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2020 ; 27
(7
): 910-921
Nephropedia Template TP
gab.com Text
Twit Text FOAVip
Twit Text #
English Wikipedia
CT Manifestations and Clinical Characteristics of 1115 Patients with Coronavirus
Disease 2019 (COVID-19): A Systematic Review and Meta-analysis
#MMPMID32505599
Wan S
; Li M
; Ye Z
; Yang C
; Cai Q
; Duan S
; Song B
Acad Radiol
2020[Jul]; 27
(7
): 910-921
PMID32505599
show ga
RATIONALE AND OBJECTIVES: We aimed to assess the prevalence of significant
computed tomographic(CT) manifestations and describe some notable features based
on chest CT images, as well as the main clinical features of patients with
coronavirus disease 2019(COVID-19). MATERIALS AND METHODS: A systematic
literature search of PubMed, EMBASE, the Cochrane Library, and Web of Science was
performed to identify studies assessing CT features, clinical, and laboratory
results of COVID-19 patients. A single-arm meta-analysis was conducted to obtain
the pooled prevalence and 95% confidence interval (95% CI). RESULTS: A total of
14 articles (including 1115 patients) based on chest CT images were retrieved. In
the lesion patterns on chest CTs, we found that pure ground-glass opacities (GGO)
(69%, 95% CI 58-80%), consolidation (47%, 35-60%) and "air bronchogram sign"
(46%, 25-66%) were more common than the atypical lesion of "crazy-paving pattern"
(15%, 8-22%). With regard to disease extent and involvement, 70% (95% CI 46-95%)
of cases showed a location preference for the right lower lobe, 65% (58-73%) of
patients presented with ?3 lobes involvement, and meanwhile, 42% (32-53%) of
patients had involvement of all five lobes, while 67% (55-78%) of patients showed
a predominant peripheral distribution. An understanding of some important CT
features might be helpful for medical surveillance and management. In terms of
clinical features, muscle soreness (21%, 95% CI 15-26%) and diarrhea (7%, 4-10%)
were minor symptoms compared to fever (80%, 74-87%) and cough (53%, 33-72%).
CONCLUSION: Chest CT manifestations in patients with COVID-19, as well as its
main clinical characteristics, might be helpful in disease evolution and
management.