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

Título

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

Autor

Wolfgang Huber, Ulrike Protzer, Roland M Schmid, Marcus R. Makowski, Gerhard Schneider, Markus Schwaiger, Tobias Lahmer, Christoph D. Spinner, Michael Dommasch, Fabian Geisler, Egon Burian, Rickmer F Braren, Georgios A Kaissis, Fabian K Lohöfer, Friederike Jungmann, Matthias Treiber

Descripción

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.

Fecha

2020

Materia

Computed tomography, Intensive care unit, clinical parameters, radiological parameters, COVID-19, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)

Identificador

DOI: 10.3390/jcm9051514

Fuente

Journal of Clinical Medicine

Editor

MDPI AG

Cobertura

Medicine

Archivos

https://socictopen.socict.org/files/to_import/pdfs/4957596.pdf

Colección

Citación

Wolfgang Huber, Ulrike Protzer, Roland M Schmid, Marcus R. Makowski, Gerhard Schneider, Markus Schwaiger, Tobias Lahmer, Christoph D. Spinner, Michael Dommasch, Fabian Geisler, Egon Burian, Rickmer F Braren, Georgios A Kaissis, Fabian K Lohöfer, Friederike Jungmann, Matthias Treiber, “Intensive Care Risk Estimation in COVID-19 Pneumonia Based on Clinical and Imaging Parameters: Experiences from the Munich Cohort,” SOCICT Open, consulta 21 de abril de 2026, https://socictopen.socict.org/items/show/2639.

Formatos de Salida

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