Importance of risk stratification models in cardiac surgeryThe opinions expressed in this article are not necessarily those of the Editors of the European Heart Journal or of the European Society of Cardiology.

Abstract

This editorial refers to ‘Comparison of 19 pre-operative risk stratification models in open-heart surgery’† by J. Nilsson et al., on page 867 In a context of growing control of health-care expenditures, it is important to assess cardiac surgical results as precisely as possible. However, as patient population may differ significantly between institutions and geographic areas, comparison of absolute numbers, such as mortality rates, is inappropriate for cost-benefit analysis and comparison of results between institutions.1,2 Therefore, various risk stratification models have been developed to correct for differences between populations and to allow comparison of actual outcome with predicted outcome.3 Those models are increasingly used to investigate patient outcomes in relation to pre-operative patient and disease characteristics. Such models estimate coefficients for each risk factor of mortality, which are translated to risk scores. Then, the scores assigned to each risk factor are added to calculate the overall risk score of mortality for a patient and to construct clinical risk groups. Reference to these groups can be made to adjust clinical decisions to individual patients, to compare surgical performances, and for patient counselling. Health authorities, hospitals, medical practitioners, and patients are increasingly placing importance in those models, aimed at obtaining objective risk-adjusted prediction of mortality after cardiac surgery. Indeed, risk stratification models can detect and quantify differences and changes in the risk profiles of patients presented for cardiac surgery. Risk prediction allows a more objective assessment of the surgical indication in individual patients by facilitating accurate balancing of potential risks and benefits.4 Usually, such models do predict outcome more accurately in the original setting than when used for other patients populations. Indeed, there are significant differences with regard to the initial patient population on which the score design … *Corresponding author. E-mail address : philippe.kolh{at}chu.ulg.ac.be