Objective To create a prediction model for clinical blood transfusion decision-making by analyzing the factors that affect blood transfusion in patients with traumatic brain injury(TBI).Methods The clinical data of 3 579 patients with TBI admitted to the First Affiliated Hospital of Nanchang University from January 1,2015 to June 30,2021 were analyzed retrospectively.The patients were divided into transfusion group and non-transfusion group based on in-hospital red blood cell transfusion.The patients were randomly divided into training set and test set according to the ratio of 7∶3.The clinical information of two groups as well as clinical prognostic outcomes were examined.The risk factors associated with in-hospital blood transfusion were screened using logistic regression to create a nomogram predictive model,and the model's predictive capability was assessed.Results There were differences in basic data,clinical indications and laboratory test indexes between TBI patients with blood transfusion and those without blood transfusion(P<0.05).The in-hospital mortality,complication rate,mechanical ventilation,intensive care unit admission and hospitalization time in the blood transfusion group were significantly higher than those in the non-blood transfusion group(P<0.05).Age≥60 years,heart rate,Glasgow coma score,skull fracture,other fractures,hemorrhagic shock,Hct,INR and Ca were included in the nomogram model.The area under the ROC curve of the nomogram model in the training set and the test set was 0.931(95%CI:0.921-0.941)and 0.920(95%CI:0.902-0.938),and the sensitivity and specificity were 80.0%,88.8%and 78.0%,87.0%,respectively.Conclusions Nomogram prediction model has good performance,which can be used to predict the blood transfusion demand of TBI patients,assist clinicians in blood transfusion decision-making,and improve the success rate of treatment.
traumatic brain injuryblood transfusionlogistic regressionnomogrampredictive model
国家科技期刊平台
NSTL
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