Dataset Information

Predicting gangrenous cholecystitis.

ABSTRACT:

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) >13,000/mm(3), gallbladder wall thickening (GBWT) ? 4 mm, 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.

SUBMITTER: Wu B

PROVIDER: S-EPMC4159452 | biostudies-literature | 2014 Sep

REPOSITORIES: biostudies-literature

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Publications

Predicting gangrenous cholecystitis.

Wu Bin B Buddensick Thomas J TJ Ferdosi Hamid H Narducci Dusty Marie DM Sautter Amanda A Setiawan Lisa L Shaukat Haroon H Siddique Mustafa M Sulkowski Gisela N GN Kamangar Farin F Kowdley Gopal C GC Cunningham Steven C SC

HPB : the official journal of the International Hepato Pancreato Biliary Association 20140317 9

<h4>Background</h4>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.<h4>Methods</h4>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.<h4>Results ...[more]

PMID: 24635779

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Dataset Information

Predicting gangrenous cholecystitis.

Background

Methods

Results

Conclusion

Publications

Predicting gangrenous cholecystitis.

Similar Datasets

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