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Predicting Long Term Outcome in Patients Treated With Continuous Flow Left Ventricular Assist Device: The Penn—Columbia Risk Score

BACKGROUND: Predicting which patients are unlikely to benefit from continuous flow left ventricular assist device (LVAD) treatment is crucial for the identification of appropriate patients. Previously developed scoring systems are limited to past eras of device or restricted to specific devices. Our...

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Autores principales: Birati, Edo Y., Hanff, Thomas C., Maldonado, Dawn, Grandin, E. Wilson, Kennel, Peter J., Mazurek, Jeremy A., Vorovich, Esther, Seigerman, Matthew, Howard, Jessica L.L., Acker, Michael A., Naka, Yoshifumi, Wald, Joyce, Goldberg, Lee R., Jessup, Mariell, Atluri, Pavan, Margulies, Kenneth B., Schulze, P. Christian, Rame, J. Eduardo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5907534/
https://www.ncbi.nlm.nih.gov/pubmed/29514805
http://dx.doi.org/10.1161/JAHA.117.006408
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author Birati, Edo Y.
Hanff, Thomas C.
Maldonado, Dawn
Grandin, E. Wilson
Kennel, Peter J.
Mazurek, Jeremy A.
Vorovich, Esther
Seigerman, Matthew
Howard, Jessica L.L.
Acker, Michael A.
Naka, Yoshifumi
Wald, Joyce
Goldberg, Lee R.
Jessup, Mariell
Atluri, Pavan
Margulies, Kenneth B.
Schulze, P. Christian
Rame, J. Eduardo
author_facet Birati, Edo Y.
Hanff, Thomas C.
Maldonado, Dawn
Grandin, E. Wilson
Kennel, Peter J.
Mazurek, Jeremy A.
Vorovich, Esther
Seigerman, Matthew
Howard, Jessica L.L.
Acker, Michael A.
Naka, Yoshifumi
Wald, Joyce
Goldberg, Lee R.
Jessup, Mariell
Atluri, Pavan
Margulies, Kenneth B.
Schulze, P. Christian
Rame, J. Eduardo
author_sort Birati, Edo Y.
collection PubMed
description BACKGROUND: Predicting which patients are unlikely to benefit from continuous flow left ventricular assist device (LVAD) treatment is crucial for the identification of appropriate patients. Previously developed scoring systems are limited to past eras of device or restricted to specific devices. Our objective was to create a risk model for patients treated with continuous flow LVAD based on the preimplant variables. METHODS AND RESULTS: We performed a retrospective analysis of all patients implanted with a continuous flow LVAD between 2006 and 2014 at the University of Pennsylvania and included a total of 210 patients (male 78%; mean age, 56±15; mean follow‐up, 465±486 days). From all plausible preoperative covariates, we performed univariate Cox regression analysis for covariates affecting the odds of 1‐year survival following implantation (P<0.2). These variables were included in a multivariable model and dropped if significance rose above P=0.2. From this base model, we performed step‐wise forward and backward selection for other covariates that improved power by minimizing Akaike Information Criteria while maximizing the Harrell Concordance Index. We then used Kaplan–Meier curves, the log‐rank test, and Cox proportional hazard models to assess internal validity of the scoring system and its ability to stratify survival. A final optimized model was identified based on clinical and echocardiographic parameters preceding LVAD implantation. One‐year mortality was significantly higher in patients with higher risk scores (hazard ratio, 1.38; P=0.004). This hazard ratio represents the multiplied risk of death for every increase of 1 point in the risk score. The risk score was validated in a separate patient cohort of 260 patients at Columbia University, which confirmed the prognostic utility of this risk score (P=0.0237). CONCLUSION: We present a novel risk score and its validation for prediction of long‐term survival in patients with current types of continuous flow LVAD support.
