Mortality prediction for patients with the severe acute respiratory distress syndrome (ARDS) supported with veno-venous extracorporeal membrane oxygenation (VV-ECMO) is challenging. Clinical variables at baseline and on day 3 after initiation of ECMO support of all patients treated from October 2010 through April 2020 were analyzed. Multivariate logistic regression analysis was used to identify score variables. Internal and external (Monza, Italy) validation was used to evaluate the predictive value of the model. Overall, 272 patients could be included for data analysis and creation of the PREDICT VV-ECMO score. The score comprises five parameters (age, lung fibrosis, immunosuppression, cumulative fluid balance, and ECMO sweep gas flow on day 3). Higher score values are associated with a higher probability of hospital death. The score showed favorable results in derivation and external validation cohorts (area under the receiver operating curve, AUC derivation cohort 0.76 [95% confidence interval, CI, 0.71-0.82] and AUC validation cohort 0.74 [95% CI, 0.67-0.82]). Four risk classes were defined: I ≤ 30, II 31-60, III 61-90, and IV ≥ 91 with a predicted mortality of 28.2%, 56.2%, 84.8%, and 96.1%, respectively. The PREDICT VV-ECMO score suggests favorable performance in predicting hospital mortality under ongoing ECMO support providing a sound basis for further evaluation in larger cohorts.
Rilinger, J., Book, R., Kaier, K., Giani, M., Fumagalli, B., Jackel, M., et al. (2024). A Mortality Prediction Score for Patients With Veno-Venous Extracorporeal Membrane Oxygenation (VV-ECMO): The PREDICT VV-ECMO Score. ASAIO JOURNAL, 70(4), 293-298 [10.1097/MAT.0000000000002088].
A Mortality Prediction Score for Patients With Veno-Venous Extracorporeal Membrane Oxygenation (VV-ECMO): The PREDICT VV-ECMO Score
Giani M.;Fumagalli B.;Foti G.;
2024
Abstract
Mortality prediction for patients with the severe acute respiratory distress syndrome (ARDS) supported with veno-venous extracorporeal membrane oxygenation (VV-ECMO) is challenging. Clinical variables at baseline and on day 3 after initiation of ECMO support of all patients treated from October 2010 through April 2020 were analyzed. Multivariate logistic regression analysis was used to identify score variables. Internal and external (Monza, Italy) validation was used to evaluate the predictive value of the model. Overall, 272 patients could be included for data analysis and creation of the PREDICT VV-ECMO score. The score comprises five parameters (age, lung fibrosis, immunosuppression, cumulative fluid balance, and ECMO sweep gas flow on day 3). Higher score values are associated with a higher probability of hospital death. The score showed favorable results in derivation and external validation cohorts (area under the receiver operating curve, AUC derivation cohort 0.76 [95% confidence interval, CI, 0.71-0.82] and AUC validation cohort 0.74 [95% CI, 0.67-0.82]). Four risk classes were defined: I ≤ 30, II 31-60, III 61-90, and IV ≥ 91 with a predicted mortality of 28.2%, 56.2%, 84.8%, and 96.1%, respectively. The PREDICT VV-ECMO score suggests favorable performance in predicting hospital mortality under ongoing ECMO support providing a sound basis for further evaluation in larger cohorts.File | Dimensione | Formato | |
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