Literature DB >> 33196593

Diagnostic Yield of Computed Tomography for the Identification of Coronavirus Disease 2019 Using Repeated Reverse Transcriptase Polymerase Chain Reaction Testing or Confirmed True-Negative State as Reference Standard: Systematic Review and Meta-Analysis.

Davide Bellini1, Nicola Panvini1, Iacopo Carbone1, Marco Rengo1, Carolyn L Wang2, Achille Mileto2.   

Abstract

OBJECTIVE: The aim of this study was to perform a meta-analysis assessing the diagnostic yield of computed tomography (CT) for the identification of coronavirus disease 2019 (COVID-19) using repeated reverse transcriptase polymerase chain reaction testing or confirmed true-negative state as reference standard.
METHODS: In May 2020, we interrogated the MEDLINE, Embase, and CENTRAL databases. Pooled sensitivity, specificity, and diagnostic odds ratios of CT for COVID-19 identification were computed. Cumulative positive predictive value (PPV) and negative predictive value, stratified by disease prevalence, were calculated.
RESULTS: Ten articles were included (1332 patients). Pooled sensitivity, specificity, and summary diagnostic odds ratio of CT were 82% [95% confidence interval (CI), 79%-84%], 68% (95% CI, 65%-71%), and 18 (95% CI, 9.8-32.8). The PPV and negative predictive value were 54% (95% CI, 30%-77%) and 94% (95% CI, 88%-99%) at a COVID-19 prevalence lower than 40%, and 80% (95% CI, 62%-91%) and 77% (95% CI, 68%-85%) at a prevalence higher than 40%.
CONCLUSION: CT yields higher specificity and PPV, albeit lower sensitivity, than previously reported for the identification of COVID-19.

Entities:  

Mesh:

Year:  2020        PMID: 33196593     DOI: 10.1097/RCT.0000000000001105

Source DB:  PubMed          Journal:  J Comput Assist Tomogr        ISSN: 0363-8715            Impact factor:   1.826


  2 in total

1.  Radiographers and COVID-19 pneumonia: Diagnostic performance using CO-RADS.

Authors:  S Vicini; N Panvini; D Bellini; M Rengo; M Ciotola; M De Vivo; C Gambaretto; V Caldon; S Panno; C Del Borgo; I Carbone
Journal:  Radiography (Lond)       Date:  2021-04-30

2.  Using artificial intelligence to improve the diagnostic efficiency of pulmonologists in differentiating COVID-19 pneumonia from community-acquired pneumonia.

Authors:  Erdal İn; Ayşegül A Geçkil; Gürkan Kavuran; Mahmut Şahin; Nurcan K Berber; Mutlu Kuluöztürk
Journal:  J Med Virol       Date:  2022-05-02       Impact factor: 20.693

  2 in total

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