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Updated: Jan 3, 2026
A Pre-Clinical Porcine Model of Orthotopic Heart Transplantation
Published on: April 27, 2019
Risk prediction models for survival after heart transplantation: A systematic review
Natasha Aleksova1, Ana C Alba1, Victoria M Molinero1
1Peter Munk Cardiac Centre, Toronto General Hospital-University Health Network, Toronto, Canada.
Insights
Predicting survival after heart transplantation (HT) is crucial. Current risk scores show limited accuracy, with insufficient data to recommend one over others for post-HT outcomes.
Area of Science:
- Cardiology
- Transplantation Medicine
- Biostatistics
Background:
- Heart transplantation (HT) outcomes rely on accurate survival prediction.
- Various risk prediction scores exist to estimate post-transplant mortality.
Purpose of the Study:
- To systematically review the characteristics and predictive performance of existing risk scores for survival after heart transplantation.
- To identify the most validated and accurate scores for clinical use.
Main Methods:
- Systematic literature search of multiple databases (Ovid Medline, Embase, Cochrane) up to December 2018.
- Inclusion of studies deriving and/or validating risk scores for HT mortality.
- Analysis of model characteristics, external validation, and performance metrics (C-statistic).
Main Results:
- 21 studies identified 16 distinct risk prediction scores.
- Only 44% of scores underwent external validation; 50% assessed model performance.
- Overall model discrimination was poor to moderate (C-statistic 0.54–0.77).
- The IMPACT score showed the best performance for 3-month survival (C-statistic 0.76) but most scores performed poorly.
Conclusions:
- Existing risk prediction scores for heart transplantation demonstrate limited accuracy and variable performance.
- Insufficient evidence supports the routine use of any single score for predicting post-HT outcomes.
- Further research is needed to develop and validate more robust prediction models.
Abstract:
Risk prediction scores have been developed to predict survival following heart transplantation (HT). Our objective was to systematically review the model characteristics and performance for all available scores that predict survival after HT. Ovid Medline and Epub Ahead of Print and In-Process & Other Non-Indexed Citations, Ovid Embase, Cochrane Database of Systematic Reviews, and Cochrane Central Register of Controlled Clinical Trials were searched to December 2018. Eligible articles reported a score to predict mortality following HT. Of the 5392 studies screened, 21 studies were included that derived and/or validated 16 scores. Seven (44%) scores were validated in external cohorts and 8 (50%) assessed model performance. Overall model discrimination ranged from poor to moderate (C-statistic/area under the receiver operating characteristics 0.54-0.77). The IMPACT score was the most widely validated, was well calibrated in two large registries, and was best at discriminating 3-month survival (C-statistic 0.76). Most scores did not perform particularly well in any cohort in which they were assessed. This review shows that there are insufficient data to recommend the use of one model over the others for prediction of post-HT outcomes.
