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. 2020 Apr;20(4):1137-1151.
doi: 10.1111/ajt.15708. Epub 2019 Dec 16.

Risk prediction models for survival after heart transplantation: A systematic review

Natasha Aleksova  1 , Ana C Alba  1 , Victoria M Molinero  1 , Katherine Connolly  2 , Ani Orchanian-Cheff  3 , Mitesh Badiwala  1 , Heather J Ross  1 , Juan G Duero Posada  1
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Free article

Risk prediction models for survival after heart transplantation: A systematic review

Natasha Aleksova et al. Am J Transplant. 2020 Apr.
Free article

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.

Keywords: clinical research/practice; heart transplantation/cardiology; organ procurement and allocation; patient survival; risk assessment/risk stratification.

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References

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