Evidence map›Paper›PMID 41327196›Full record

ArticleBMC pulmonary medicine2025

Consolidation-to-ground-glass opacity ratio on chest CT as a prognostic marker for critical outcomes in COVID-19: a retrospective cohort study.

Hiromu Tanaka, Naoya Tanabe, Shotaro Chubachi, Tomoki Maetani, Yusuke Shiraishi, Ho Namkoong, Takanori Asakura, Takashi Shimada, Shuhei Azekawa, Shiro Otake and 24 more

Abstract readMulticenter Study
In one paragraph

Article in BMC pulmonary medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

34 authors.

Hiromu Tanaka *Department of Medicine, Division of Pulmonary Medicine, Keio University School of Medicine, Tokyo, Japan.
Naoya Tanabe *Department of Respiratory Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan.
Shotaro ChubachiDepartment of Medicine, Division of Pulmonary Medicine, Keio University School of Medicine, Tokyo, Japan. bachibachi472000@keio.jp.
Tomoki MaetaniDepartment of Respiratory Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan.
Yusuke ShiraishiDepartment of Respiratory Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan.
Ho NamkoongDepartment of Infectious Diseases, Keio University School of Medicine, Tokyo, Japan.
Takanori AsakuraDepartment of Medicine, Division of Pulmonary Medicine, Keio University School of Medicine, Tokyo, Japan.
Takashi ShimadaDepartment of Medicine, Division of Pulmonary Medicine, Keio University School of Medicine, Tokyo, Japan.
Shuhei AzekawaDepartment of Medicine, Division of Pulmonary Medicine, Keio University School of Medicine, Tokyo, Japan.
Shiro OtakeDepartment of Medicine, Division of Pulmonary Medicine, Keio University School of Medicine, Tokyo, Japan.
Kensuke NakagawaraDepartment of Medicine, Division of Pulmonary Medicine, Keio University School of Medicine, Tokyo, Japan.
Takahiro FukushimaDepartment of Medicine, Division of Pulmonary Medicine, Keio University School of Medicine, Tokyo, Japan.
Mayuko WataseDepartment of Medicine, Division of Pulmonary Medicine, Keio University School of Medicine, Tokyo, Japan.
Hideki TeraiDepartment of Medicine, Division of Pulmonary Medicine, Keio University School of Medicine, Tokyo, Japan.
Mamoru SasakiDepartment of Internal Medicine, JCHO (Japan Community Health care Organization) Saitama Medical Center, Saitama, Japan.
Soichiro UedaDepartment of Internal Medicine, JCHO (Japan Community Health care Organization) Saitama Medical Center, Saitama, Japan.
Yukari KatoDepartment of Respiratory Medicine, Juntendo University Faculty of Medicine and Graduate School of Medicine, Tokyo, Japan.
Norihiro HaradaDepartment of Respiratory Medicine, Juntendo University Faculty of Medicine and Graduate School of Medicine, Tokyo, Japan.
Shoji SuzukiDepartment of Pulmonary Medicine, Saitama City Hospital, Saitama, Japan.
Shuichi YoshidaDepartment of Pulmonary Medicine, Saitama City Hospital, Saitama, Japan.
Hiroki TatenoDepartment of Pulmonary Medicine, Saitama City Hospital, Saitama, Japan.
Yoshitake YamadaDepartment of Radiology, Keio University School of Medicine, Tokyo, Japan.
Masahiro JinzakiDepartment of Radiology, Keio University School of Medicine, Tokyo, Japan.
Toyohiro HiraiDepartment of Respiratory Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan.
Yukinori OkadaDepartment of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan.
Ryuji KoikeHealth Science Research and Development Center (HeRD), Institute of Science Tokyo, Tokyo, Japan.
Makoto IshiiDepartment of Medicine, Division of Pulmonary Medicine, Keio University School of Medicine, Tokyo, Japan.
Naoki HasegawaDepartment of Infectious Diseases, Keio University School of Medicine, Tokyo, Japan.
Akinori KimuraInstitute of Research, Institute of Science Tokyo, Tokyo, Japan.
Seiya ImotoDivision of Health Medical Intelligence, Human Genome Center, the Institute of Medical Science, the University of Tokyo, Tokyo, Japan.
Satoru MiyanoM&D Data Science Center, Institute of Science Tokyo, Tokyo, Japan.
Seishi OgawaDepartment of Pathology and Tumor Biology, Kyoto University, Kyoto, Japan.
Takanori KanaiDepartment of Medicine, Division of Gastroenterology and Hepatology, Keio University School of Medicine, Tokyo, Japan.
Koichi FukunagaDepartment of Medicine, Division of Pulmonary Medicine, Keio University School of Medicine, Tokyo, Japan.

