Risk Prediction of Transcatheter Aortic Valve Implantation by the Incorporation of Albumin to Surgical Risk Scores

Yoni Grossman 1,2 Israel Barbash 1,2 Paul Fefer 1,2 Ilan Goldenberg 1,2 Anat Bercovitch 1,2 Aharon Erez 1,2 Ehud Regev 1,2 Noam Fink 1,2 Ashraf Hamdan 1,2 Ilan Hay 1,2 Dan Spigelstein 1,2 Ehud Raanani 1,2 Victor Guetta 1,2 Amit Segev 1,2
1Leviev Heart Center, Sheba Medical Center, Tel Hashomer, Israel
2Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel

Objectives: Surgical risk scores (such as Euroscore, STS) are used for risk assessment of candidates for Transcatheter aortic valve implantation (TAVI). Currents guidelines recommend against the sole reliance on such risk scores. Frailty and albumin as a strong marker of frailty were found to have a prognostic value in TAVI patients. This study aims to compare the prognostic value of commonly used risk scores when pre-procedural albumin level is incorporated.

Methods: The study is based on a registry of 426 patients who underwent TAVI between 2008-2014. Mean age was 83.7, 46% were men. Uni-variable and multi-variable regression models were used in order to assess the prognostic value of the EUROSCORE I, EUROSCORE II and STS risk scores alone and when albumin pre-procedural value was incorporated. Primary end point was 1 year mortality.

Results: The Average STS, EUROSCORE1 and EUROSCORE2 scores were 5.59 ± 3.8, 19 ± 15.4 and 5.31 ± 5.83, respectively. The fit of the models of all risk scores was similar, with a C-statistic of 0.7 for STS and EUROSCORE 1, and 0.72 for EUROSCORE 2. All were statistically significant. The incorporation of STS score with pre-procedural albumin had a better ability to predict 1 year mortality than STS alone (C-statistic of 0.77 and 0.7, respectively). The best predictive ability was seen with the incorporation of EUROSCORE2 and albumin, with a C-statistic of 0.79.

Conclusions: In the TAVI pre-procedural risk evaluation, the incorporation of established surgical risk scores with albumin (as a frailty marker) increases the precision of the risk assessment.









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