About: Computed tomography surveillance helps tracking COVID-19 outbreak

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About: Computed tomography surveillance helps tracking COVID-19 outbreak Goto Sponge NotDistinct Permalink

An Entity of Type : schema:ScholarlyArticle, within Data Space : covidontheweb.inria.fr associated with source document(s)

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	Computed tomography surveillance helps tracking COVID-19 outbreak
Creator	Aoki, Shigeki Horioka, Nobuhiko Imai, Yutaka Ishigami, Kousei Kakihara, Daisuke Kawata, Yusuke Machitori, Akihiro Nishie, Akihiro Noguchi, Tomoyuki Kousei, · Noguchi, ·
Source	Medline; PMC
abstract	PURPOSE: To reveal that a computed tomography surveillance program (CT-surveillance) could demonstrate the epidemiologic features of COVID-19 infection and simultaneously investigate the type and frequency of CT findings using clinical CT data. MATERIALS AND METHODS: We targeted individuals with possible CT findings of viral pneumonia. Using an online questionnaire, we asked Japanese board-certified radiologists to register their patients’ information including patient age and sex, the CT examination date, the results of PCR test for COVID-19 infection, CT findings, and the postal code of the medical institution that performed the CT. We compared the diurnal patient number and the cumulative regional distribution map of registrations in CT-surveillance to those of the PCR-positive patient surveillance (PCR-surveillance). RESULTS: A total of 637 patients was registered from January 1 to April 17, 2020 for CT-surveillance. Their PCR test results were positive (n = 62.5–398%), negative (n = 8.9–57%), unknown (n = 26.2–167%), and other disease (n = 2.4–15%). An age peak at 60–69 years and male dominance were observed in CT-surveillance. The most common CT finding was bilaterally distributed ground-glass opacities. The diurnal number and the cumulative regional distribution map by CT-surveillance showed tendencies that were similar to those revealed by PCR-surveillance. CONCLUSION: Using clinical CT data, CT-surveillance program delineated the epidemiologic features of COVID-19 infection.
has issue date	2020-08-07(xsd:dateTime)
bibo:doi	10.1007/s11604-020-01026-z
bibo:pmid	32766927
has license	no-cc
sha1sum (hex)	8931a667486c19e796f098e775023957fbc14219
schema:url	https://doi.org/10.1007/s11604-020-01026-z
resource representing a document's title	Computed tomography surveillance helps tracking COVID-19 outbreak
has PubMed Central identifier	PMC7410527
has PubMed identifier	32766927
schema:publication	Jpn J Radiol
resource representing a document's body	covid:8931a667486c19e796f098e775023957fbc14219#body_text
is schema:about of	named entity 'cumulative' named entity 'patients' named entity 'age' named entity 'COVID-19' named entity 'patient' named entity 'Computed tomography' named entity 'DATA' named entity 'JANUARY' named entity 'PCR' named entity 'FEATURES' named entity 'SIMULTANEOUSLY' named entity 'INDIVIDUALS' named entity 'EPIDEMIOLOGIC' named entity 'SEX' named entity 'PEAK' named entity 'DELINEATED' named entity 'FREQUENCY' named entity 'REVEALED' named entity 'infection' named entity 'demonstrate' named entity 'diurnal' named entity 'online questionnaire' named entity 'regional' named entity 'institution' named entity 'test' named entity 'targeted individuals' named entity 'patient' named entity 'number' named entity 'epidemiologic' named entity 'questionnaire' named entity 'infection' named entity 'PCR test' named entity 'Computed tomography' named entity 'postal code' named entity 'examining physicians' named entity 'medical institution' named entity 'PCR test' named entity 'PCR test' named entity 'PCR' named entity 'postal code' named entity 'COVID' named entity 'Japan' named entity 'PCR' named entity 'lung' named entity 'statistical analyses' named entity 'ground-glass opacities' named entity 'lung' named entity 'COVID-19' named entity 'lung' named entity 'oxygen saturation' named entity 'medical treatment' named entity 'infection' named entity 'radiologist' named entity 'Japan' named entity 'radiologists' named entity 'bronchial' named entity 'PCR' named entity 'COVID' named entity 'Japan' named entity 'incubation period' named entity 'Ethics' named entity 'correlation' named entity 'PCR' named entity '47 prefectures' named entity 'Japan' named entity 'infection' named entity 'epidemic curve' named entity '47 prefectures' named entity 'PCR' named entity 'Japanese holidays' named entity 'diurnal'

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