Funding

Japan Agency for Medical Research and Development JP20fk0108415Japan Agency for Medical Research and Development JP20nk0101612Japan Agency for Medical Research and Development JP21fk0108563Japan Agency for Medical Research and Development JP21fk0108573Japan Agency for Medical Research and Development JP21jk0210034Japan Agency for Medical Research and Development JP21km0405211Japan Agency for Medical Research and Development JP21wm0325031Japan Agency for Medical Research and Development JP22fk0108513Japan Science and Technology Corporation JPMJCR20H2Japan Science and Technology Corporation JPMJPR21R7Ministry of Health, Labour and Welfare 20CA2054
6 · The paper itself

Abstract

backgroundComputed tomography (CT)-based quantification of coronavirus disease 2019 (COVID-19) pneumonia is widely performed, and total pneumonia volume, ground-glass opacity (GGO), and consolidation affect disease severity. However, there is insufficient information on how consolidation to GGO (C/G) ratio correlates with clinical characteristics including disease severity and complications in COVID-19 patients.

methodsThis retrospective cohort study included 1,194 hospitalized patients with COVID-19 from four member hospitals of the Japan COVID-19 Task Force. Critical outcomes were defined as conditions requiring high-flow oxygen or invasive mechanical ventilation, or death. Patients were divided into two groups based on %pneumonia (percentage of pneumonia volume divided by total lung volume) using receiver operating characteristic curve, and those with high %pneumonia were further divided into two groups based on C/G ratio. Critical outcomes and complications were then compared between high and low C/G ratio groups.

resultsThe optimal cutoff value of %pneumonia to predict critical outcomes was 17.1%, classifying the included patients into low (Group 1, n = 900) and high (n = 294) %pneumonia groups. The optimal cutoff value of C/G ratio was 0.202, classifying patients in the high %pneumonia group into two groups: low (Group 2, n = 192) and high C/G (Group 3, n = 102) ratio groups. The incidence of critical outcomes was stair-step high in all three groups (2.1%, 21.4%, and 37.3%, respectively). Multivariable analysis revealed an independent relationship between C/G ratio and critical outcomes from other known risk factors (adjusted odds ratio: 1.92, 95% confidential interval: 1.03-3.59, P = 0.040). Group 3 also showed significantly higher serum C-reactive protein (Group 1: 2.96 mg/dL, Group 2: 8.90 mg/dL, Group 3: 11.4 mg/dL) and procalcitonin (Group 1: 0.16 ng/mL, Group 2: 0.25 ng/mL, Group 3: 1.19 ng/mL) levels and incidence of bacterial infection (Group 1: 5.6%, Group 2: 10.4%, Group 3: 20.3%), compared with other groups.

conclusionsCT-density analysis of COVID-19 pneumonia in a large patient population showed that C/G ratio was a significant predictor of critical outcomes and useful for prognosis evaluation.

Indexed as

COVID-19LungTomography, X-Ray ComputedAgedAged, 80 and overFemaleHumansJapanMaleMiddle AgedPrognosisRespiration, ArtificialRetrospective StudiesROC CurveSARS-CoV-2Severity of Illness IndexBiomarkerConsolidation-to-ground glass opacity ratioCoronavirus disease 2019CT density analysisPrognostic prediction

Identifiers

PMID41327196
PMCPMC12667167

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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.