The Application of Comorbidity Indices to Predict Early Postoperative Outcomes After Laparoscopic Roux-en-Y Gastric Bypass: A Nationwide Comparative Analysis of Over 70,000 Cases
- 401 Downloads
Patients undergoing laparoscopic Roux-en-Y gastric bypass (LRYGB) often have substantial comorbidities, which must be taken into account to appropriately assess expected postoperative outcomes. The Charlson/Deyo and Elixhauser indices are widely used comorbidity measures, both of which also have revised algorithms based on enhanced ICD-9-CM coding. It is currently unclear which of the existing comorbidity measures best predicts early postoperative outcomes following LRYGB.
Using the Nationwide Inpatient Sample, patients 18 years or older undergoing LRYGB for obesity between 2001 and 2008 were identified. Comorbidities were assessed according to the original and enhanced Charlson/Deyo and Elixhauser indices. Using multivariate logistic regression, the following early postoperative outcomes were assessed: overall postoperative complications, length of hospital stay, and conversion to open surgery. Model performance for the four comorbidity indices was assessed and compared using C-statistics and the Akaike’s information criterion (AIC).
A total of 70,287 patients were included. Mean age was 43.1 years (SD, 10.8), 81.6 % were female and 60.3 % were White. Both the original and enhanced Elixhauser indices modestly outperformed the Charlson/Deyo in predicting the surgical outcomes. All four models had similar C-statistics, but the original Elixhauser index was associated with the smallest AIC for all of the surgical outcomes.
The original Elixhauser index is the best predictor of early postoperative outcomes in our cohort of patients undergoing LRYGB. However, differences between the Charlson/Deyo and Elixhauser indices are modest, and each of these indices provides clinically relevant insight for predicting early postoperative outcomes in this high-risk patient population.
KeywordsLaparoscopic Roux-en-Y gastric bypass Comorbidity Charlson/Deyo index Elixhauser index Postoperative outcomes
Conflicts of Interest
All contributing authors, including Jin Hee Shin, Mathias Worni, Anthony W. Castleberry, Ricardo Pietrobon, Philip A. Omotosho, Mina Silberberg, and Truls Østbye, declare that they have no conflicts of interest in relation to this manuscript.
- 26.Agency for Healthcare Research and Quality. Healthcare Cost and Utilization Project. Overview of the Nationwide Inpatients Sample(NIS). 2009. http://www.hcup-us.ahrq.gov/nisoverview.jsp. Accessed 22 Feb 2010.
- 27.Healthcare Cost and Utilization Project. Overview of the Nationwide Inpatients Sample (NIS). http://www.hcup-us.ahrq.gov/nisoverview.jsp. Accessed February 2010.
- 28.Whalen D, Houchens R, Elixhauser A. 2004 HCUP Nationwide Inpatient Sample (NIS) comparison report. HCUP Method Series Report No. 2007-03. Healthcare Cost and Utilization Project (HCUP) web site. 2006. http://www.hcup-us.ahrg.gov/reports/methods/methods.jsp. Accessed February 2010.
- 38.Burnham KP, Anderson DR. Model selection and multimodel inference: a practical information-theoretic approach. New York: Springer; 2002.Google Scholar