Risk Prediction in Clinical Practice: A Practical Guide for Cardiothoracic Surgeons.

The prediction of a patient's risk for disease, death, or morbidity has become an ever more essential part of modern clinical care. Guidelines for clinical management are often dependent on risk estimates. As such, it is imperative that surgeons understand how to properly use and evaluate risk estimates and the models that underlie them. Making matters more complex, an expanding number of risk prediction models are now available to cardiothoracic surgeons.1-4 Table 1 displays a few high-profile examples along with some key measures of model performance, which we describe in the following sections. This review is intended to be a practical guide for clinicians without any specialized training in statistics. The examples and literature herein focus on models a cardiothoracic surgeon is most likely to encounter and the statistical procedures used to validate them. Our purpose is to provide guidance to cardiothoracic surgeons on the evaluation of risk models and their application in clinical decision making. The use of risk models for quality assessment, public reporting, value-based purchasing, and cost effectiveness are well covered elsewhere and beyond the scope of this manuscript.