Prediction of mortality in adult patients with severe acute lung failure receiving veno-venous extracorporeal membrane oxygenation: a prospective observational study

Abstract

IntroductionVeno-venous extracorporeal membrane oxygenation (vvECMO) can be a life-saving therapy in patients with severe acute lung failure refractory to conventional therapy. Nevertheless, vvECMO is a procedure associated with high costs and resource utilization. The aim of this study was to assess published models for prediction of mortality following vvECMO and optimize an alternative model.MethodsEstablished mortality risk scores were validated to assess their usefulness in 304 adult patients undergoing vvECMO for refractory lung failure at the University Medical Center Regensburg from 2008 to 2013. A parsimonious prediction model was developed based on variables available before ECMO initiation using logistic regression modelling. We then assessed whether addition of variables available one day after ECMO implementation enhanced mortality prediction. Models were internally validated and calibrated by bootstrapping (400 runs). Predictive ability, goodness-of-fit and model discrimination were compared across the different models.ResultsIn the present study population, existing mortality prediction tools for vvECMO patients showed suboptimal performance. Evaluated before vvECMO initiation, a logistic prediction model comprising age, immunocompromised state, artificial minute ventilation, pre-ECMO serum lactate and hemoglobin concentrations showed best mortality prediction in our patients (area under curve, AUC: 0.75). Additional information about norepinephrine dosage, fraction of inspired oxygen, C-reactive protein and fibrinogen concentrations the first day following ECMO initiation further improved discrimination (AUC: 0.79, P = 0.03) and predictive ability (likelihood ratio test, P < 0.001). When classifying patients as lower (<40%) or higher (>80%) risk based on their predicted mortality, the pre-ECMO and day1-on-ECMO models had negative/positive predictive values of 76%/82% and 82%/81%, respectively.ConclusionsWhile pre-ECMO mortality prediction remains a challenge due to large patient heterogeneity, evaluation one day after ECMO initiation may improve the ability to separate lower- and higher-risk patients. Our findings support the clinical perception that chronic health condition, high comorbidity and reduced functional reserves are strongly related to survival during and following ECMO support. Renewed evaluation the first day after ECMO initiation may provide enhanced guidance for further handling of ECMO patients. Despite the usefulness of prediction models, thorough clinical evaluation should always represent the cornerstone in decision for ECMO.

Mathematical modeling of extracorporeal CO2 removal therapy

“…Acute Respiratory Distress Syndrome (ARDS) is still life threatening despite new strategies in mechanical ventilations [28,18,8]. Mortality and morbidity of chronic obstructive pulmonary disease (COPD) are also considerable [34,7].…”

Importance of metabolism variations in a model of extracorporeal carbon dioxide removal

“…Acute Lung Injuries (ALI) or Acute Respiratory Distress Syndrome (ARDS) are still life threatening despite new strategies in mechanical ventilations [1,2,3]. In a clinical environment, a patient with ARDS is typically ventilated with low tidal volumes (6ml/kg) and a driving pressure (maximal pressure) below 30 cmH 2 O.…”

“…In a clinical environment, a patient with ARDS is typically ventilated with low tidal volumes (6ml/kg) and a driving pressure (maximal pressure) below 30 cmH 2 O. This technique, named as protective ventilation strategy, is important to reduce ventilator-induced lung injuries [4].…”

Extracorporeal Gas Exchange for Acute Respiratory Failure in Adult Patients: A Systematic Review

“…Factors associated with poor outcomes after ECMO for acute respiratory failure include older age [26,27,30,32,33,49,50], a greater number of days of mechanical ventilation before ECMO establishment [26,27,30,33,50], a higher number of organ failures [26,27,30,32,33,49,50], low pre-ECMO respiratory system compliance [50], and immunosuppression [33,50,51]. Predictive survival models have been recently developed that might help clinicians select appropriate candidates for ECMO [33,[49][50][51][52].…”

“…Predictive survival models have been recently developed that might help clinicians select appropriate candidates for ECMO [33,[49][50][51][52]. For example, the Respiratory Extracorporeal Membrane Oxygenation Survival (RESP) score [50], constructed on data extracted from a large multicenter international population (n = 2,355), computes 12 simple pre-ECMO parameters, to provide a relevant and validated tool predicting survival after ECMO for acute respiratory failure.…”