Literature DB >> 21764604

Selecting patients for heart transplantation: comparison of the Heart Failure Survival Score (HFSS) and the Seattle heart failure model (SHFM).

Ayumi Goda1, Paula Williams, Donna Mancini, Lars H Lund.   

Abstract

BACKGROUND: The Heart Failure Survival Score (HFSS) risk-stratifies patients with chronic heart failure (CHF) referred for heart transplantation using 7 parameters, including peak VO₂. The Seattle Heart Failure Model (SHFM) is a 20-variable model that combines clinical, laboratory and therapeutic data. Although both models have excellent accuracy, only the HFSS was derived and validated in patients referred for transplantation, and the HFSS and SHFM have not been directly compared.
METHODS: We tested the accuracy of the SHFM and compared the HFSS and SHFM in 715 patients referred for heart transplantation.
RESULTS: Over a follow-up of 962 ± 912 days, 354 patients died or received an urgent heart transplantation or a ventricular assist device. One-year event-free survival was 89%, 72% and 60%, respectively, for the low-, medium- and high-risk HFSS strata, and 93%, 76%, and 58%, respectively, for the low-, medium- and high-risk SHFM strata. The HFSS and SHFM were modestly correlated (R = -0.48, p < 0.001). In receiver operating characteristic curve analysis, areas under the curves (AUCs) for the HFSS and SHFM were comparable (1 year: 0.72 vs 0.73; 2-year: 0.70 vs 0.74, respectively) and incremental to New York Heart Association class. The 1- and 2-year combined HFSS+SHFM AUCs were 0.77 and 0.76, respectively, significantly better than the HFSS or SHFM alone.
CONCLUSIONS: The HFSS and SHFM provide accurate and comparable risk stratification in CHF patients referred for transplantation. Combining the HFSS and SHFM improves predictive ability. 2011 International Society for Heart and Lung Transplantation. Published by Elsevier Inc. All rights reserved.

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Year:  2011        PMID: 21764604     DOI: 10.1016/j.healun.2011.05.012

Source DB:  PubMed          Journal:  J Heart Lung Transplant        ISSN: 1053-2498            Impact factor:   10.247


  17 in total

1.  An Appraisal of Biomarker-Based Risk-Scoring Models in Chronic Heart Failure: Which One Is Best?

Authors:  Barbara S Doumouras; Douglas S Lee; Wayne C Levy; Ana C Alba
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2.  Physical and psychological symptom profiling and event-free survival in adults with moderate to advanced heart failure.

Authors:  Christopher S Lee; Jill M Gelow; Quin E Denfeld; James O Mudd; Donna Burgess; Jennifer K Green; Shirin O Hiatt; Corrine Y Jurgens
Journal:  J Cardiovasc Nurs       Date:  2014-07       Impact factor: 2.083

3.  Risk stratification of ambulatory patients with advanced heart failure undergoing evaluation for heart transplantation.

Authors:  Tomoko S Kato; Gerin R Stevens; Jeffrey Jiang; P Christian Schulze; Natalie Gukasyan; Matthew Lippel; Alison Levin; Shunichi Homma; Donna Mancini; Maryjane Farr
Journal:  J Heart Lung Transplant       Date:  2013-03       Impact factor: 10.247

4.  Gender aspects in clinical presentation and prognostication of chronic heart failure according to NT-proBNP and the Heart Failure Survival Score.

Authors:  Jennifer Franke; Andreas Lindmark; Matthias Hochadel; Christian Zugck; Eva Koerner; Jeannette Keppler; Philipp Ehlermann; Ralph Winkler; Ralf Zahn; Hugo A Katus; Jochen Senges; Lutz Frankenstein
Journal:  Clin Res Cardiol       Date:  2014-11-06       Impact factor: 5.460

5.  The Utility of Pentraxin and Modified Prognostic Scales in Predicting Outcomes of Patients with End-Stage Heart Failure.

Authors:  Wioletta Szczurek-Wasilewicz; Michał Skrzypek; Ewa Romuk; Mariusz Gąsior; Bożena Szyguła-Jurkiewicz
Journal:  J Clin Med       Date:  2022-05-04       Impact factor: 4.964

6.  Patient selection for advanced heart failure therapy referral.

Authors:  Alexander C Fanaroff; Adam D DeVore; Robert J Mentz; Mani A Daneshmand; Chetan B Patel
Journal:  Crit Pathw Cardiol       Date:  2014-03

7.  Is cardiopulmonary exercise testing essential to indicate ventricular assist device implantation in patients with INTERMACS profile 4-7?

Authors:  Teruhiko Imamura; Koichiro Kinugawa; Daisuke Nitta; Osamu Kinoshita; Kan Nawata; Minoru Ono
Journal:  J Artif Organs       Date:  2016-03-18       Impact factor: 1.731

8.  Hepatic dysfunction in ambulatory patients with heart failure: application of the MELD scoring system for outcome prediction.

Authors:  Margaret S Kim; Tomoko S Kato; Maryjane Farr; Christina Wu; Raymond C Givens; Ellias Collado; Donna M Mancini; P Christian Schulze
Journal:  J Am Coll Cardiol       Date:  2013-04-03       Impact factor: 24.094

Review 9.  Evaluation of a Heart Transplant Candidate.

Authors:  Sook Jin Lee; Kyung Hee Kim; Suk Keun Hong; Shelley Hankins
Journal:  Curr Cardiol Rep       Date:  2017-11-04       Impact factor: 2.931

10.  Assessment of a University of California, Los Angeles 4-variable risk score for advanced heart failure.

Authors:  Ulrik Sartipy; Ayumi Goda; Donna M Mancini; Lars H Lund
Journal:  J Am Heart Assoc       Date:  2014-06-06       Impact factor: 5.501

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