RT-PCR cycle threshold value in combination with visual scoring of chest computed tomography at hospital admission predicts outcome in COVID-19. Issue 6 (3rd June 2022)

• Record Type: Journal Article
• Authors: Ingberg, Edvin; Ahlstrand, Erik; Cajander, Per; Löf, Erika; Sundqvist, Martin; Wegener, Matthias; Lidén, Mats; Cajander, Sara
• Is Part Of: Infectious diseases. Volume 54:Issue 6(2022)
• Page Start: 431
• Page End: 440
• Publication Date: 2022-06-03
• Subjects: COVID-19 -- Sars-cov-2 -- computed tomography -- cycle threshold -- outcome; Communicable diseases -- Periodicals; Communicable Diseases -- Periodicals; Communicable diseases; Periodicals; 616.9
• DOI: 10.1080/23744235.2022.2035428
• Languages: English
• ISSNs: 2374-4235

Abstract

Abstract: Background: COVID-19 has a most variable prognosis. Several risk factors for an unfavourable outcome have been identified including extensive lung involvement on chest CT and high viral load estimated by RT-PCR cycle threshold (Ct) values. We investigated Ct value for outcome prediction, relation between Ct value and extent of lung involvement on chest CT and the combination of Ct value and chest CT lung involvement to predict outcome in COVID-19. Methods: Population-based retrospective study on all patients ( n = 286) hospitalised for COVID-19 in Örebro Region, Sweden, between 1 March and 31 August 2020. Nasopharyngeal samples and chest CT at hospital admission were evaluated in relation to outcome of COVID-19. Results: Both Ct value and chest CT lung involvement were independently associated with risk for ICU admission or death. Lung involvement was superior as a single parameter, but addition of Ct value increased the prediction performance. Ct value was especially useful to identify patients with high risk for severe disease despite limited lung involvement. Conclusions: The addition of RT-PCR Ct value to the assessment of lung involvement on chest CT adds valuable prognostic information in COVID-19. We believe that this information can be used to support clinical decision-making when managing COVID-19 patients.