Chest computed tomography and alveolar–arterial oxygen gradient as rapid tools to diagnose and triage mildly symptomatic COVID-19 pneumonia patients
| Autor: | Marlise P. de Roos, Iris D. Kilsdonk, Pieter-Paul W. Hekking, Jan Peringa, Nynke G. Dijkstra, Peter W.A. Kunst, Paul Bresser, Herre J. Reesink |
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| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: | |
| Zdroj: | ERJ Open Research, Vol 7, Iss 1 (2021) |
| Druh dokumentu: | article |
| ISSN: | 2312-0541 23120541 |
| DOI: | 10.1183/23120541.00737-2020 |
| Popis: | 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 |
| Databáze: | Directory of Open Access Journals |
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