Key result
Most of the 26 ECMO mortality prediction models lack external validation and apply only post-initiation.
Why the study?
Prognostic scores for ECMO are essential to guide patient selection, but most models lack external validation and do not address whether ECMO should be initiated.
Systematic Review
Existing predictive models for ECMO mortality suffer from high risk of bias and lack of external validation, highlighting the need for improved methodological approaches before clinical implementation.
Clinicians need validated ECMO scores for initiation decisions; this review extends the evidence base to guide future tool development.
PurposeExtracorporeal 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. MethodsPubMed, CINAHL, Embase, MEDLINE and Scopus were consulted. Articles between Jan 2011 and Feb 2022, including adults undergoing ECMO reporting a developed and validated predictive model, were included. 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).ResultsTwenty-six prognostic scores for in-hospital mortality were identified. 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.ConclusionMost models have not been validated externally or are inadequately built and apply after ECMO initiation, failing to answer if ECMO should be initiated or not. 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.
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Giordano et al. (2022) conducted a systematic review in Critically ill patients requiring Extracorporeal Membrane Oxygenation (ECMO). Predictive prognostic models was evaluated on In-hospital mortality prediction (model performance and validation). This systematic review identified 26 predictive prognostic models for ECMO mortality, finding that most have not been externally validated, are inadequately built, and apply only after ECMO initiation.
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