Title

Predicting major complications after laparoscopic cholecystectomy: a simple risk score

UMMS Affiliation

Department of Surgery

Date

11-13-2009

Document Type

Article

Medical Subject Headings

Adult; Aged; Algorithms; Cholecystectomy, Laparoscopic; Cholelithiasis; Comorbidity; Female; Humans; Logistic Models; Male; Middle Aged; Postoperative Complications; ROC Curve; Risk Assessment

Disciplines

Surgery

Abstract

INTRODUCTION: Reported morbidity varies widely for laparoscopic cholecystectomy (LC). A reliable method to determine complication risk may be useful to optimize care. We developed an integer-based risk score to determine the likelihood of major complications following LC.

METHODS: Using the Nationwide Inpatient Sample 1998-2006, patient discharges for LC were identified. Using previously validated methods, major complications were assessed. Preoperative covariates including patient demographics, disease characteristics, and hospital factors were used in logistic regression/bootstrap analyses to generate an integer score predicting postoperative complication rates. A randomly selected 80% was used to create the risk score, with validation in the remaining 20%.

RESULTS: Patient discharges (561,923) were identified with an overall complication rate of 6.5%. Predictive characteristics included: age, sex, Charlson comorbidity score, biliary tract inflammation, hospital teaching status, and admission type. Integer values were assigned and used to calculate an additive score. Three groups stratifying risk were assembled, with a fourfold gradient for complications ranging from 3.2% to 13.5%. The score discriminated well in both derivation and validation sets (c-statistic of 0.7).

CONCLUSION: An integer-based risk score can be used to predict complications following LC and may assist in preoperative risk stratification and patient counseling.

Rights and Permissions

Citation: J Gastrointest Surg. 2009 Nov;13(11):1929-36. Epub 2009 Aug 12. Link to article on publisher's site

Related Resources

Link to Article in PubMed

PubMed ID

19672665