Update and, internal and temporal-validation of the FRANCE-2 and ACC-TAVI early-mortality prediction models for Transcatheter Aortic Valve Implantation (TAVI) using data from the Netherlands heart registration (NHR).

Background: The predictive performance of the models FRANCE-2 and ACC-TAVI for early-mortality after Transcatheter Aortic Valve Implantation (TAVI) can decline over time and can be enhanced by updating them on new populations. We aim to update and internally and temporally validate these models using a recent TAVI-cohort from the Netherlands Heart Registration (NHR).

Methods: We used data of TAVI-patients treated in 2013-2017.

External validation of existing prediction models of 30-day mortality after Transcatheter Aortic Valve Implantation (TAVI) in the Netherlands Heart Registration.

Background: 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).

Utility of a next generation framework for assessment of genomic damage: A case study using the industrial chemical benzene.

We recently published a next generation framework for assessing the risk of genomic damage via exposure to chemical substances. The framework entails a systematic approach with the aim to quantify risk levels for substances that induce genomic damage contributing to human adverse health outcomes. Here, we evaluated the utility of the framework for assessing the risk for industrial chemicals, using the case of benzene.