A Novel Prediction Model for Bloodstream Infections in Hepatobiliary–Pancreatic Surgery Patients

Background Bloodstream infections (BSI) are an important source of postoperative mortality in hepatobiliary–pancreatic surgery (HBPS) patients, and no prediction model has been analyzed before. Methods Using big data from the electronic medical records of the administrative and culture databases of MacKay Memorial Hospital, we identified the potential risk factors for community-acquired and healthcare-associated BSI and mortality of patients who received HBPS. Subsequently, we analyzed the microorganisms’ profiles and antimicrobial susceptibility patterns for these BSI. Results BSI were found in 6.3% patients (349 of 5513 HBPS patients), and hospital mortality was 1.48% (82 of 5513). Dividing patients into low-, intermediate-, and high-risk groups on the basis of sex, age, status of comorbidity (renal failure, peptic ulcer disease, fluid and electrolyte disorders, and acute cholecystitis), a predictive BSI risk score model was developed. According to this model, BSI risk ranged from 1.43% to 11.95%; AUROC to predict BSI risk was 0.72 (95% CI 0.69–0.75). From this retrospective study, Enterobacteriaceae were the most common microorganisms that were isolated from BSI. For both community-acquired and healthcare-associated BSI, imipenem and colistin are the most successful. Conclusion This novel model can be useful to predict who is at risk of BSI after HBPS, and new prophylactic protocols for these patients are needed.