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

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. 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: The need for intensive care treatment is independently associated with affected lung volume, radiological severity score, CRP and IL-6. Funding Statement: No external funding was obtained. Declaration of Interests: The authors declare no conflict of interest. Ethics Approval Statement: This study was conducted according to the principles set forward in the Declaration of Helsinki and according to Good Clinical Practice. All patients gave consent for scientific evaluation of clinical and imaging data at the time of admission. The local institutional review board has approved this prospective study (protocol numbers: 245/19 S-SR and 111/20 S).