Comparative Analysis of Established Risk Scores and Novel Hemodynamic Metrics in Predicting Right Ventricular Failure in Left Ventricular Assist Device Patients.
Right heart failure
mechanical circulatory support
prediction models
preoperative end-organ dysfunction
Journal
Journal of cardiac failure
ISSN: 1532-8414
Titre abrégé: J Card Fail
Pays: United States
ID NLM: 9442138
Informations de publication
Date de publication:
Aug 2019
Aug 2019
Historique:
received:
13
04
2018
revised:
15
01
2019
accepted:
12
02
2019
pubmed:
23
2
2019
medline:
23
7
2020
entrez:
22
2
2019
Statut:
ppublish
Résumé
Right ventricular failure (RVF) portends poor outcomes after left ventricular assist device (LVAD) implantation. Although numerous RVF predictive models have been developed, there are few independent comparative analyses of these risk models. RVF was defined as use of inotropes for >14 days, inhaled pulmonary vasodilators for >48 hours or unplanned right ventricular mechanical support postoperatively during the index hospitalization. Risk models were evaluated for the primary outcome of RVF by means of logistic regression and receiver operating characteristic curves. Among 93 LVAD patients with complete data from 2011 to 2016, the Michigan RVF score (C = 0.74 [95% CI 0.61-0.87]; P = .0004) was the only risk model to demonstrate significant discrimination for RVF, compared with newer risk scores (Utah, Pitt, EuroMACS). Among individual hemodynamic/echocardiographic metrics, preoperative right ventricular dysfunction (C = 0.72 [95% CI 0.58-0.85]; P = .0022) also demonstrated significant discrimination of RVF. The Michigan RVF score was also the best predictor of in-hospital mortality (C = 0.67 [95% CI 0.52-0.83]; P = .0319) and 3-year survival (Kaplan-Meier log-rank 0.0135). In external validation analysis, the more established Michigan RVF score-which emphasizes preoperative hemodynamic instability and target end-organ dysfunction-performed best, albeit modestly, in predicting RVF and demonstrated association with in-hospital and long-term mortality.
Sections du résumé
BACKGROUND
BACKGROUND
Right ventricular failure (RVF) portends poor outcomes after left ventricular assist device (LVAD) implantation. Although numerous RVF predictive models have been developed, there are few independent comparative analyses of these risk models.
METHODS AND RESULTS
RESULTS
RVF was defined as use of inotropes for >14 days, inhaled pulmonary vasodilators for >48 hours or unplanned right ventricular mechanical support postoperatively during the index hospitalization. Risk models were evaluated for the primary outcome of RVF by means of logistic regression and receiver operating characteristic curves. Among 93 LVAD patients with complete data from 2011 to 2016, the Michigan RVF score (C = 0.74 [95% CI 0.61-0.87]; P = .0004) was the only risk model to demonstrate significant discrimination for RVF, compared with newer risk scores (Utah, Pitt, EuroMACS). Among individual hemodynamic/echocardiographic metrics, preoperative right ventricular dysfunction (C = 0.72 [95% CI 0.58-0.85]; P = .0022) also demonstrated significant discrimination of RVF. The Michigan RVF score was also the best predictor of in-hospital mortality (C = 0.67 [95% CI 0.52-0.83]; P = .0319) and 3-year survival (Kaplan-Meier log-rank 0.0135).
CONCLUSIONS
CONCLUSIONS
In external validation analysis, the more established Michigan RVF score-which emphasizes preoperative hemodynamic instability and target end-organ dysfunction-performed best, albeit modestly, in predicting RVF and demonstrated association with in-hospital and long-term mortality.
Identifiants
pubmed: 30790625
pii: S1071-9164(19)30171-X
doi: 10.1016/j.cardfail.2019.02.011
pmc: PMC6945118
mid: NIHMS1063925
pii:
doi:
Types de publication
Comparative Study
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
620-628Subventions
Organisme : NHLBI NIH HHS
ID : K01 HL142848
Pays : United States
Commentaires et corrections
Type : CommentIn
Type : CommentIn
Type : CommentIn
Informations de copyright
Copyright © 2019 Elsevier Inc. All rights reserved.
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