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

Po Sheng Yang, Chang Pan Liu, Yi Chiung Hsu, Chuen Fei Chen, Chi Chan Lee, Shih Ping Cheng

Research output: Contribution to journalArticlepeer-review

6 Scopus citations

Abstract

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.

Original languageEnglish
Pages (from-to)1294-1302
Number of pages9
JournalWorld Journal of Surgery
Volume43
Issue number5
DOIs
StatePublished - 15 May 2019

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