ArticleEuropean journal of radiology2020
Can CT performed in the early disease phase predict outcome of patients with COVID 19 pneumonia? Analysis of a cohort of 64 patients from Germany.
Article in European journal of radiology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 1 of them a synthesis that pooled it.
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Who cites it
16 citing papers in PubMed, 1 synthesis or guideline pooled it, 33 citations in OpenAlex.
- Digital imaging, technologies and artificial intelligence applications during COVID-19 pandemic.Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society · 2021Pooled it
- Predicting Severe Respiratory Failure in Patients with COVID-19: A Machine Learning Approach.Journal of clinical medicine · 2024Article
- [Correlation between comorbidities and thoracic CT manifestations of COVID-19 pneumonia].Medizinische Klinik, Intensivmedizin und Notfallmedizin · 2024Article
- Doubts and concerns about COVID-19 uncertainties on imaging data, clinical score, and outcomes.BMC pulmonary medicine · 2023Article
- Quantitative evaluation of CT scan images to determinate the prognosis of COVID-19 patient using deep learning.European journal of translational myology · 2023Article
- Prognostic findings for ICU admission in patients with COVID-19 pneumonia: baseline and follow-up chest CT and the added value of artificial intelligence.Emergency radiology · 2022Review
- CT of Post-Acute Lung Complications of COVID-19.Radiology · 2021Review
- CT Examinations for COVID-19: A Systematic Review of Protocols, Radiation Dose, and Numbers Needed to Diagnose and Predict.Taehan Yongsang Uihakhoe chi · 2021Article
- Automated quantitative thin slice volumetric low dose CT analysis predicts disease severity in COVID-19 patients.Clinical imaging · 2021Article
- The Usefulness of Chest CT Imaging in Patients With Suspected or Diagnosed COVID-19: A Review of Literature.Chest · 2021Review
- An analysis of the radiological factors associated with respiratory failure in COVID-19 pneumonia and the CT features among different age categories.Japanese journal of radiology · 2021Article
- Mediastinal lymphadenopathy may predict 30-day mortality in patients with COVID-19.Clinical imaging · 2021Article
- Robust prediction of mortality of COVID-19 patients based on quantitative, operator-independent, lung CT densitometry.Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB) · 2021Article
- Prognostic value of lung ultrasound and its link with inflammatory biomarkers in patients with SARS-CoV-2 infection.Respiratory medicine and research · 2021Observational
- Prognostic value of CT integrated with clinical and laboratory data during the first peak of the COVID-19 pandemic in Northern Italy: A nomogram to predict unfavorable outcome.European journal of radiology · 2021Article
- Prediction of disease progression in patients with COVID-19 by artificial intelligence assisted lesion quantification.Scientific reports · 2020Article
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Authors and funding
11 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeThe aim of this study was to investigate if CT performed in the early disease phase can predict the course of COVID-19 pneumonia in a German cohort.
methodAll patients with RT-PCR proven COVID-19 pneumonia and chest CT performed within 10 days of symptom onset between March 1st and April 15th 2020 were retrospectively identified from two tertiary care hospitals. 12 CT features, their distribution in the lung and the global extent of opacifications were evaluated. For analysis of prognosis two compound outcomes were defined: positive outcome was defined as either discharge or regular ward care; negative outcome was defined as need for mechanical ventilation, treatment on intensive care unit, extracorporeal membrane oxygenation or death. Follow-up was performed until June 19th. For statistical analysis uni- und multivariable logistic regression models were calculated.
results64 patients were included in the study. By univariable analysis the following parameters predicted a negative outcome: consolidation (p = 0.034), crazy paving (p = 0.004), geographic shape of opacification (p = 0.022), dilatation of bronchi (p = 0.002), air bronchogram (p = 0.013), vessel enlargement (p = 0.014), pleural effusion (p = 0.05), bilateral disease (p = 0.004), involvement of the upper lobes (p = 0.004, p = 0.015) or the right middle lobe (p < 0.001) and severe extent of opacifications (p = 0.002). Multivariable analysis revealed crazy paving and severe extent of parenchymal involvement to be independently predictive for a poor outcome.
conclusionsEasy to assess CT features in the early phase of disease independently predicted an adverse outcome of patients with COVID-19 pneumonia.
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