Imaging-based indices combining disease severity and time from disease onset to predict COVID-19 mortality: A cohort study

Abstract

Background COVID-19 prognostic factors include age, sex, comorbidities, laboratory and imaging findings, and time from symptom onset to seeking care. Purpose The study aim was to evaluate indices combining disease severity measures and time from disease onset to predict mortality of COVID-19 patients admitted to the emergency department (ED). Materials and methods All consecutive COVID-19 patients who underwent both computed tomography (CT) and chest X-ray (CXR) at ED presentation between 27/02/2020 and 13/03/2020 were included. CT visual score of disease extension and CXR Radiographic Assessment of Lung Edema (RALE) score were collected. The CT- and CXR-based scores, C-reactive protein (CRP), and oxygen saturation levels (sO2) were separately combined with time from symptom onset to ED presentation to obtain severity/time indices. Multivariable regression age- and sex-adjusted models without and with severity/time indices were compared. For CXR-RALE, the models were tested in a validation cohort. Results Of the 308 included patients, 55 (17.9%) died. In multivariable logistic age- and sex-adjusted models for death at 30 days, severity/time indices showed good discrimination ability, higher for imaging than for laboratory measures (AUCCT = 0.92, AUCCXR = 0.90, AUCCRP = 0.88, AUCsO2 = 0.88). AUCCXR was lower in the validation cohort (0.79). The models including severity/time indices performed slightly better than models including measures of disease severity not combined with time and those including the Charlson Comorbidity Index, except for CRP-based models. Conclusion Time from symptom onset to ED admission is a strong prognostic factor and provides added value to the interpretation of imaging and laboratory findings at ED presentation.

Clinical prediction model for pulmonary thrombosis diagnosis in hospitalized patients with SARS-CoV-2 infection

“…The main limitation of our study is its retrospective nature. The RALE score is subject to interobserver variability, although the degree of agreement between RALE score points and lung involvement on CTPA is high [47]. Finally, the model was constructed with COVID-19 patients and suspected PT who underwent a CTPA to obtain a certain diagnosis.…”

Relationship between hyponatremia at hospital admission and cardiopulmonary profile at follow-up in patients with SARS-CoV-2 (COVID-19) infection

“…The RALE assessment has been found to be associated with a worse outcome in different conditions, such as ARDS [ 28 , 31 ], refractory cardiogenic shock and refractory cardiac arrest [ 32 ]. Interestingly, in recent studies the RALE score has been indicated among the variables associated with a higher risk of death in COVID-19 patients [ 29 , 30 , 33 , 34 ].…”

Clinical prediction model for pulmonary embolism diagnosis in hospitalized patients with SARS-CoV-2 infection

“…In our study, as published previously [42,43] The main limitation of our study is its retrospective nature. The RALE score is subject to interobserver variability, although the degree of agreement between RALE score points and lung involvement on CTPA is high [44].Finally, the model was constructed with COVID-19 patients and suspected PE who underwent a CTPA to obtain a certain diagnosis. Therefore, the model is applicable in this clinical scenario.…”