About: Intensive care risk estimation in COVID-19 pneumonia based on clinical and imaging parameters: experiences from the Munich cohort

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About: Intensive care risk estimation in COVID-19 pneumonia based on clinical and imaging parameters: experiences from the Munich cohort Goto Sponge NotDistinct Permalink

An Entity of Type : schema:ScholarlyArticle, within Data Space : wasabi.inria.fr associated with source document(s)

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	Intensive care risk estimation in COVID-19 pneumonia based on clinical and imaging parameters: experiences from the Munich cohort
Creator	Protzer, Ulrike Huber, Wolfgang Lahmer, Tobias Schmid, Roland Dommasch, Michael Geisler, Fabian Makowski, Marcus Schneider, Gerhard Spinner, Christoph Treiber, Matthias Braren, Rickmer Burian, Egon Jungmann, Friederike Kaissis, Georgios Lohöfer, Fabian Schwaiger, Markus
Source	MedRxiv
abstract	Background: The rapidly evolving dynamics of coronavirus disease 2019 (COVID-19) and the steadily 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. Methods: We collected clinical, laboratory and imaging data from 65 patients with confirmed COVID-19 infection based on PCR positivity. IL-6, CRP, leukocyte and lymphocyte counts were determined in blood samples. Two radiologists evaluated the severity of imaging 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 intensive care unit treatment. Findings: Patients with a severe course of COVID-19 had significantly increased IL-6, 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 ROC-AUC of 0.79 +/- 0.1. The most important predictive parameters were affected lung volume, radiological severity score, CRP and IL-6. Summary and Conclusion: Estimation of need for intensive care treatment is possible based on the clinical and radiological parameters.
has issue date	2020-05-08(xsd:dateTime)
bibo:doi	10.1101/2020.05.04.20076349
has license	medrxiv
sha1sum (hex)	b34a1122a20b0e6ab0977fd88faf8f1bcd5a7628
schema:url	https://doi.org/10.1101/2020.05.04.20076349
resource representing a document's title	Intensive care risk estimation in COVID-19 pneumonia based on clinical and imaging parameters: experiences from the Munich cohort
resource representing a document's body	covid:b34a1122a20b0e6ab0977fd88faf8f1bcd5a7628#body_text
is schema:about of	named entity 'evolving' named entity 'risk' named entity 'HIGH RISK' named entity 'EVOLVING' named entity 'high risk' named entity 'Here' named entity 'severe' named entity 'ICU' named entity 'intensive care unit' named entity 'medRxiv' named entity 'mechanical ventilation' named entity 'medRxiv' named entity 'CC-BY-ND' named entity 'CRP' named entity 'arterial oxygen tension' named entity 'New York' named entity 'ICU' named entity 'ICU' named entity 'viral load' named entity 'CC-BY-ND' named entity 'Helsinki declaration' named entity 'ICU' named entity 'imaging studies' named entity 'pharyngeal' named entity 'random forest classification' named entity 'COVID' named entity 'preprint' named entity 'comorbidity' named entity 'ICU' named entity 'IL-6' named entity 'LDH' named entity 'preprint' named entity 'Technical University of Munich' named entity 'cardiovascular shock' named entity 'chest CT' named entity 'statistical analysis' named entity 'chest CT' named entity 'creatine kinase MB' named entity 'Wuhan' named entity 'CC-BY-ND' named entity 'respiratory failure' named entity 'computed tomography images' named entity 'lymphocyte count' named entity 'Routine laboratory tests' named entity 'anti-viral therapy' named entity 'preprint' named entity 'COVID-19 pandemic' named entity 'lower respiratory tract' named entity 'Coronavirus' named entity 'CRP' named entity 'triage' named entity 'medRxiv' named entity 'preprint' named entity 'data analysis' named entity 'institutional review board' named entity 'CRP' named entity 'dyspnea' named entity 'medRxiv' named entity 'descriptive statistics' named entity 'Netherlands' named entity 'dyspnea' named entity 'CRP' named entity 'emergency department' named entity 'intensive care unit' named entity 'pneumonia' named entity 'pneumonia' named entity 'PaO2' named entity 'serum' named entity 'clinically defined' named entity 'lymphopenia'

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