Mortality prediction models in acute respiratory failure treated with extracorporeal membrane oxygenation: it must be firstly designed for clinicians and beside use

In a recent issue of Critical Care, we read with great interest the article by Enger and colleagues [1] regarding the development of novel mortality prediction models on extracorporeal membrane oxygenation (ECMO) in acute respiratory failure and the comparison of its performance with the ECMOnet (Extracorporeal Membrane Oxygenation Network) [2], PRESERVE (Predicting Death for Severe Acute Respiratory Distress Syndrome on Veno-venous Extracorporeal Membrane Oxygenation) [3], and Sequential Organ Failure Assessment scores. We commend the efforts made by the authors to externally validate the ECMOnet and the PRESERVE scores, but we recognize that a problem common to all prediction models, including their own, is that inevitably performance is better in the dataset from which they were derived. A potential limitation of the approach taken by Enger and colleagues is that the calculation of predicted mortality requires the use of a computer-generated algorithm which may limit immediate ease of use and applicability by clinicians. Prediction scores (such as the ECMOnet and the PRESERVE) which contain