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spelling pubmed-59075342018-05-01 Predicting Long Term Outcome in Patients Treated With Continuous Flow Left Ventricular Assist Device: The Penn—Columbia Risk Score Birati, Edo Y. Hanff, Thomas C. Maldonado, Dawn Grandin, E. Wilson Kennel, Peter J. Mazurek, Jeremy A. Vorovich, Esther Seigerman, Matthew Howard, Jessica L.L. Acker, Michael A. Naka, Yoshifumi Wald, Joyce Goldberg, Lee R. Jessup, Mariell Atluri, Pavan Margulies, Kenneth B. Schulze, P. Christian Rame, J. Eduardo J Am Heart Assoc Original Research BACKGROUND: Predicting which patients are unlikely to benefit from continuous flow left ventricular assist device (LVAD) treatment is crucial for the identification of appropriate patients. Previously developed scoring systems are limited to past eras of device or restricted to specific devices. Our objective was to create a risk model for patients treated with continuous flow LVAD based on the preimplant variables. METHODS AND RESULTS: We performed a retrospective analysis of all patients implanted with a continuous flow LVAD between 2006 and 2014 at the University of Pennsylvania and included a total of 210 patients (male 78%; mean age, 56±15; mean follow‐up, 465±486 days). From all plausible preoperative covariates, we performed univariate Cox regression analysis for covariates affecting the odds of 1‐year survival following implantation (P<0.2). These variables were included in a multivariable model and dropped if significance rose above P=0.2. From this base model, we performed step‐wise forward and backward selection for other covariates that improved power by minimizing Akaike Information Criteria while maximizing the Harrell Concordance Index. We then used Kaplan–Meier curves, the log‐rank test, and Cox proportional hazard models to assess internal validity of the scoring system and its ability to stratify survival. A final optimized model was identified based on clinical and echocardiographic parameters preceding LVAD implantation. One‐year mortality was significantly higher in patients with higher risk scores (hazard ratio, 1.38; P=0.004). This hazard ratio represents the multiplied risk of death for every increase of 1 point in the risk score. The risk score was validated in a separate patient cohort of 260 patients at Columbia University, which confirmed the prognostic utility of this risk score (P=0.0237). CONCLUSION: We present a novel risk score and its validation for prediction of long‐term survival in patients with current types of continuous flow LVAD support. John Wiley and Sons Inc. 2018-03-07 /pmc/articles/PMC5907534/ /pubmed/29514805 http://dx.doi.org/10.1161/JAHA.117.006408 Text en © 2018 The Authors. Published on behalf of the American Heart Association, Inc., by Wiley. This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.
spellingShingle Original Research
Birati, Edo Y.
Hanff, Thomas C.
Maldonado, Dawn
Grandin, E. Wilson
Kennel, Peter J.
Mazurek, Jeremy A.
Vorovich, Esther
Seigerman, Matthew
Howard, Jessica L.L.
Acker, Michael A.
Naka, Yoshifumi
Wald, Joyce
Goldberg, Lee R.
Jessup, Mariell
Atluri, Pavan
Margulies, Kenneth B.
Schulze, P. Christian
Rame, J. Eduardo
Predicting Long Term Outcome in Patients Treated With Continuous Flow Left Ventricular Assist Device: The Penn—Columbia Risk Score
title Predicting Long Term Outcome in Patients Treated With Continuous Flow Left Ventricular Assist Device: The Penn—Columbia Risk Score
title_full Predicting Long Term Outcome in Patients Treated With Continuous Flow Left Ventricular Assist Device: The Penn—Columbia Risk Score
title_fullStr Predicting Long Term Outcome in Patients Treated With Continuous Flow Left Ventricular Assist Device: The Penn—Columbia Risk Score
title_full_unstemmed Predicting Long Term Outcome in Patients Treated With Continuous Flow Left Ventricular Assist Device: The Penn—Columbia Risk Score
title_short Predicting Long Term Outcome in Patients Treated With Continuous Flow Left Ventricular Assist Device: The Penn—Columbia Risk Score
title_sort predicting long term outcome in patients treated with continuous flow left ventricular assist device: the penn—columbia risk score
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5907534/
https://www.ncbi.nlm.nih.gov/pubmed/29514805
http://dx.doi.org/10.1161/JAHA.117.006408
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