Inadequacy of existing clinical prediction models for predicting mortality after transcatheter aortic valve implantation

Abstract

BackgroundThe performance of emerging transcatheter aortic valve implantation (TAVI) clinical prediction models (CPMs) in national TAVI cohorts distinct from those where they have been derived is unknown. This study aimed to investigate the performance of the German Aortic Valve, FRANCE-2, OBSERVANT and American College of Cardiology (ACC) TAVI CPMs compared with the performance of historic cardiac CPMs such as the EuroSCORE and STS-PROM, in a large national TAVI registry.MethodsThe calibration and discrimination of each CPM were analyzed in 6676 patients from the UK TAVI registry, as a whole cohort and across several subgroups. Strata included gender, diabetes status, access route, and valve type. Furthermore, the amount of agreement in risk classification between each of the considered CPMs was analyzed at an individual patient level.ResultsThe observed 30-day mortality rate was 5.4%. In the whole cohort, the majority of CPMs over-estimated the risk of 30-day mortality, although the mean ACC score (5.2%) approximately matched the observed mortality rate. The areas under ROC curve were between 0.57 for OBSERVANT and 0.64 for ACC. Risk classification agreement was low across all models, with Fleiss's kappa values between 0.17 and 0.50.ConclusionsAlthough the FRANCE-2 and ACC models outperformed all other CPMs, the performance of current TAVI-CPMs was low when applied to an independent cohort of TAVI patients. Hence, TAVI specific CPMs need to be derived outside populations previously used for model derivation, either by adapting existing CPMs or developing new risk scores in large national registries.

UK TAVI registry

“…Their performance is recognised to be limited, and this was also confirmed when these models are applied to the UK dataset 9. The addition of frailty measures, however, does improve risk prediction 10.…”

Association of comorbid burden with clinical outcomes after transcatheter aortic valve implantation

“…The poor performance of the STS score and the LES/ESII are due to the fact that they were derived for predicting surgical populations with different clinical characteristics from those of TAVI cohorts 29. Thus, precluding accurate model calibrations to perform in TAVI patients that were excluded from SAVR by virtue of certain comorbidities, such as porcelain aorta, chest radiation/hostile chest, cancer, immunodeficiency, liver disease/cirrhosis and frailty that, among others, are not computed into the STS score and LES/ESII risk models.…”

Nutrition and mobility predict all-cause mortality in patients 12 months after transcatheter aortic valve implantation

“…Several clinical prediction models for TAVI have been suggested [ 6 – 8 , 20 ], so that the “eyeball test” does not need to be used. Nevertheless, despite including multiple parameters, the predictive power is still rather inadequate [ 21 ]. Thus, there is an urgent need for the characterization of potentially threatened patients, including readmission [ 22 ] and all-cause mortality [ 23 ].…”