External validation of existing prediction models of 30-day mortality after Transcatheter Aortic Valve Implantation (TAVI) in the Netherlands Heart Registration
Several mortality prediction models (MPM) are used for predicting early (30-day) mortality following transcatheter aortic valve implantation (TAVI). Little is known about their predictive performance in external TAVI populations. We aim to externally validate established MPMs on a large TAVI dataset...
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Published in | International journal of cardiology Vol. 317; pp. 25 - 32 |
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Main Authors | , , , , , , , , , , , , , , , , , , , |
Format | Journal Article |
Language | English |
Published |
Netherlands
Elsevier B.V
15.10.2020
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Subjects | |
Online Access | Get full text |
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Summary: | Several mortality prediction models (MPM) are used for predicting early (30-day) mortality following transcatheter aortic valve implantation (TAVI). Little is known about their predictive performance in external TAVI populations. We aim to externally validate established MPMs on a large TAVI dataset from the Netherlands Heart Registration (NHR).
We included data from NHR-patients who underwent TAVI during 2013–2017. We calculated the predicted mortalities per MPM. We assessed the predictive performance by discrimination (Area Under Receiver Operating-characteristic Curve, AU-ROC); the Area Under Precision-Recall Curve, AU-PRC; calibration (using calibration-intercept and calibration-slope); Brier Score and Brier Skill Score. We also assessed the predictive performance among subgroups: tertiles of mortality-risk for non-survivors, gender, and access-route.
We included 6177 TAVI-patients with an observed early-mortality rate of 4.5% (n = 280). We applied seven MPMs (STS, EuroSCORE-I, EuroSCORE-II, ACC-TAVI, FRANCE-2, OBSERVANT, and German-AV) on our cohort. The highest AU-ROCs were 0.64 (95%CI 0.61–0.67) for ACC-TAVI and 0.63 (95%CI 0.60–0.67) for FRANCE-2. All MPMs had a very low AU-PRC of ≤0.09. ACC-TAVI had the best calibration-intercept and calibration-slope. Brier Score values ranged between 0.043 and 0.063. Brier Skill Score ranged between −0.47 and 0.004. ACC-TAVI and FRANCE-2 predicted high mortality-risk better than other MPMs. ACC-TAVI outperformed other MPMs in different subgroups.
The ACC-TAVI model has relatively the best predictive performance. However, all models have poor predictive performance. Because of the poor discrimination, miscalibration and limited accuracy of the models there is a need to update the existing models or develop new TAVI-specific models for local populations.
•Existing MPMs have different ability in predicting early-mortality after TAVI.•Existing MPMs had poor predictive performance in external TAVI population.•Using such MPMs outside the original population is questionable.•Developing TAVI-specific MPM (preferably global model) is a need. |
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
ISSN: | 0167-5273 1874-1754 |
DOI: | 10.1016/j.ijcard.2020.05.039 |