Predictive models in extracorporeal membrane oxygenation (ECMO): a systematic review

Luca Giordano; Andrea Francavilla; Tomaso Bottio; Andrea Dell'Amore; Dario Gregori; Paolo Navalesi; Giulia Lorenzoni; Ileana Baldi

doi:10.1186/s13643-023-02211-7

Predictive models in extracorporeal membrane oxygenation (ECMO): a systematic review

Syst Rev. 2023 Mar 15;12(1):44. doi: 10.1186/s13643-023-02211-7.

Authors

Luca Giordano^#^{1

2}, Andrea Francavilla^#¹, Tomaso Bottio³, Andrea Dell'Amore³, Dario Gregori¹, Paolo Navalesi⁴, Giulia Lorenzoni¹, Ileana Baldi⁵

Affiliations

¹ Unit of Biostatistics, Epidemiology and Public Health, Department of Cardiac Thoracic Vascular Sciences and Public Health, University of Padova, Via Loredan 18, 35121, Padova, Italy.
² ClinOpsHub s.r.l., Via Manfredi Svevo 30 B, 72023, Mesagne, Brindisi, Italy.
³ Thoracic Surgery Unit, Department of Cardiac Thoracic Vascular Sciences and Public Health, University of Padova, Via Loredan 18, 35121, Padova, Italy.
⁴ Department of Medicine (DIMED), Institute of Anesthesia and Intensive Care, University of Padova, Padova, Italy.
⁵ Unit of Biostatistics, Epidemiology and Public Health, Department of Cardiac Thoracic Vascular Sciences and Public Health, University of Padova, Via Loredan 18, 35121, Padova, Italy. ileana.baldi@unipd.it.

^# Contributed equally.

Abstract

Purpose: Extracorporeal membrane oxygenation (ECMO) has been increasingly used in the last years to provide hemodynamic and respiratory support in critically ill patients. In this scenario, prognostic scores remain essential to choose which patients should initiate ECMO. This systematic review aims to assess the current landscape and inform subsequent efforts in the development of risk prediction tools for ECMO.

Methods: PubMed, CINAHL, Embase, MEDLINE and Scopus were consulted. Articles between Jan 2011 and Feb 2022, including adults undergoing ECMO reporting a newly developed and validated predictive model for mortality, were included. Studies based on animal models, systematic reviews, case reports and conference abstracts were excluded. Data extraction aimed to capture study characteristics, risk model characteristics and model performance. The risk of bias was evaluated through the prediction model risk-of-bias assessment tool (PROBAST). The protocol has been registered in Open Science Framework ( https://osf.io/fevw5 ).

Results: Twenty-six prognostic scores for in-hospital mortality were identified, with a study size ranging from 60 to 4557 patients. The most common candidate variables were age, lactate concentration, creatinine concentration, bilirubin concentration and days in mechanical ventilation prior to ECMO. Five out of 16 venous-arterial (VA)-ECMO scores and 3 out of 9 veno-venous (VV)-ECMO scores had been validated externally. Additionally, one score was developed for both VA and VV populations. No score was judged at low risk of bias.

Conclusion: Most models have not been validated externally and apply after ECMO initiation; thus, some uncertainty whether ECMO should be initiated still remains. It has yet to be determined whether and to what extent a new methodological perspective may enhance the performance of predictive models for ECMO, with the ultimate goal to implement a model that positively influences patient outcomes.

Keywords: ECMO; Extracorporeal membrane oxygenation; Mortality; Predictive models; Predictive scores.

Publication types

Systematic Review
Research Support, Non-U.S. Gov't

MeSH terms

Bias
Extracorporeal Membrane Oxygenation* / methods
Hospital Mortality
Risk Assessment
Risk Factors