Predicting gangrenous cholecystitis

Bin Wu, Thomas J. Buddensick, Hamid Ferdosi, Dusty Marie Narducci, Amanda Sautter, Lisa Setiawan, Haroon Shaukat, Mustafa Siddique, Gisela N. Sulkowski, Farin Kamangar, Gopal C. Kowdley, Steven C. Cunningham

Research output: Contribution to journalArticlepeer-review

23 Scopus citations


Background Gangrenous cholecystitis (GC) is often challenging to treat. The objectives of this study were to determine the accuracy of pre-operative diagnosis, to assess the rate of post-cholecystectomy complications and to assess models to predict GC. Methods A retrospective single-institution review identified patients undergoing a cholecystectomy. Logistic regression models were used to examine the association of variables with GC and to build risk-assessment models. Results Of 5812 patients undergoing a cholecystectomy, 2219 had acute, 4837 chronic and 351 GC. Surgeons diagnosed GC pre-operatively in only 9% of cases. Patients with GC had more complications, including bile-duct injury, increased estimated blood loss (EBL) and more frequent open cholecystectomies. In unadjusted analyses, variables significantly associated with GC included: age >45 years, male gender, heart rate (HR) >90, white blood cell count (WBC) >13000/mm3, gallbladder wall thickening (GBWT) ≥ 4mm, pericholecystic fluid (PCCF) and American Society of Anesthesiology (ASA) >2. In adjusted analyses, age, WBC, GBWT and HR, but not gender, PCCF or ASA remained statistically significant. A 5-point scoring system was created: 0 points gave a 2% probability of GC and 5 points a 63% probability. Conclusion Using models can improve a diagnosis of GC pre-operatively. A prediction of GC pre-operatively may allow surgeons to be better prepared for a difficult operation.

Original languageEnglish (US)
Pages (from-to)801-806
Number of pages6
Issue number9
StatePublished - Sep 2014

ASJC Scopus subject areas

  • Hepatology
  • Gastroenterology


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