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

Abstract

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.

Keywords: COVID-19; clinical parameters; computed tomography; intensive care unit; radiological parameters; severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2).

Figure 1

Images exemplifying the five radiological severity scores in computed tomography images alongside their descriptions. COVID, coronavirus disease.

Figure 2

Axial (A,B) and coronal (C,D) reformations of the chest computed tomography (CT) of a 68-year-old female patient presenting with fever and cough. Radiological severity grade 3 was assigned. Lung volume quantification accounted for >90% ventilated volume (shaded blue in B and D).

Figure 3

Axial (A,B) and coronal (C,D) reformations of the chest CT of a 78-year-old-male patient presenting with mild dyspnea. Radiological severity grade 4 was assigned. Forty-five percent of the lung volume is affected by characteristic parenchymal changes, most prominent in the right upper lobe (shaded blue in B and D).