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Open AccessArticle

Intensive Care Risk Estimation in COVID-19 Pneumonia Based on Clinical and Imaging Parameters: Experiences from the Munich Cohort

1
Department of Diagnostic and Interventional Radiology, School of Medicine, Technical University of Munich, Ismaninger Str. 22, 81675 Munich, Germany
2
Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Technical University of Munich, Ismaninger Str. 22, 81675 Munich, Germany
3
Department of Internal Medicine II, School of Medicine, Technical University of Munich, Ismaninger Str. 22, 81675 Munich, Germany
4
Department of Internal Medicine I, School of Medicine, Technical University of Munich, Ismaninger Str. 22, 81675 Munich, Germany
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Clinic for Anesthesiology and Intensive Care Medicine, School of Medicine, Technical University of Munich, Ismaninger Str. 22, 81675 Munich, Germany
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Institute of Virology, School of Medicine, Technical University of Munich, Ismaninger Str. 22, 81675 Munich, Germany
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School of Medicine, Dean, Technical University of Munich, Ismaninger Str. 22, 81675 Munich, Germany
*
Author to whom correspondence should be addressed.
These authors contributed equally to this work.
These authors contributed equally to this work.
J. Clin. Med. 2020, 9(5), 1514; https://doi.org/10.3390/jcm9051514
Received: 20 April 2020 / Revised: 11 May 2020 / Accepted: 15 May 2020 / Published: 18 May 2020
(This article belongs to the Section Emergency Medicine)
The evolving dynamics of coronavirus disease 2019 (COVID-19) and the increasing infection numbers require diagnostic tools to identify patients at high risk for a severe disease course. Here we evaluate clinical and imaging parameters for estimating the need of intensive care unit (ICU) treatment. We collected clinical, laboratory and imaging data from 65 patients with confirmed COVID-19 infection based on polymerase chain reaction (PCR) testing. Two radiologists evaluated the severity of findings in computed tomography (CT) images on a scale from 1 (no characteristic signs of COVID-19) to 5 (confluent ground glass opacities in over 50% of the lung parenchyma). The volume of affected lung was quantified using commercially available software. Machine learning modelling was performed to estimate the risk for ICU treatment. Patients with a severe course of COVID-19 had significantly increased interleukin (IL)-6, C-reactive protein (CRP), and leukocyte counts and significantly decreased lymphocyte counts. The radiological severity grading was significantly increased in ICU patients. Multivariate random forest modelling showed a mean ± standard deviation sensitivity, specificity and accuracy of 0.72 ± 0.1, 0.86 ± 0.16 and 0.80 ± 0.1 and a receiver operating characteristic-area under curve (ROC-AUC) of 0.79 ± 0.1. The need for ICU treatment is independently associated with affected lung volume, radiological severity score, CRP, and IL-6. View Full-Text
Keywords: COVID-19; severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); clinical parameters; radiological parameters; computed tomography; intensive care unit COVID-19; severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); clinical parameters; radiological parameters; computed tomography; intensive care unit
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Burian, E.; Jungmann, F.; Kaissis, G.A.; Lohöfer, F.K.; Spinner, C.D.; Lahmer, T.; Treiber, M.; Dommasch, M.; Schneider, G.; Geisler, F.; Huber, W.; Protzer, U.; Schmid, R.M.; Schwaiger, M.; Makowski, M.R.; Braren, R.F. Intensive Care Risk Estimation in COVID-19 Pneumonia Based on Clinical and Imaging Parameters: Experiences from the Munich Cohort. J. Clin. Med. 2020, 9, 1514.

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