Predictive value of systemic immunity index for sepsis in low-medium risk community-acquired pneumonia

Objective:To assess the predictive value of systemic immune inflammation index(SII)for sepsis in low-and medium-risk community-acquired pneumonia.Methods:A total of 589 elderly patients with low-and medium-risk community-acquired pneumonia admitted to the Emergency Department of the Second Affiliated Hospital of Hainan Medical University from January 2020 to January 2023 were included as the research subjects,and the general information and laboratory test results of the patients were collected,and the optimal cut-off value of continuous variables for predicting sepsis in elderly patients with low-and medium-risk community-acquired pneumonia was determined by plotting the receiver work characteristic(ROC)curve,which was converted into dichotomous variables and univariate and multivariate logistic Regression analysis of the influencing factors of sepsis in elderly patients with low-and medium-risk community-acquired pneumonia.Based on this,a nomogram model is constructed to predict the risk of sepsis.The differentiation,consistency and accuracy of the model were verified by calibration curve and subject operating characteristic(ROC)curve,and the clinical utility of the model was determined by decision curve analysis.Results:A total of 589 elderly patients with low-and intermediate-risk community-acquired pneumonia were included in this study,of which 96(16.30%)developed sepsis.There were significant differences in age,diabetes mellitus and chronic obstructive pulmonary disease,Lac,PCT,SII and other indexes between sepsis and non-sepsis groups(P<0.05).Logistics regression analysis showed that age,diabetes mellitus and chronic obstructive pulmonary disease,Lac,and SII were independent risk factors for sepsis in elderly patients with low-and medium-risk community-acquired pneumonia.The nomogram prediction model was used to verify the results,and the AUC was 0.826(95%CI:0.780-0.872),and the calibration curve tended to the ideal curve with good accuracy.The decision curve shows that when the threshold of the model is between 0.10~0.78,the model has the advantage of clinical benefit.Conclusion:The nomogram prediction model constructed based on SII to predict sepsis in elderly patients with low-and medium-risk community-acquired pneumonia has good accuracy,which can predict the occurrence of sepsis early,help early identification of high-risk groups and timely intervention,and thus improve the prognosis of patients.