Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2022 Feb 14;15(3):237-247.
doi: 10.1016/j.jcin.2021.09.032. Epub 2022 Jan 12.

Resuscitation Using ECPR During In-Hospital Cardiac Arrest (RESCUE-IHCA) Mortality Prediction Score and External Validation

Joseph E Tonna  1 , Craig H Selzman  2 , Saket Girotra  3 , Angela P Presson  4 , Ravi R Thiagarajan  5 , Lance B Becker  6 , Chong Zhang  4 , Peter Rycus  7 , Heather T Keenan  8 ; American Heart Association Get With the Guidelines–Resuscitation Investigators
Affiliations

Resuscitation Using ECPR During In-Hospital Cardiac Arrest (RESCUE-IHCA) Mortality Prediction Score and External Validation

Joseph E Tonna et al. JACC Cardiovasc Interv. .

Abstract

Objectives: The aim of this study was to develop and validate a score to accurately predict the probability of death for adult extracorporeal cardiopulmonary resuscitation (ECPR).

Background: ECPR is being increasingly used to treat refractory in-hospital cardiac arrest (IHCA), but survival varies from 20% to 40%.

Methods: Adult patients with extracorporeal membrane oxygenation for IHCA (ECPR) were identified from the American Heart Association GWTG-R (Get With the Guidelines-Resuscitation) registry. A multivariate survival prediction model and score were developed to predict hospital death. Findings were externally validated in a separate cohort of patients from the Extracorporeal Life Support Organization registry who underwent ECPR for IHCA.

Results: A total of 1,075 patients treated with ECPR were included. Twenty-eight percent survived to discharge in both the derivation and validation cohorts. A total of 6 variables were associated with in-hospital death: age, time of day, initial rhythm, history of renal insufficiency, patient type (cardiac vs noncardiac and medical vs surgical), and duration of the cardiac arrest event, which were combined into the RESCUE-IHCA (Resuscitation Using ECPR During IHCA) score. The model had good discrimination (area under the curve: 0.719; 95% CI: 0.680-0.757) and acceptable calibration (Hosmer and Lemeshow goodness of fit P = 0.079). Discrimination was fair in the external validation cohort (area under the curve: 0.676; 95% CI: 0.606-0.746) with good calibration (P = 0.66), demonstrating the model's ability to predict in-hospital death across a wide range of probabilities.

Conclusions: The RESCUE-IHCA score can be used by clinicians in real time to predict in-hospital death among patients with IHCA who are treated with ECPR.

Keywords: extracorporeal cardiopulmonary resuscitation; extracorporeal membrane oxygenation; in-hospital cardiac arrest; mortality prediction; survival prediction.

PubMed Disclaimer

Conflict of interest statement

Funding Support and Author Disclosures Dr Tonna was supported by a career development award (K23HL141596) from the National Heart, Lung, and Blood Institute of the National Institutes of Health. This study was also supported, in part, by the University of Utah Study Design and Biostatistics Center, with funding in part from the National Center for Research Resources and the National Center for Advancing Translational Sciences, National Institutes of Health, through grant UL1TR002538 (formerly 5UL1TR001067-05, 8UL1TR000105, and UL1RR025764). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. None of the funding sources were involved in the design or conduct of the study; collection, management, analysis, or interpretation of the data; or preparation, review, or approval of the manuscript. Dr Tonna has received speaker fees and travel compensation from LivaNova and Philips Healthcare, unrelated to this work. All other authors have reported that they have no relationships relevant to the contents of this paper to disclose.

Figures

Figure 1:
Figure 1:. Study enrollment flowchart.
Patients with IHCA from the AHA GWTG-R Registry treated with ECPR. Patients with prior OHCA, non-index arrest, or missing outcome data were excluded, as were patients who arrested at a hospital where ECPR had not previously been performed.
Figure 2:
Figure 2:. Adjusted odds of individual risk factors with death.
Adjusted association (odds ratio of death) for individual patient factors retained the multivariate mortality prediction model.
Figure 3:
Figure 3:. Predicted probability of death across points.
Curve with 95% CI shading showing the association between score points and mortality of in-hospital death, among the derivation cohort. Abbreviations: CI—confidence interval
Figure 4:
Figure 4:. Calibration Plot of Observed (Y Axis) versus Predicted (X Axis) Mortality from Derivation dataset (Get With The Guidelines®-R).
Discrimination and calibration of the model among 1,075 patients from the AHA GWTG-R registry. Correlation between observed mortality the AHA GWTG-R dataset (Y axis) vs predicted mortality according to the RESCUE-IHCA mortality prediction score (X axis), in the derivation dataset. A p value greater than 0.05 indicates acceptable fit.
Figure 5:
Figure 5:. Calibration Plot of Observed (Y Axis) versus Predicted (X Axis) Mortality from Validation dataset (Extracorporeal Life Support Organization).
Discrimination and calibration from external validation among 297 cardiac arrest patients treated with ECMO/ECPR from the ELSO Registry. Correlation between observed mortality the ELSO dataset (Y axis) vs predicted mortality according to the RESCUE-IHCA mortality prediction score (X axis), in the external validation dataset. A p value greater than 0.05 indicates acceptable fit.
Central Illustration:
Central Illustration:. RESCUE-IHCA Score to predict hospital mortality for adult ECPR.
The probability of hospital mortality for adult ECPR can be accurately predicted with the RESCUE-IHCA Score using five pre-existing patient factors (age, time of day, initial rhythm, history of renal insufficiency, and patient type (cardiac versus non-cardiac and medical versus surgical)), and one intra-arrest factor (duration of the cardiac arrest event). The score predicts the probability of mortality (ranging from 22-99%) with 72% accuracy and is externally validated with similar performance.
See this image and copyright information in PMC

Comment in

References

    1. Richardson AS, Schmidt M, Bailey M, Pellegrino VA, Rycus PT, Pilcher DV. ECMO Cardio-Pulmonary Resuscitation (ECPR), trends in survival from an international multicentre cohort study over 12-years. Resuscitation 2017;112:34–40. - PubMed
    1. Yannopoulos D, Bartos J, Raveendran G et al. Advanced reperfusion strategies for patients with out-of-hospital cardiac arrest and refractory ventricular fibrillation (ARREST): a phase 2, single centre, open-label, randomised controlled trial. The Lancet 2020. - PMC - PubMed
    1. D'Arrigo S, Cacciola S, Dennis M et al. Predictors of favourable outcome after in-hospital cardiac arrest treated with extracorporeal cardiopulmonary resuscitation: A systematic review and meta-analysis. Resuscitation 2017;121:62–70. - PubMed
    1. Stub D, Bernard S, Pellegrino V et al. Refractory cardiac arrest treated with mechanical CPR, hypothermia, ECMO and early reperfusion (the CHEER trial). Resuscitation 2015;86:88–94. - PubMed
    1. Tonna JE, Selzman CH, Girotra S et al. Patient and Institutional Characteristics Influence the Decision to Use Extracorporeal Cardiopulmonary Resuscitation for In-Hospital Cardiac Arrest. J Am Heart Assoc 2020;9:e015522. - PMC - PubMed

Publication types