Prognostic Factors of Staphylococcus aureus Bloodstream Infection in ICU Patients and Establishment of a Prediction Model

Aims/Background: Staphylococcus aureus bacteremia (SAB) bloodstream infection (BSI) is a common complication among patients treated in the intensive care unit (ICU), predisposing them to high morbidity and mortality. The mortality rate at one and three months is 18% and 27%, respectively, and the recurrence and reinfection rate reaches 9%. This study aims to analyze prognostic factors for ICU patients with SAB BSI and establish a prediction model. Methods: A total of 210 SAB BSI patients admitted to the ICU from January 2020 to December 2023 were retrospectively selected. Patients were randomly divided in a 3:2 ratio into a modeling group (n = 126) and a validation group (n = 84). Within the modeling group, patients were further categorized into the good prognosis group (n = 75) and the poor prognosis group (n = 51) based on their prognosis outcomes. Univariate and binary logistic regression analyses were conducted to identify prognostic factors for SAB BSI patients. A prediction model was constructed using SPSS, receiver operating characteristic (ROC) curves were generated with R programming language, and calibration and decision curve analysis (DCA) curves were utilized to assess the model’s application value. Results: Inappropriate initial antibiotic therapy, infection source, Acute Physiology and Chronic Health Evaluation II (APACHE II) score, and central venous catheter placement showed significant differences (p < 0.05). The results of binary logistic regression analysis indicated that inappropriate initial antibiotic therapy, infection source, APACHE II score, and central venous catheter placement were prognostic factors for SAB BSI patients (p < 0.05). The model equation was Logit(P) = –3.549 + (0.871X1) + (0.959X2) + (0.070X3) + (0.832X4). The model in the modeling group and the validation group showed a calibration curve with a slope close to 1, which indicates good consistency between the predicted risk and the actual risk. The ROC analysis results indicated that in the validation group, the model had an area under the curve of 0.7857 with a standard error of 0.0331 (95% confidence interval (CI): 0.7229–0.8518, p < 0.001) and a Youden’s index of 0.61, resulting in a sensitivity of 80.96% and a specificity of 79.64%. The decision curve analysis (DCA) curve demonstrated that the model had a clear positive net benefit. Conclusion: Inappropriate initial antibiotic therapy, infection source, APACHE II score, and central venous catheter placement are prognostic factors for SAB BSI patients receiving care in the ICU. This study successfully established and validated a prediction model for SAB BSI.