Selected article for: "disease progression and lobe involvement"

Author: Adams, Hugo J.A.; Kwee, Thomas C.; Yakar, Derya; Hope, Michael D.; Kwee, Robert M.
Title: Chest CT imaging signature of COVID-19 infection: in pursuit of the scientific evidence
  • Cord-id: 5x3lyuuf
  • Document date: 2020_6_25
  • ID: 5x3lyuuf
    Snippet: Abstract Background Chest computed tomography (CT) may be used for the diagnosis of Corona virus disease 2019 (COVID-19), but clear scientific evidence is lacking. Therefore, we systematically reviewed and meta-analyzed the chest CT imaging signature of COVID-19. Methods A systematic literature search was performed for original studies on chest CT findings in patients with COVID-19. Methodological quality of studies was evaluated. Pooled prevalences of chest CT findings were calculated using a r
    Document: Abstract Background Chest computed tomography (CT) may be used for the diagnosis of Corona virus disease 2019 (COVID-19), but clear scientific evidence is lacking. Therefore, we systematically reviewed and meta-analyzed the chest CT imaging signature of COVID-19. Methods A systematic literature search was performed for original studies on chest CT findings in patients with COVID-19. Methodological quality of studies was evaluated. Pooled prevalences of chest CT findings were calculated using a random effects model in case of between-study heterogeneity (predefined as I2≥50), otherwise a fixed effects model was used. Results Twenty-eight studies were included. Median number of COVID-19 patients per study was 124 (range 50-476), comprising a total of 3,466 patients. Median prevalence of symptomatic patients was 99% (range >76.3%-100%). 27/28 (96%) of studies had a retrospective design. Methodological quality concerns were present with either risk of or actual referral bias (13 studies), patient spectrum bias (8 studies), disease progression bias (26 studies), observer variability bias (27 studies), and test review bias (14 studies). Pooled prevalence was 10.6% for normal chest CT findings. Pooled prevalences were 90.0% for posterior predilection, 81.0% for ground-glass opacity, 75.8% for bilateral abnormalities, 73.1% for left lower lobe involvement, 72.9% for vascular thickening, and 72.2% for right lower lobe involvement. Pooled prevalences were 5.2% for pleural effusion, 5.1% for lymphadenopathy, 4.1% for airway secretions/tree-in-bud sign, 3.6% for central lesion distribution, 2.7% for pericardial effusion, and 0.7% for cavitation/cystic changes. Pooled prevalences of other CT findings ranged between 10.5%-63.2%. Conclusion Studies on chest CT findings in COVID-19 suffer from methodological quality concerns. More high-quality research is necessary to establish diagnostic CT criteria for COVID-19. Based on the available evidence that requires cautious interpretation, several chest CT findings appear to be suggestive of COVID-19, but normal chest CT findings do not exclude COVID-19, even not in symptomatic patients.

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