Sage Journals: Discover world-class research

Abstract

Aims:

Several scoring systems have been introduced for prognostication after initiating venoarterial extracorporeal membrane oxygenation (VA-ECMO) therapy. However, static scores offer limited guidance once VA-ECMO is implanted, although continued allocation of healthcare resources is critical. Patients requiring continued VA-ECMO support are extremely unstable, with minimal heart function and multi-organ failure in most cases. The aim of the present study was to develop and validate a dynamic prognostic model for patients treated with VA-ECMO.

Methods and results:

A derivation cohort included 205 all-comers undergoing VA-ECMO implantation at a tertiary referral hospital (51% received VA-ECMO during resuscitation and 43% had severe shock). Two prediction models based on point-of-care biomarkers were developed using penalised logistic regression in an elastic net approach. A validation cohort was recruited from an independent tertiary referral hospital. Comparators for the prediction of hospital survival were the SAVE score (area under the receiver operation characteristic curve (AUC) of 0.686), the SAPS score (AUC 0.679), the APACHE score (AUC 0.662) and the SOFA score (AUC 0.732) in 6-hour survivors. The 6-hour PREDICT VA-ECMO score (based on lactate, pH and standard bicarbonate concentration) outperformed the comparator scores with an AUC of 0.823. The 12-hour PREDICT VA-ECMO integrated lactate, pH and standard bicarbonate concentration at 1 hour, 6 hours and 12 hours after ECMO insertion allowed even better prognostication (AUC 0.839). Performance of the scores in the external validation cohort was good (AUCs 0.718 for the 6-hour score and 0.735 for the 12-hour score, respectively).

Conclusion:

In patients requiring VA-ECMO therapy, a dynamic score using three point-of-care biomarkers predicts hospital mortality with high reliability. Furthermore, the PREDICT scores are the first scores for extracorporeal cardiopulmonary resuscitation patients.

Keywords

ECMO ECLS VA-ECMO cardiogenic shock eCPR prognosis

Get full access to this article

View all access options for this article.

References

Hou

Yin

et al . Safety research of extracorporeal membrane oxygenation treatment on cardiogenic shock: a multicenter clinical study. Minerva Cardioangiol 2016; 64: 121–126.

Kane

Thiagarajan

Wypij

et al . Rapid-response extracorporeal membrane oxygenation to support cardiopulmonary resuscitation in children with cardiac disease. Circulation 2010; 122 (11 Suppl): S241–S248.

Kim

Lee

et al . Comparing extracorporeal cardiopulmonary resuscitation with conventional cardiopulmonary resuscitation: a meta-analysis. Resuscitation 2016; 103: 106–116.

Barbaro

Odetola

Kidwell

et al . Association of hospital-level volume of extracorporeal membrane oxygenation cases and mortality. Analysis of the extracorporeal life support organization registry. Am J Respir Crit Care Med 2015; 191: 894–901.

Karagiannidis

Brodie

Strassmann

et al . Extracorporeal membrane oxygenation: evolving epidemiology and mortality. Intensive Care Med 2016; 42: 889–896.

Muller

Flecher

Lebreton

et al . The ENCOURAGE mortality risk score and analysis of long-term outcomes after VA-ECMO for acute myocardial infarction with cardiogenic shock. Intensive Care Med 2016; 42: 370–378.

Schmidt

Burrell

Roberts

et al . Predicting survival after ECMO for refractory cardiogenic shock: the survival after veno-arterial-ECMO (SAVE)-score. Eur Heart J 2015; 36: 2246–2256.

Goldstein

Neragi-Miandoab

Mechanical bridge to decision: what are the options for the management of acute refractory cardiogenic shock?

Curr Heart Fail Rep 2011; 8: 51–58.

Staudacher

Bode

Wengenmayer

Duration of extracorporeal membrane oxygenation is a poor predictor of hospital survival. J Crit Care 2016; 32: 207–208.

10.

Bottiroli

Decaria

Maraffi

et al . Blood lactate normalization following venoarterial ECMO institution for refractory cardiogenic shock. Crit Care 2015; 19: 1–201.

11.

Zou

Hastie

Regularization and variable selection via the elastic net. J Roy Stat Soc: Series B (Statistical Methodology) 2005; 67: 301–320.

12.

Friedman

Hastie

Tibshirani

Regularization paths for generalized linear models via coordinate descent. J Statist Software 2010; 33: 1.

13.

Gerds

. ModelGood: Validation of risk prediction models. R package version 1.0.9, 2014. Retrieved from http://cran.r-project.org/package=ModelGood (accessed 11 May 2016).

14.

Chen

W-C

Huang

K-Y

Yao

C-W

et al . The modified SAVE score: predicting survival using urgent veno-arterial extracorporeal membrane oxygenation within 24 hours of arrival at the emergency department. Crit Care 2016; 20: 336.

15.

Rivers

Yataco

Jaehne

et al . Oxygen extraction and perfusion markers in severe sepsis and septic shock: diagnostic, therapeutic and outcome implications. Curr Opin Crit Care 2015; 21: 381–387.

16.

Vincent

J-L

Moreno

Takala

et al . The SOFA (Sepsis-related Organ Failure Assessment) score to describe organ dysfunction/failure. Intensive Care Med 1996; 22: 707–710.

17.

Wengenmayer

Rombach

Ramshorn

et al . Influence of low-flow time on survival after extracorporeal cardiopulmonary resuscitation (eCPR). Crit Care 2017; 21: 157.

18.

Nolan

Soar

Cariou

et al . European Resuscitation Council and European Society of Intensive Care MedicineGuidelines for post-resuscitation care 2015: section 5 of the European Resuscitation Council guidelines for resuscitation 2015. Resuscitation 2015; 95: 202–222.

19.

Perman

Kirkpatrick

Reitsma

et al . Timing of neuroprognostication in postcardiac arrest therapeutic hypothermia. Crit Care Med 2012; 40: 719–724.

20.

ELSO.ELSO guidelines for ECMO centers. https://www.elso.org/portals/0/igd/archive/filemanager/faf3f6a3c7cusersshyerdocumentselsoguidelinesecmocentersv1.8.pdf (accessed 14 March 2017).

Supplementary Material

Please find the following supplemental material available below.

For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.

For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.

0.00 MB

0.56 MB