Literature DB >> 28274574

A Risk Model for Prediction of 1-Year Mortality in Patients Undergoing MitraClip Implantation.

Sergio Buccheri1, Davide Capodanno2, Marco Barbanti1, Antonio Popolo Rubbio1, Maria Elena Di Salvo1, Salvatore Scandura1, Sarah Mangiafico1, Giuseppe Ronsivalle1, Marta Chiarandà1, Piera Capranzano1, Carmelo Grasso1, Corrado Tamburino1.   

Abstract

There is a lack of specific tools for risk stratification in patients who undergo MitraClip implantation. We aimed at combining preprocedural variables with prognostic impact into a specific risk model for the prediction of 1-year mortality in patients undergoing MitraClip implantation. A total of 311 consecutive patients who underwent MitraClip implantation were included. A lasso-penalized Cox-proportional hazard regression model was used to identify independent predictors of 1-year all-cause mortality. A nomogram (GRASP [Getting Reduction of mitrAl inSufficiency by Percutaneous clip implantation] nomogram) was obtained from the Cox model. Validation was performed using internal bootstrap resampling. Forty-two deaths occurred at 1-year follow-up. The Kaplan-Meier estimate of 1-year survival was 0.845 (95% confidence interval, 0.802 to 0.895). Four independent predictors of mortality (mean arterial blood pressure, hemoglobin natural log-transformed pro-brain natriuretic peptide levels, New York Heart Association class IV at presentation) were identified. At internal bootstrap resampling validation, the GRASP nomogram had good discrimination (area under receiver operating characteristic curve of 0.78, Somers' Dxy statistic of 0.53) and calibration (le Cessie-van Houwelingen-Copas-Hosmer p value of 0.780). Conversely, the discriminative ability of the EuroSCORE II (the European System for Cardiac Operative Risk Evaluation II) and the STS-PROM (the Society of Thoracic Surgeons Predicted Risk of Mortality score) was fairly modest with area under the curve values of 0.61 and 0.55, respectively. A treatment-specific risk model in patients who undergo MitraClip implantation may be useful for the stratification of mortality at 1 year. Further studies are needed to provide external validation and support the generalizability of the GRASP nomogram.
Copyright © 2017 Elsevier Inc. All rights reserved.

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Year:  2017        PMID: 28274574     DOI: 10.1016/j.amjcard.2017.01.024

Source DB:  PubMed          Journal:  Am J Cardiol        ISSN: 0002-9149            Impact factor:   2.778


  6 in total

1.  The PASCAL transcatheter mitral valve repair system for the treatment of mitral regurgitation: another piece to the puzzle of edge-to-edge technique.

Authors:  Carmelo Grasso; Antonio Popolo Rubbio
Journal:  J Thorac Dis       Date:  2017-12       Impact factor: 2.895

2.  The Value of Claims-Based Nontraditional Risk Factors in Predicting Long-term Mortality After MitraClip Procedure.

Authors:  Harun Kundi; Jeffrey J Popma; Linda R Valsdottir; Changyu Shen; Kamil F Faridi; Duane S Pinto; Robert W Yeh
Journal:  Can J Cardiol       Date:  2018-10-13       Impact factor: 5.223

3.  Periprocedural changes in natriuretic peptide levels and clinical outcome after transcatheter mitral valve repair.

Authors:  Tetsu Tanaka; Refik Kavsur; Maximilian Spieker; Christos Iliadis; Clemens Metze; Patrick Horn; Atsushi Sugiura; Malte Kelm; Stephan Baldus; Georg Nickenig; Ralf Westenfeld; Roman Pfister; Marc Ulrich Becher
Journal:  ESC Heart Fail       Date:  2021-09-14

4.  Comparison of standard and penalized logistic regression in risk model development.

Authors:  Yan Yan; Zhizhou Yang; Tara R Semenkovich; Benjamin D Kozower; Bryan F Meyers; Ruben G Nava; Daniel Kreisel; Varun Puri
Journal:  JTCVS Open       Date:  2022-01-22

5.  "Get with the Guidelines Heart Failure Risk Score" for mortality prediction in patients undergoing MitraClip.

Authors:  Christos Iliadis; Maximilian Spieker; Refik Kavsur; Clemens Metze; Martin Hellmich; Patrick Horn; Ralf Westenfeld; Vedat Tiyerili; Marc Ulrich Becher; Malte Kelm; Georg Nickenig; Stephan Baldus; Roman Pfister
Journal:  Clin Res Cardiol       Date:  2021-01-31       Impact factor: 5.460

Review 6.  Implementing Machine Learning in Interventional Cardiology: The Benefits Are Worth the Trouble.

Authors:  Walid Ben Ali; Ahmad Pesaranghader; Robert Avram; Pavel Overtchouk; Nils Perrin; Stéphane Laffite; Raymond Cartier; Reda Ibrahim; Thomas Modine; Julie G Hussin
Journal:  Front Cardiovasc Med       Date:  2021-12-08
  6 in total

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