The Official Journal of EuroPCR and the European Association of Percutaneous Coronary Interventions (EAPCI)

Performance of Current Risk Models in Predicting Short-Term Mortality After Transcatheter Aortic Valve Replacement: A Systematic Review and Meta-Analysis

DOI: 10.4244/EIJ-D-19-00636

1. Department of Medicine, Dow University of Health Sciences, Karachi, Pakistan.
2. Department of Medicine, Dow University of Health Sciences, Karachi, Pakistan.
3. Department of Medicine, John H Stroger Jr. Hospital of Cook County, Chicago, USA, United States
4. Department of Medicine, Dow University of Health Sciences, Karachi, Pakistan.
5. Department of Cardiovascular Medicine, Cleveland Clinic, Cleveland, USA.
6. Department of Medicine, West Virginia University, Morgantown, USA.
7. Evidence-based Practice Center, Mayo Clinic, Rochester, USA.
8. Department of Cardiovascular Medicine, Rush University Medical Center, Chicago, USA.
9. Department of Medicine, John H Stroger Jr. Hospital of Cook County, Chicago, USA; Department of Cardiovascular Medicine, Rush University Medical Center, Chicago, USA.
10. Department of Cardiovascular Medicine, Cleveland Clinic, Cleveland, USA.
11. Department of Cardiovascular Medicine, Cleveland Clinic, Cleveland, USA.
12. Department of Cardiovascular Medicine, Brigham and Women’s Hospital Heart & Vascular Center, Boston, USA.
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Aims: To evaluate the performance of risk stratification models (RSMs) in predicting short-term mortality after transcatheter aortic valve replacement (TAVR). 

Methods and results: MEDLINE and Scopus were queried to identify studies which validated RSMs designed to assess 30-day or in-hospital mortality after TAVR. Discrimination and calibration were assessed using C-statistics and observed/expected ratios (OERs), respectively. C-statistics were pooled using a random-effects inverse-variance method, while OERs were pooled using the Peto odds ratio. A good RSM is defined as one with c-statistic >0.7 and OER close to 1.0. Twenty-four studies (n=68,215 patients) testing 11 different RSMs were identified. Discrimination of all RSMs was poor (C-statistic<0.7); however, certain TAVR-specific RSMs such as the in-hospital STS/ACC TVT (C-statistic=0.65) and STT (C-statistic=0.66) predicted individual mortality more reliably than surgical models (C-statistic range=0.59-0.61). A good calibration was demonstrated by the in-hospital STS/ACC TVT (OER=0.99), 30-day STS/ACC TVT (OER=1.08) and STS (OER=1.01) models. Baseline dialysis (OER: 2.64 [1.88, 3.70]; p<0.001) was the strongest predictor of mortality. 

Conclusions: This study demonstrates that the STS/ACC TVT model (in-hospital and 30-day) and the STS model have accurate calibration, making them useful for comparison of center-level risk-adjusted mortality. In contrast, the discriminative ability of currently available models is limited.

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