A Prognostic Model for the Thirty-day Mortality Risk after Adult Heart Transplantation

Abstract

Objective: To develop a prognostic model for the thirty-day mortality risk after adult heart transplantation. Methods: In this report we developed a prediction model for the 30-day mortality risk after adult heart transplantation. Logistic regression analysis was used to develop the model in 1,262 adult patients undergoing primary heart transplantation. We evaluated the accuracy of the prediction model; the agreement between the predicted probability and the observed mortality (calibration); and the ability of the model to correctly discriminate between the discordant survival pairs (discrimination). The internal validity of the prediction model was evaluated using the bootstrapping procedures. Results: Recipients age and sex, pre-transplant diagnosis, transplant status, waiting time, cardiopulmonary bypass time, donors age and sex, donor-recipient mismatch for BMI and blood type were independent predictors for 30-day mortality risk after adult heart transplantation. The model showed a good calibration and reasonable discrimination (the corrected area under the receiver operating characteristic curve was 0.71). The internal validity of the prediction model was acceptable. For practical use, we converted the prediction model to score chart. Conclusion: The accuracy and the validity of the prediction model were acceptable. This easy-to-use instrument for predicting the 30-day mortality risk after adult heart transplantation would benefit decision-making by classifying recipients according to their mortality risk and allowing optimal allocation of a donor to a recipient for heart transplantation.

Keywords

• heart transplant
• mortality
• risk
• scoring system
• prediction models