Evidence map›Paper›PMID 37871048›Full record

ArticlePloS one2023

Quantitative analysis of chest computed tomography of COVID-19 pneumonia using a software widely used in Japan.

Minako Suzuki, Yoshimi Fujii, Yurie Nishimura, Kazuma Yasui, Hidefumi Fujisawa

Abstract read
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Article in PloS one, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

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0 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Minako SuzukiDepartment of Radiology, Showa University Northern Yokohama Hospital, Yokohama, Kanagawa, Japan.ORCID 0009-0009-9815-0763
Yoshimi FujiiDepartment of Radiology, Fujisawa City Hospital, Fujisawa, Kanagawa, Japan.
Yurie NishimuraDepartment of Radiology, Fujisawa City Hospital, Fujisawa, Kanagawa, Japan.
Kazuma YasuiDepartment of Radiology, Fujisawa City Hospital, Fujisawa, Kanagawa, Japan.
Hidefumi FujisawaDepartment of Radiology, Showa University Northern Yokohama Hospital, Yokohama, Kanagawa, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study aimed to determine the optimal conditions to measure the percentage of the area considered as pneumonia (pneumonia volume ratio [PVR]) and the computed tomography (CT) score due to coronavirus disease 2019 (COVID-19) using the Ziostation2 image analysis software (Z2; Ziosoft, Tokyo, Japan), which is popular in Japan, and to evaluate its usefulness for assessing the clinical severity. We included 53 patients (41 men and 12 women, mean age: 61.3 years) diagnosed with COVID-19 using polymerase chain reaction who had undergone chest CT and were hospitalized between January 2020 and January 2021. Based on the COVID-19 infection severity, the patients were classified as mild (n = 38) or severe (n = 15). For 10 randomly selected samples, the PVR and CT scores by Z2 under different conditions and the visual simple PVR and CT scores were compared. The conditions with the highest statistical agreement were determined. The usefulness of the clinical severity assessment based on the PVR and CT scores using Z2 under the determined conditions was statistically evaluated. The best agreement with the visual measurement was achieved by the Z2 measurement condition of ≥-600 HU. The areas under the receiver operating characteristic curves, Youden's index, and the sensitivity, specificity, and p-values of the PVR and CT scores by Z2 were as follows: PVR: 0.881, 18.69, 66.7, 94.7, and <0.001; CT score: 0.77, 7.5, 40, 74, and 0.002, respectively. We determined the optimal condition for assessing the PVR of COVID-19 pneumonia using Z2 and demonstrated that the AUC of the PVR was higher than that of CT scores in the assessment of clinical severity. The introduction of new technologies is time-consuming and expensive; our method has high clinical utility and can be promptly used in any facility where Z2 has been introduced.

Indexed as

COVID-19PneumoniaFemaleHumansJapanLungMaleMiddle AgedRetrospective StudiesSARS-CoV-2SoftwareTomography, X-Ray Computed

Identifiers

PMID37871048
PMCPMC10593239

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.