预测模型构建  

Analysis of influencing factors of blood transfusion in children with traumatic brain injury and construc⁃tion of prediction model:A multi⁃center retrospective study

作　　者：刘威[1] 侯君 唐龙泉[2] 周鹏 钟艳 罗沁妍 况小雨 刘华[4] 熊紫清 熊伟 吴承高[1] 乐爱平[1,5] LIU Wei;HOU Jun;TANG Longquan;ZHOU Peng;ZHONG Yan;LUO Qinyan;KUANG Xiaoyu;LIU Hua;XIONG Ziqing;XIONG Wei;WU Chenggao;LE Aiping(Department of Transfusion Medicine,the First Affiliated Hospital of Nanchang University,Nanchang 330006,Jiangxi,China;不详)

机构地区：[1]南昌大学第一附属医院输血医学科,江西南昌330006 [2]抚州市第一人民医院输血科,江西抚州344099 [3]上饶市立医院输血科,江西上饶334099 [4]南昌市第一医院输血科,江西南昌330008 [5]输血医学江西省重点实验室,江西南昌330006

出　　处：《实用医学杂志》2025年第4期553-560,共8页The Journal of Practical Medicine

基　　金：江西省重点研发计划项目(编号:20192ACB50014);江西省科技创新平台项目(编号:20212BCD42006)。

摘　　要：目的通过分析儿童创伤性颅脑损伤(traumatic brain injury,TBI)患者临床输血影响因素,建立其临床输血预测模型,以指导临床输血决策。方法回顾性分析4家医疗机构2015年1月1日至2022年12月31日收治的1535例儿童TBI患者病历资料,根据患者院内是否输注红细胞将患者分为输血组和未输血组,分析两组患者间临床资料,通过logistic回归筛选患者院内输血相关危险因素,并采用列线图建立预测模型,利用ROC曲线评价模型的预测性能。结果输血组与未输血组患者基本资料、临床指征和实验室检测指标间均存在差异(P<0.05)。输血组患者院内死亡率、并发症发生率、机械通气、ICU入住率、住院时间均明显高于未输血组(P<0.05)。多因素logistic回归分析显示心率、其他骨折、治疗方式、血红蛋白(Hb)、血小板计数(Plt)、活化部分凝血活酶时间(APTT)、D-二聚体7个影响因素是TBI患者临床输血的独立危险因素。根据独立危险因素构建的临床输血预测模型ROC曲线下面积为0.95(95%CI:0.94~0.97);校准曲线和决策曲线亦显示该模型具有良好的预测效果。结论心率、其他骨折、治疗方式、Hb、Plt、APTT、D-二聚体是TBI患者临床输血的独立危险因素,据此构建的预测模型具有较好预测效果,可指导临床医师输血决策,有助于提高患者救治成功率。Objective To develop a predictive model for guiding blood transfusion decisions in pediatric patients with traumatic brain injury(TBI)by identifying and analyzing key factors that influence blood transfusion requirements.Methods A retrospective analysis was conducted on the clinical data of 1,535 pediatric patients with TBI admitted to four medical institutions from January 1,2015,to December 31,2022.Patients were divided into two groups:those who received red blood cell transfusions during hospitalization and those who did not.Comparative analyses were performed on demographic,clinical,and laboratory data between these two groups.Logistic regression analysis was used to identify risk factors associated with in-hospital blood transfusion,and a predictive model was developed using a nomogram.The performance of this model was evaluated using a receiver operating characteristic(ROC)curve.Results Significant differences were observed between the blood transfusion and non-blood transfusion groups in terms of baseline demographics,clinical indicators,and laboratory test results(all P<0.05).Patients in the blood transfusion group exhibited significantly higher in-hospital mortality,compli⁃cation rates,use of mechanical ventilation,ICU admission rates,and length of stay compared to those in the nonblood transfusion group(all P<0.05).Multivariate logistic regression analysis identified heart rate,presence of other fractures,treatment methods,hemoglobin(Hb),platelet count(Plt),activated partial thromboplastin time(APTT),and D-dimer levels as independent risk factors for blood transfusion in TBI patients.The area under the ROC curve for the blood transfusion prediction model,based on these independent risk factors,was 0.95(95%CI:0.94~0.97),indicating excellent predictive accuracy.Calibration and decision curves further validated the robust⁃ness and reliability of the model′s predictive capacity.Conclusions Heart rate,presence of other fractures,treatment methods,Hb,Plt count,APTT,and D-dimer levels serve as independen

关 键 词：创伤性颅脑损伤 临床输血 LOGISTIC回归 列线图 儿童 

分 类 号：R446.1[医药卫生—诊断学]