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Predictive Factors of Early Mortality After Transcatheter Aortic Valve Implantation: Individual Risk Assessment Using a Simple Score
Study Questions:
What are the predictors of 30-day mortality in patients undergoing transcatheter aortic valve implantation (TAVI)?
Methods:
The authors used data from the French Aortic National CoreValve and Edwards (FRANCE 2) registry to analyse the predictive factors of early mortality after TAVI. A population of 3,833 consecutive patients was randomly split into two cohorts comprising 2,552 and 1,281 patients, used respectively to develop and validate a scoring system predicting 30-day or in-hospital mortality.
Results:
TAVI was performed using the Edwards Sapien prosthesis in 2,551 (66.8%) patients and the Medtronic CoreValve in 1,270 (33.2%). The majority of patients were treated with a transfemoral approach (73.4%), with the rest treated with transapical (17.8%) or subclavian (5.7%) approaches. Early mortality was 10.0% (382 patients). Predictors of early mortality were age ≥90 years, body mass index <30 kg/m2, New York Heart Association class IV, pulmonary hypertension, critical hemodynamic state, ≥2 pulmonary edemas during the prior year, respiratory insufficiency, dialysis, and transapical or other (transaortic and transcarotid) approaches. A 21-point predictive score was derived using these factors. The c-index was 0.67 for the score in the development cohort and 0.59 in the validation cohort. There was a good concordance between predicted and observed 30-day mortality rates in the development and validation cohorts.
Conclusions:
The authors concluded that early mortality after TAVI is related to age, symptom severity, comorbidities, and use of an apical approach.
Perspective:
TAVI (or TAVR) is one of the few procedures that prolongs life and improves quality of life, even in extremely elderly patients. However, some patients will not benefit from the procedure, and in others, the risk of early mortality is exceedingly high. The authors attempted to develop a prediction model to determine early mortality in this cohort and identify the factors that were associated with a poor outcome in this registry. The poor discrimination of the model makes it unsuitable for use in clinical practice, and better models need to be developed to identify patients who either will not benefit from TAVI or will be at an extremely high risk of death.
Keywords: Renal Dialysis, Pulmonary Edema, Hospital Mortality, Body Mass Index, Quality of Life, Hypertension, Pulmonary, Comorbidity, Respiratory Insufficiency, Risk Assessment, Hemodynamics
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