The Journal of Thoracic and Cardiovascular Surgery
Volume 133, Issue 4 , Pages 865-875 , April 2007

Case complexity scores in congenital heart surgery: A comparative study of the Aristotle Basic Complexity score and the Risk Adjustment in Congenital Heart Surgery (RACHS-1) system

Read at the Eighty-fifth Annual Meeting of The American Association for Thoracic Surgery, San Francisco, Calif, April 10-13, 2005.

  • Osman O. Al-Radi, MD, MSc

      Affiliations

    • Hospital for Sick Children, University of Toronto, Toronto, Canada
  • ,
  • Frank E. Harrell Jr, PhD

      Affiliations

    • Department of Biostatistics, Vanderbilt University School of Medicine, Nashville, Tenn.
  • ,
  • Christopher A. Caldarone, MD

      Affiliations

    • Hospital for Sick Children, University of Toronto, Toronto, Canada
  • ,
  • Brian W. McCrindle, MD, MPH

      Affiliations

    • Hospital for Sick Children, University of Toronto, Toronto, Canada
  • ,
  • Jeffrey P. Jacobs, MD

      Affiliations

    • The Congenital Heart Institute of Florida, University of South Florida, Saint Petersburg, Fla.
  • ,
  • M. Gail Williams

      Affiliations

    • Hospital for Sick Children, University of Toronto, Toronto, Canada
  • ,
  • Glen S. Van Arsdell, MD

      Affiliations

    • Hospital for Sick Children, University of Toronto, Toronto, Canada
  • ,
  • William G. Williams, MD

      Affiliations

    • Hospital for Sick Children, University of Toronto, Toronto, Canada
    • Corresponding Author InformationAddress for reprints: William G. Williams, MD, 555 University Avenue, Room 1525, Toronto, ON, M5G 1X8, Canada.

Received 20 April 2005 ,Revised 26 April 2006 ,Accepted 17 May 2006.

References 

  1. Jenkins KJ, Gauvreau K, Newburger JW, Spray TL, Moller JH, Iezzoni LI. Consensus-based method for risk adjustment for surgery for congenital heart disease. J Thorac Cardiovasc Surg. 2002;123:110–118
  2. Lacour-Gayet F, Clarke D, Jacobs J, Comas J, Daebritz S, Daenen W, et al. The Aristotle score: a complexity-adjusted method to evaluate surgical results. Eur J Cardiothorac Surg. 2004;25:911–924
  3. Lacour-Gayet F. Risk stratification theme for congenital heart surgery. Semin Thorac Cardiovasc Surg Pediatr Card Surg Annu. 2002;5:148–152
  4. Lacour-Gayet F, Clarke D, Jacobs J, Gaynor W, Hamilton L, Jacobs M, et al. The Aristotle score for congenital heart surgery. Semin Thorac Cardiovasc Surg Pediatr Card Surg Annu. 2004;7:185–191
  5. Lacour-Gayet F, Clarke DR. The Aristotle method: a new concept to evaluate quality of care based on complexity. Curr Opin Pediatr. 2005;17:412–417
  6. Jenkins KJ, Gauvreau K. Center-specific differences in mortality: preliminary analyses using the Risk Adjustment in Congenital Heart Surgery (RACHS-1) method. J Thorac Cardiovasc Surg. 2002;124:97–104
  7. Jenkins KJ. Risk adjustment for congenital heart surgery: the RACHS-1 method. Semin Thorac Cardiovasc Surg Pediatr Card Surg Annu. 2004;7:180–184
  8. Larsen SH, Pedersen J, Jacobsen J, Johnsen SP, Hansen OK, Hjortdal V. The RACHS-1 risk categories reflect mortality and length of stay in a Danish population of children operated for congenital heart disease. Eur J Cardiothorac Surg. 2005;28:877–881
  9. Boethig D, Jenkins KJ, Hecker H, Thies WR, Breymann T. The RACHS-1 risk categories reflect mortality and length of hospital stay in a large German pediatric cardiac surgery population. Eur J Cardiothorac Surg. 2004;26:12–17
  10. Iezzoni LI. Risk adjustment for measuring health care outcomes. 3rd ed.. Chicago: Health Administration Press; 2003;
  11. Harrell FE. Regression modeling strategies with applications to linear models, logistic regression, and survival analysis. New York: Springer; 2001;
  12. Harrell FE, Lee KL, Pollock BG. Regression models in clinical studies: determining relationships between predictors and response. J Natl Cancer Inst. 1988;80:1198–1202
  13. White H. Maximum likelihood estimation of misspecified models. Econometrica. 1982;50:1–25
  14. Hmisc: A Package of Miscellaneous S Functions. 2006.
  15. Proc Fifth Berkeley Symposium Math Stat. 1967.
  16. Feng Z, McLerran D, Grizzle J. A comparison of statistical methods for clustered data analysis with Gaussian error. Stat Med. 1996;15:1793–1806
  17. Califf RM, Phillips HR, Hindman MC, Mark DB, Lee KL, Behar VS, et al. Prognostic value of a coronary artery jeopardy score. J Am Coll Cardiol. 1985;5:1055–1063
  18. Aalen OO. Nonparametric estimation of partial transition probabilities in multiple decrement models. Annals of Statistics. 2006;61:534–545
  19. Gray RJ. A class of K-sample tests for comparing the cumulative incidence of a competing risk. Annals of Statistics. 1988;16:1141–1154
  20. Blackstone EH. Let the data speak for themselves?. Semin Thorac Cardiovasc Surg Pediatr Card Surg Annu. 2004;7:192–198
  21. Monro JL. The next challenge-adapting to change. Eur J Cardiothorac Surg. 2004;26:1063–1072

PII: S0022-5223(06)02281-1

doi: 10.1016/j.jtcvs.2006.05.071

The Journal of Thoracic and Cardiovascular Surgery
Volume 133, Issue 4 , Pages 865-875 , April 2007