Abstract 10719: Deep Learning to Estimate COVID-19 Mortality Risk from Chest Radiographs

Abstract

Introduction: Management of coronavirus disease 2019 (COVID-19) requires accurate assessment of risk of future cardiopulmonary complications. Deep learning can extract complex relationships between medical imaging and clinical outcomes. Hypothesis: A deep learning model can predict 30-day mortality from COVID-19 based on a chest radiograph image. Methods: A deep learning model (CXR-CovRisk) was developed to estimate 30-day mortality risk using a single chest radiograph image (chest x-ray or CXR). The model was developed using 1,738 patients with PCR-confirmed coronavirus disease 2019 (COVID-19) from four Boston-area hospitals between March 1, 2020 and April 24, 2020. CXR-CovRisk was tested on 903 consecutive patients with confirmed COVID-19 between April 25, 2020 and June 15, 2020. CXR-CovRisk was compared to two published deep learning models (PXS and COVID-GMIC) and a clinical risk factor-based severity score for discrimination of 30-day mortality. The continuous risk score was converted to three risk groups: Low, Medium, and High based on development dataset probability quantiles. Results are provided for the independent testing set only Results: CXR-CovRisk had high discrimination for 30-day mortality (AUC = 0.839, 95% CI [0.79,0.89]), which was higher than when using a deep learning lung disease severity score (PXS AUC 0.750 [0.70,0.80], p < 0.001) or the output of a model trained for 96-hour mortality prediction (COVID-GMIC 0.755 [0.70,0.81], p = 0.003). CXR-CovRisk had added value to the clinical risk-factor based severity score (Clinical Severity Score AUC 0.799 [0.76,0.84] vs. Combined AUC 0.872 [0.84,0.90], p < 0.001). Among outpatients not admitted to the hospital, the CXR-CovRisk High-risk group had a high rate of subsequent hospital admission and 30-day mortality (composite event rate 11/26, 42.3%), higher than the medium-risk (30/179, 16.8%, p=0.005) and low-risk groups (17/172, 9.9%, p < 0.001). Conclusion: A deep learning model, CXR-CovRisk, can estimate 30-day mortality risk from a chest radiograph image.