Chest computed tomography and alveolar–arterial oxygen gradient as rapid tools to diagnose and triage mildly symptomatic covid-19 pneumonia patients

Abstract

Background: In the coronavirus disease 2019 (COVID-19) pandemic, rapid clinical triage is crucial to determine which patients need hospitalisation. We hypothesised that chest computed tomography (CT) and alveolar-arterial oxygen tension ratio (A-a) gradient may be useful to triage these patients, since they reflect the severity of the pneumonia-associated ventilation/perfusion abnormalities. Methods: A retrospective analysis was performed in 235 consecutive patients suspected for COVID-19. The diagnostic protocol included low-dose chest CT and arterial blood gas analysis. In patients with CT-based COVID-19 pneumonia, the association between “need for hospitalisation” and A-a gradient was investigated by a multivariable logistic regression model. The A-a gradient was tested as a predictor for need for hospitalisation using receiver operating characteristic curve analysis and a logistic regression model. Results: 72 out of 235 patients (mean±SD age 55.5±14.6 years, 40% female) screened by chest CT showed evidence for COVID-19 pneumonia. In these patients, A-a gradient was shown to be a predictor of need for hospitalisation, with an optimal decision level (cut-off ) of 36.4 mmHg (95% CI 0.70–0.91, p<0.001). The A-a gradient was shown to be independently associated with need for hospitalisation (OR 1.97 (95% CI 1.23–3.15), p=0.005; A-a gradient per 10 points) from CT severity score (OR 1.13 (95% CI 0.94–1.36), p=0.191), National Early Warning Score (OR 1.19 (95% CI 0.91–1.57), p=0.321) or peripheral oxygen saturation (OR 0.88 (95% CI 0.68–1.14), p=0.345). Conclusion: Low-dose chest CT and the A-a gradient may serve as rapid and accurate tools to diagnose COVID-19 pneumonia and to select mildly symptomatic patients in need for hospitalisation.