Development And Validation Of A Nomogram Prediction Model For Survival And Prognosis Of Adult Patients With Sepsis

Background:Sepsis is one of the major causes of death in critical patients worldwide,prognosis of patients with sepsis is still very poor.Intensive Care Over Nations(ICON)studies confirmed that approximately 29.5% of patients had sepsis on admission or during hospitalization,and the in-hospital mortality rate was 35.3%.In recent years,the level of treatment of sepsis has been greatly improved.The overall mortality rate of sepsis patients is decreasing,but the incidence of sepsis and the number of sepsis related deaths are increasing.This indicates that patients with sepsis still face great challenges in treatment and care.Therefore,in the process of diagnosis and treatment,it is necessary to evaluate the prognosis of patients and intervene the development of the disease as early as possible,so as to improve the prognosis of patients,reduce the mortality of sepsis patients to a certain extent,shorten the length of hospitalization and reduce the cost of hospitalization.Objective:The purpose of this study was to investigate the risk factors for mortality in sepsis patients and to construct a clinical prediction model,and to develop and validate a new nomogram to predict the risk of death in sepsis patients.Methods:Clinical data of sepsis patients older than 18 years admitted to the Intensive Care Unit of the Department of Intensive Care and Emergency Medicine in the First Hospital of Bethune,Jilin University from January 2020 to June 2022 were retrospectively collected.Multivariate logistic regression analyses were used to screen the independent risk factors of sepsis patients,which was used to construct the prediction model and conduct external verification,These risk factors were used to construct a nomogram.A series of validation methods,including calibration plots and area under the receiver operating characteristic curve(AUC),were used to validate the accuracy and reliability of the prediction model and nomogram.Decision curve analysis(DCA)was used to evaluate the clinical application value of the prediction model.Results:A total of 168 patients were included and divided into training cohort(n=123)and verification cohort(n=45)according to time.In univariate and multivariate logistic regression,five variables including age,CI,lactic acid,surgical treatment,and solid tumor were prognostic factors in sepsis patients.The area under the ROC curve(AUC)of our prediction model was 0.831,(95%CI 0.7577-0.905)and 0.814,(95%CI0.691-0.937)in the training cohort and validation cohort.The calibration curve shows that there is no significant difference between the predicted value and the measured value,which proves that the Nome graph has good accuracy.The DCA showed that the nomogram had good clinical value.Conclusion:Age,surgical treatment,solid tumor,lactic acid and coagulation indexes were independent risk factors for death in sepsis patients,based on these risk factors,a graph was developed to predict the death outcome of sepsis patients.The correction curve shows that the predicted value is in good agreement with the measured value.The analysis of decision curve shows that the column chart has good clinical value..