The predictive value of the combined diagnosis with multiple indexes in the prognosis of septic patients after severe trauma

Yang Hui; Yang Haijie; Pan Xianfeng

doi:10.3969/j.issn.1002-1949.2024.04.010

Abstract：Objective To explore the relevant risk factors that affect the prognosis of septic patients after severe trauma for constructing a nomogram prediction model,and to evaluate the clinical value of the model.Methods A retrospective analysis was conducted on 100 patients with severe post-traumatic sepsis admitted to the emergency ICU of the 920 Hospital of the Joint Logistics Support Force from January 2017 to May 2023.According to clinical outcomes,the patients were divided into death group and survival group.The injury mechanism,injury type,infection site,hospitalization time,ICU stay time,mechanical ventilation time,acute physiology and chronic health evaluationⅡ(APACHEⅡ)score,Glasgow coma scale(GCS)score,sequential organ failure assessmen(SOFA)score after entry to ICU,procalcitonin(PCT)on the 7th day,cumulative fluid balance on the 7th day,and neutrophil/lymphocyte ratio(NLR)on the 7th day were collected from the two groups.Statistically significant indicators obtained by comparing the two groups were analyzed by univariate and multivariate Logistic regression analysis to screen independent risk factors for the mortality of patients with sepsis after severe trauma for constructing a predictive model.R software was used to draw Nomogram column charts,the predictive performance of the model was validated by receiver operating characteristic(ROC)curves and calibration curves,and the clinical net benefit of the model was evaluated by using decision curve analysis(DCA).Results PCT on the 7th day of ICU admission(95%CI 2.067-10.432,OR =4.644,P<0.001)and cumulative fluid balance on the 7th day(95%CI 1.529-6.079,OR =3.048,P = 0.002)were independent risk factors for the mortality in severe post-traumatic sepsis patients;The GCS score(95%CI 0.054-0.459,OR =0.158,P =0.001)was an independent risk factor associated with prognosis.Based on the results of multivariate Logistic regression analysis,a Nomogram model was established.After verification,the consistency index(C-index)of the predictive model was 0.902,and the calibration curve and fitting curve responded well.The AUC was 0.902,with a sensitivity of 85.7%and a specificity of 87.9%.The clinical value of the model was evaluated by DCA,and the results showed that the probability interval of the maximum net benefit threshold was 12.0%-100.0%,indicating that the model has a high net benefit value.Conclusions PCT on the 7th day of ICU admission and cumulative fluid balance on the 7th day are independent risk factors for the mortality of patients with severe post-traumatic sepsis,while GCS score is an independent risk factor related to prognosis.Based on this,the Nomogram model has good predictive effect and clinical value.