ArticleKorean journal of radiology2020
Prognostic Implication of Volumetric Quantitative CT Analysis in Patients with COVID-19: A Multicenter Study in Daegu, Korea.
Article in Korean journal of radiology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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18 citing papers in PubMed.
- CT-derived quantitative imaging biomarkers for hypoxemia risk in repeated lung resection: a retrospective study.BMC medical imaging · 2026Article
- Quantitative lung CT indicators have good predictive ability for hypoxemia during one-lung ventilation in radical resection for lung cancer.Journal of anesthesia · 2025Article
- Prediction of oxygen supplementation by a deep-learning model integrating clinical parameters and chest CT images in COVID-19.Japanese journal of radiology · 2023Article
- Quantitative chest computed tomography combined with plasma cytokines predict outcomes in COVID-19 patients.Heliyon · 2022Article
- How to Clearly and Accurately Report Odds Ratio and Hazard Ratio in Diagnostic Research Studies?Korean journal of radiology · 2022Article
- Predefined and data driven CT densitometric features predict critical illness and hospital length of stay in COVID-19 patients.Scientific reports · 2022Article
- Article
- Quantitative chest CT combined with plasma cytokines predict outcomes in COVID-19 patients.medRxiv : the preprint server for health sciences · 2021Article
- Mistakes to Avoid for Accurate and Transparent Reporting of Survival Analysis in Imaging Research.Korean journal of radiology · 2021Article
- Machine Learning-Based Prediction of COVID-19 Severity and Progression to Critical Illness Using CT Imaging and Clinical Data.Korean journal of radiology · 2021Article
- Prediction of Patient Management in COVID-19 Using Deep Learning-Based Fully Automated Extraction of Cardiothoracic CT Metrics and Laboratory Findings.Korean journal of radiology · 2021Article
- Automated CT Lung Density Analysis of Viral Pneumonia and Healthy Lungs Using Deep Learning-Based Segmentation, Histograms and HU Thresholds.Diagnostics (Basel, Switzerland) · 2021Article
- Prognostic Implications of CT Feature Analysis in Patients with COVID-19: a Nationwide Cohort Study.Journal of Korean medical science · 2021Article
- Value of quantitative analysis in lung computed tomography in patients severely ill with COVID-19.PloS one · 2021Article
- What's New in theKorean journal of radiology · 2021Article
- Establishment of a Nationwide Korean Imaging Cohort of Coronavirus Disease 2019.Journal of Korean medical science · 2020Article
- An Assessment of the Novel COVISTRESS Questionnaire: COVID-19 Impact on Physical Activity, Sedentary Action and Psychological Emotion.Journal of clinical medicine · 2020Article
- Predictive criteria of severe cases in COVID-19 patients of early stage: A retrospective observational study.Journal of clinical laboratory analysis · 2020Observational
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13 authors.
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Abstract
objectiveLung segmentation using volumetric quantitative computed tomography (CT) analysis may help predict outcomes of patients with coronavirus disease (COVID-19). The aim of this study was to investigate the relationship between CT volumetric quantitative analysis and prognosis in patients with COVID-19. MATERIALS AND
methodsCT images from patients diagnosed with COVID-19 from February 18 to April 15, 2020 were retrospectively analyzed. CT with a negative finding, failure of quantitative analysis, or poor image quality was excluded. CT volumetric quantitative analysis was performed by automated volumetric methods. Patients were stratified into two risk groups according to CURB-65: mild (score of 0-1) and severe (2-5) pneumonia. Outcomes were evaluated according to the critical event-free survival (CEFS). The critical events were defined as mechanical ventilator care, ICU admission, or death. Multivariable Cox proportional hazards analyses were used to evaluate the relationship between the variables and prognosis.
resultsEighty-two patients (mean age, 63.1 ± 14.5 years; 42 females) were included. In the total cohort, male sex (hazard ratio [HR], 9.264; 95% confidence interval [CI], 2.021-42.457;
conclusionCRP in the mild pneumonia group; NALP and NALPV in the severe pneumonia group; and sex, CRP, and CALP in the total cohort were independently associated with CEFS in patients with COVID-19.
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