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 inInternational journal of cardiology Vol. 317; pp. 25 - 32
Main Authors Al-Farra, Hatem, Abu-Hanna, Ameen, de Mol, Bas A.J.M., ter Burg, W.J., Houterman, Saskia, Henriques, José P.S., Ravelli, Anita C.J., Vis, M.M., Vos, J., Ten Berg, J., Tonino, W.A.L., Schotborgh, C.E., Roolvink, V., Porta, F., Stoel, M., Kats, S., Amoroso, G., van der Werf, H.W., Stella, P.R., de Jaegere, P.
Format Journal Article
LanguageEnglish
Published Netherlands Elsevier B.V 15.10.2020
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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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ISSN:0167-5273
1874-1754
DOI:10.1016/j.ijcard.2020.05.039