Aims: Several scoring systems have been introduced for prognostication after initiating venoarterial extracorporeal membrane oxygenation (VA-ECMO) therapy. However, static scores offer limited guidance once VA-ECMO is implanted, although continued allocation of healthcare resources is critical. Patients requiring continued VA-ECMO support are extremely unstable, with minimal heart function and multi-organ failure in most cases. The aim of the present study was to develop and validate a dynamic prognostic model for patients treated with VA-ECMO.
Methods and results: A derivation cohort included 205 all-comers undergoing VA-ECMO implantation at a tertiary referral hospital (51% received VA-ECMO during resuscitation and 43% had severe shock). Two prediction models based on point-of-care biomarkers were developed using penalised logistic regression in an elastic net approach. A validation cohort was recruited from an independent tertiary referral hospital. Comparators for the prediction of hospital survival were the SAVE score (area under the receiver operation characteristic curve (AUC) of 0.686), the SAPS score (AUC 0.679), the APACHE score (AUC 0.662) and the SOFA score (AUC 0.732) in 6-hour survivors. The 6-hour PREDICT VA-ECMO score (based on lactate, pH and standard bicarbonate concentration) outperformed the comparator scores with an AUC of 0.823. The 12-hour PREDICT VA-ECMO integrated lactate, pH and standard bicarbonate concentration at 1 hour, 6 hours and 12 hours after ECMO insertion allowed even better prognostication (AUC 0.839). Performance of the scores in the external validation cohort was good (AUCs 0.718 for the 6-hour score and 0.735 for the 12-hour score, respectively).
Conclusion: In patients requiring VA-ECMO therapy, a dynamic score using three point-of-care biomarkers predicts hospital mortality with high reliability. Furthermore, the PREDICT scores are the first scores for extracorporeal cardiopulmonary resuscitation patients.
Keywords: ECLS; ECMO; VA-ECMO; cardiogenic shock; eCPR; prognosis.