• C S Almond, K Gauvreau, C E Canter, S K Rajagopal, G E Piercey, and T P Singh.
• Department of Cardiology, Children's Hospital, Boston, MA, USA. Christopher.Almond@cardio.chboston.org
• Am. J. Transplant. 2012 May 1; 12 (5): 1240-8.

AbstractWe sought to develop and validate a quantitative risk-prediction model for predicting the risk of posttransplant in-hospital mortality in pediatric heart transplantation (HT). Children <18 years of age who underwent primary HT in the United States during 1999-2008 (n = 2707) were identified using Organ Procurement and Transplant Network data. A risk-prediction model was developed using two-thirds of the cohort (random sample), internally validated in the remaining one-third, and independently validated in a cohort of 338 children transplanted during 2009-2010. The best predictive model had four categorical variables: hemodynamic support (ECMO, ventilator support, VAD support vs. medical therapy), cardiac diagnosis (repaired congenital heart disease [CHD], unrepaired CHD vs. cardiomyopathy), renal dysfunction (severe, mild-moderate vs. normal) and total bilirubin (≥ 2.0, 0.6 to <2.0 vs. <0.6 mg/dL). The C-statistic (0.78) and the Hosmer-Lemeshow goodness-of-fit (p = 0.89) in the model-development cohort were replicated in the internal validation and independent validation cohorts (C-statistic 0.75, 0.81 and the Hosmer-Lemeshow goodness-of-fit p = 0.49, 0.53, respectively) suggesting acceptable prediction for posttransplant in-hospital mortality. We conclude that this risk-prediction model using four factors at the time of transplant has good prediction characteristics for posttransplant in-hospital mortality in children and may be useful to guide decision-making around patient listing for transplant and timing of mechanical support.© Copyright 2012 The American Society of Transplantation and the American Society of Transplant Surgeons.

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