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. 2023 Feb;49(2):131-141.
doi: 10.1007/s00134-022-06947-z. Epub 2023 Jan 4.

Prognostic models for mortality risk in patients requiring ECMO

Lara C A Pladet  1 , Jaimie M M Barten  2 , Lisette M Vernooij  2 , Carlos V Elzo Kraemer  3 , Jeroen J H Bunge  4   5 , Erik Scholten  6 , Leon J Montenij  7 , Marijn Kuijpers  8 , Dirk W Donker  2   9 , Olaf L Cremer  2 , Christiaan L Meuwese  4   5
Affiliations

Prognostic models for mortality risk in patients requiring ECMO

Lara C A Pladet et al. Intensive Care Med. 2023 Feb.

Abstract

Purpose: To provide an overview and evaluate the performance of mortality prediction models for patients requiring extracorporeal membrane oxygenation (ECMO) support for refractory cardiocirculatory or respiratory failure.

Methods: A systematic literature search was undertaken to identify studies developing and/or validating multivariable prediction models for all-cause mortality in adults requiring or receiving veno-arterial (V-A) or veno-venous (V-V) ECMO. Estimates of model performance (observed versus expected (O:E) ratio and c-statistic) were summarized using random effects models and sources of heterogeneity were explored by means of meta-regression. Risk of bias was assessed using the Prediction model Risk Of BiAS Tool (PROBAST).

Results: Among 4905 articles screened, 96 studies described a total of 58 models and 225 external validations. Out of all 58 models which were specifically developed for ECMO patients, 14 (24%) were ever externally validated. Discriminatory ability of frequently validated models developed for ECMO patients (i.e., SAVE and RESP score) was moderate on average (pooled c-statistics between 0.66 and 0.70), and comparable to general intensive care population-based models (pooled c-statistics varying between 0.66 and 0.69 for the Simplified Acute Physiology Score II (SAPS II), Acute Physiology and Chronic Health Evaluation II (APACHE II) score and Sequential Organ Failure Assessment (SOFA) score). Nearly all models tended to underestimate mortality with a pooled O:E > 1. There was a wide variability in reported performance measures of external validations, reflecting a large between-study heterogeneity. Only 1 of the 58 models met the generally accepted Prediction model Risk Of BiAS Tool criteria of good quality. Importantly, all predicted outcomes were conditional on the fact that ECMO support had already been initiated, thereby reducing their applicability for patient selection in clinical practice.

Conclusions: A large number of mortality prediction models have been developed for ECMO patients, yet only a minority has been externally validated. Furthermore, we observed only moderate predictive performance, large heterogeneity between-study populations and model performance, and poor methodological quality overall. Most importantly, current models are unsuitable to provide decision support for selecting individuals in whom initiation of ECMO would be most beneficial, as all models were developed in ECMO patients only and the decision to start ECMO had, therefore, already been made.

Keywords: Extracorporeal life support; Extracorporeal membrane oxygenation; Mortality prediction; Systematic review.

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Conflict of interest statement

None of the authors has conflicts of interest to declare.

Figures

Fig. 1
Fig. 1
Study flow diagram
Fig. 2
Fig. 2
a Cohorts of all 58 derived models. b Cohorts of all 225 external validations
Fig. 3
Fig. 3
a Pooled c-statistics from external validations studies for different models. b Prediction intervals of the c-statistics for different models. c Pooled O:E ratios from external validation studies for different models. d Prediction intervals of the O:E ratios for different models
Fig. 4
Fig. 4
a Risk of bias assessments on the PROBAST-tool all derives models. b Applicability assessment based on the PROBAST-tool all derivations models. c Risk of bias assessments on the PROBAST-tool all external validations. d Applicability assessment based on the PROBAST-tool all external validations
See this image and copyright information in PMC

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