|
 |
Risk-Prediction for Early In-Hospital Mortality Following Heart Transplantation in the United States
TP Singh, C Almond, MJ Semigran... - Circulation: Heart ..., 2012 - Am Heart Assoc BackgroundRisk factors for early mortality after heart transplant (HT) have not been used for quantitative risk-prediction. We sought to develop and validate a risk-prediction model for post-transplant in-hospital mortality in HT recipients.
Methods and Results—We derived the model in subjects ≥18 years of age who underwent primary HT in the United States from January 2007 to June 2009 (N=4248) and validated it internally using a bootstrapping technique (200 random samples, N=4248). We then assessed the model's performance in patients transplanted from July 2009 to October 2010 (external-validation cohort, N=2346). Post-transplant in-hospital mortality was 4.7 % in the model-derivation cohort. The best-fitting model based on recipient characteristics at transplant had 6 variables: age, diagnosis, type of mechanical support, ventilator support, estimated glomerular filtration rate and total serum bilirubin. Model discrimination for survivors vs. non-survivors was acceptable during derivation and internal validation (C-statistic 0.722 and 0.731, respectively) as was model calibration during derivation (Hosmer Lomeshow [HL] P value 0.47). Model performance was reasonable in the external-validation cohort (predicted mortality 4.9%, actual mortality 4.3%, R2= 0.95, C-statistic 0.68, HL P value = 0.48). Adding the donor-related variables age and ischemic time to the model improved its performance in both model-derivation (C-statistic 0.742, HL P-value 0.70) and external-validation (C-statistic 0.695, HL P-value 0.42) cohorts.
More Details:
Risk-Prediction for Early In-Hospital Mortality Following Heart Transplantation in the United States |
|
|
