Literature DB >> 29127116

Predicting Mortality After Transcatheter Aortic Valve Replacement: External Validation of the Transcatheter Valve Therapy Registry Model.

Thomas Pilgrim1, Anna Franzone2, Stefan Stortecky2, Fabian Nietlispach2, Alan G Haynes2, David Tueller2, Stefan Toggweiler2, Oliver Muller2, Enrico Ferrari2, Stéphane Noble2, Francesco Maisano2, Raban Jeger2, Marco Roffi2, Jürg Grünenfelder2, Christoph Huber2, Peter Wenaweser2, Stephan Windecker2.   

Abstract

BACKGROUND: The Transcatheter Valve Therapy (TVT) registry model was recently developed to predict the risk of in-hospital mortality in patients undergoing transcatheter aortic valve replacement. We sought to externally validate the model in an independent data set of consecutively enrolled patients in the Swiss Transcatheter Aortic Valve Implantation registry. METHODS AND
RESULTS: The original prediction model was retrospectively applied to 3491 consecutive patients undergoing transcatheter aortic valve replacement in Switzerland between February 2011 and February 2016. We examined model performance in terms of discrimination (Harrel C index) and calibration (Hosmer-Lemeshow goodness-of-fit test) for prediction of in-hospital and 30-day mortality and compared its predictive accuracy with the Society of Thoracic Surgeons Predicted Risk of Mortality score. Rates of in-hospital and 30-day mortality in the external validation cohort were 2.9% and 3.8%, respectively. The TVT registry model was found to have moderate discrimination (C index, 0.66; 95% confidence interval, 0.60-0.72 and C index, 0.67; 95% confidence interval, 0.62-0.72 for in-hospital and 30-day mortality, respectively) and good calibration. Compared with the Society of Thoracic Surgeons Predicted Risk of Mortality score, the TVT registry model demonstrated improved calibration for in-hospital (slope, 0.83; P=0.23 versus slope, 0.24; P<0.001, respectively) and 30-day (slope, 1.11; P=0.40 versus slope, 0.41; P<0.001, respectively) mortality.
CONCLUSIONS: In a large, multicenter, non-US cohort of patients with transcatheter aortic valve replacement, the validation of the TVT registry model demonstrated moderate discrimination and good calibration for the prediction of in-hospital and 30-day mortality. As a result, the TVT registry model should be considered an alternative to the Society of Thoracic Surgeons Predicted Risk of Mortality score for decision making and assessment of early outcome in patients eligible for transcatheter aortic valve replacement.
© 2017 American Heart Association, Inc.

Entities:  

Keywords:  decision making; humans; mortality; risk; transcatheter aortic valve replacement

Mesh:

Year:  2017        PMID: 29127116     DOI: 10.1161/CIRCINTERVENTIONS.117.005481

Source DB:  PubMed          Journal:  Circ Cardiovasc Interv        ISSN: 1941-7640            Impact factor:   6.546


  4 in total

Review 1.  Pre-procedural risk models for patients undergoing transcatheter aortic valve implantation.

Authors:  Glen P Martin; Matthew Sperrin; Mamas A Mamas
Journal:  J Thorac Dis       Date:  2018-11       Impact factor: 2.895

2.  Comparative utility of frailty to a general prognostic score in identifying patients at risk for poor outcomes after aortic valve replacement.

Authors:  Sandra Shi; Natalia Festa; Jonathan Afilalo; Jeffrey J Popma; Kamal R Khabbaz; Roger J Laham; Kimberly Guibone; Dae Hyun Kim
Journal:  BMC Geriatr       Date:  2020-02-03       Impact factor: 3.921

3.  Practical Application of Patient-Reported Health Status Measures for Transcatheter Valve Therapies: Insights From the Society of Thoracic Surgeons/American College of Cardiology Transcatheter Valve Therapies Registry.

Authors:  Vittal Hejjaji; David J Cohen; John D Carroll; Zhuokai Li; Pratik Manandhar; Sreekanth Vemulapalli; Adam J Nelson; Ali O Malik; Michael J Mack; John A Spertus; Suzanne V Arnold
Journal:  Circ Cardiovasc Qual Outcomes       Date:  2021-02-18

4.  Temporal Trend, Prevalence, Predictors, and Outcomes of Pericardial Diseases in Patients Undergoing Transcatheter Aortic Valve Repair.

Authors:  Kashyap Shah; Matthew Krinock; Harshith Thyagaturu; Rezwan Munshi; Ayushi Pandya; Sarah Falta; John Hippen; Michael Durkin
Journal:  Cureus       Date:  2021-07-01
  4 in total

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