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Article

Risk Stratification for ECMO Requirement in COVID-19 ICU Patients Using Quantitative Imaging Features in CT Scans on Admission

1
Department of Radiology, University Hospital, LMU Munich, 81377 Munich, Germany
2
Department of Anesthesiology, University Hospital, LMU Munich, 81377 Munich, Germany
*
Author to whom correspondence should be addressed.
Academic Editor: Renato Millioni
Diagnostics 2021, 11(6), 1029; https://doi.org/10.3390/diagnostics11061029
Received: 17 May 2021 / Revised: 29 May 2021 / Accepted: 31 May 2021 / Published: 3 June 2021
(1) Background: Extracorporeal membrane oxygenation (ECMO) therapy in intensive care units (ICUs) remains the last treatment option for Coronavirus disease 2019 (COVID-19) patients with severely affected lungs but is highly resource demanding. Early risk stratification for the need of ECMO therapy upon admission to the hospital using artificial intelligence (AI)-based computed tomography (CT) assessment and clinical scores is beneficial for patient assessment and resource management; (2) Methods: Retrospective single-center study with 95 confirmed COVID-19 patients admitted to the participating ICUs. Patients requiring ECMO therapy (n = 14) during ICU stay versus patients without ECMO treatment (n = 81) were evaluated for discriminative clinical prediction parameters and AI-based CT imaging features and their diagnostic potential to predict ECMO therapy. Reported patient data include clinical scores, AI-based CT findings and patient outcomes; (3) Results: Patients subsequently allocated to ECMO therapy had significantly higher sequential organ failure (SOFA) scores (p < 0.001) and significantly lower oxygenation indices on admission (p = 0.009) than patients with standard ICU therapy. The median time from hospital admission to ECMO placement was 1.4 days (IQR 0.2–4.0). The percentage of lung involvement on AI-based CT assessment on admission to the hospital was significantly higher in ECMO patients (p < 0.001). In binary logistic regression analyses for ECMO prediction including age, sex, body mass index (BMI), SOFA score on admission, lactate on admission and percentage of lung involvement on admission CTs, only SOFA score (OR 1.32, 95% CI 1.08–1.62) and lung involvement (OR 1.06, 95% CI 1.01–1.11) were significantly associated with subsequent ECMO allocation. Receiver operating characteristic (ROC) curves showed an area under the curve (AUC) of 0.83 (95% CI 0.73–0.94) for lung involvement on admission CT and 0.82 (95% CI 0.72–0.91) for SOFA scores on ICU admission. A combined parameter of SOFA on ICU admission and lung involvement on admission CT yielded an AUC of 0.91 (0.84–0.97) with a sensitivity of 0.93 and a specificity of 0.84 for ECMO prediction; (4) Conclusions: AI-based assessment of lung involvement on CT scans on admission to the hospital and SOFA scoring, especially if combined, can be used as risk stratification tools for subsequent requirement for ECMO therapy in patients with severe COVID-19 disease to improve resource management in ICU settings. View Full-Text
Keywords: COVID-19; respiratory distress syndrome; extracorporeal membrane oxygenation; artificial intelligence; computed tomography scan COVID-19; respiratory distress syndrome; extracorporeal membrane oxygenation; artificial intelligence; computed tomography scan
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MDPI and ACS Style

Gresser, E.; Reich, J.; Sabel, B.O.; Kunz, W.G.; Fabritius, M.P.; Rübenthaler, J.; Ingrisch, M.; Wassilowsky, D.; Irlbeck, M.; Ricke, J.; Puhr-Westerheide, D. Risk Stratification for ECMO Requirement in COVID-19 ICU Patients Using Quantitative Imaging Features in CT Scans on Admission. Diagnostics 2021, 11, 1029. https://doi.org/10.3390/diagnostics11061029

AMA Style

Gresser E, Reich J, Sabel BO, Kunz WG, Fabritius MP, Rübenthaler J, Ingrisch M, Wassilowsky D, Irlbeck M, Ricke J, Puhr-Westerheide D. Risk Stratification for ECMO Requirement in COVID-19 ICU Patients Using Quantitative Imaging Features in CT Scans on Admission. Diagnostics. 2021; 11(6):1029. https://doi.org/10.3390/diagnostics11061029

Chicago/Turabian Style

Gresser, Eva, Jakob Reich, Bastian O. Sabel, Wolfgang G. Kunz, Matthias P. Fabritius, Johannes Rübenthaler, Michael Ingrisch, Dietmar Wassilowsky, Michael Irlbeck, Jens Ricke, and Daniel Puhr-Westerheide. 2021. "Risk Stratification for ECMO Requirement in COVID-19 ICU Patients Using Quantitative Imaging Features in CT Scans on Admission" Diagnostics 11, no. 6: 1029. https://doi.org/10.3390/diagnostics11061029

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