Risk Factors Analysis And Prognostic Risk Model Construction Of Sepsis In ICU After Esophageal Cancer Operation

Objective:As one of the most serious postoperative complications of esophageal cancer,sepsis leads to poor prognosis in the early postoperative period.At present,there are few studies on sepsis in patients admitted to ICU after esophageal cancer surgery.The purpose of our study was to investigate the predictive value of hematological indicators for the occurrence and prognosis of sepsis in patients admitted to ICU after esophageal cancer surgery,and to establish a relevant predictive model,so as to facilitate early clinical decision-making,strengthen perioperative management and improve prognosis.Methods:This retrospective study included patients with esophageal squamous cell carcinoma who underwent surgical treatment at Sichuan Cancer Hospital between December 2018 and January 2021 and were admitted to the intensive care unit after surgery.The patients were screened according to the inclusion and exclusion criteria from the hospital electronic medical record system,and the clinical data of patients meeting the criteria were collected.Predictive variables included general demographic data,clinical features,and hematological indicators of first admission to the ICU.The patients were divided into sepsis group and non-sepsis group according to whether they had sepsis or not.SPSS 25.0 statistical software was used to analyze the two groups of data.Independent sample t test was used for measurement data consistent with normal distribution,while Mann-Whitney U test was used for measurement data inconsistent with normal distribution.The chi-square test or Fisher’s exact probability method were used to compare the data groups.Univariate analysis and multivariate Logistic regression analysis were used to find the risk factors of sepsis.The selected independent risk factors were imported into R software to build a line graph prediction model,and its prediction efficiency was tested.Then,according to the outcome during hospitalization,patients with sepsis were divided into death group and improvement group.Binary Logistic regression analysis was performed by progressive forward regression method(LR)to find meaningful hematological indicators for predicting sepsis death.The predictive value was obtained by drawing ROC curve.Results:1.Among the 207 patients,30 had sepsis and 177 had no sepsis.Univariate analysis showed that patients with diabetes history(p=0.002),length of stay in ICU(p=0.001),preventive anticoagulation(p=0.006),APACHEII score(p=0.000),hemoglobin level(p=0.033),procalcitonin(p=0.033),and patients admitted to ICU after esophageal cancer surgery had abscess Toxicity related,the differences were statistically significant.Combined with clinical and research,p<0.1 was relaxed and included in multivariate regression analysis.The results showed that platelet count(OR=0.993,95%CI:0.987～0.999;P=0.028),diabetes history(OR=4.275,95%CI:1.456-12.557;P=0.008),APACHE II score(OR=1.177,95%CI:1.074～1.290;P=0.000)was an independent risk factor for septic infection in patients admitted to ICU after esophageal cancer surgery.Independent risk factors were imported into R software to build a line graph prediction model.The area under ROC curve was 0.7889,and the slope of the line graph calibration curve was close to 1.2.Among the 30 patients with sepsis,12 died and 18 improved.Multifactor Logistic regression analysis using stepwise forward regression(LR)showed that platelet count(OR=1.036,95%CI:1.005～1.068;P=0.024)was an independent risk factor for patients admitted to ICU after esophagectomy complicated with sepsis.PLT predicted the AUC of short-term death in patients with sepsis was 0.727(P<0.05),95%CI was 0.527～0.926,the optimal cut-off value was 144×10~9/L,the sensitivity was75%,and the specificity was 66.7%.Conclusion:1.Thrombocytopenia,history of diabetes,and increased APACHE II score are important factors for patients admitted to ICU after esophageal cancer surgery complicated with sepsis infection,which can help to predict the occurrence of sepsis.The establishment of a predictive model of a line graph has good differentiation and consistency.2.Platelet elevation within a certain range is an independent predictor of death in patients admitted to ICU after esophageal cancer surgery complicated with sepsis.