ArticleAging2021
A COVID-19 risk score combining chest CT radiomics and clinical characteristics to differentiate COVID-19 pneumonia from other viral pneumonias.
Article in Aging, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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.
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.
Who cites it
9 citing papers in PubMed.
- CT-based radiomics nomogram for distinguishingTranslational pediatrics · 2026Article
- An Intelligent System for Classifying Patient Complaints Using Machine Learning and Natural Language Processing: Development and Validation Study.Journal of medical Internet research · 2025Article
- A radiomics model utilizing CT for the early detection and diagnosis of severe community-acquired pneumonia.BMC medical imaging · 2024Article
- Radiomics-Assisted Computed Tomography-Based Analysis to Evaluate Lung Morphology Characteristics after Congenital Diaphragmatic Hernia.Journal of clinical medicine · 2023Article
- Multicenter study evaluating novel multi-specimen pooling assay for the detection of SARS-CoV-2: High sensitivity and high throughput testing.Journal of microbiology, immunology, and infection = Wei mian yu gan ran za zhi · 2022Article
- CT-based radiomic nomogram for predicting the severity of patients with COVID-19.European journal of medical research · 2022Article
- Prediction of radiation-induced acute skin toxicity in breast cancer patients using data encapsulation screening and dose-gradient-based multi-region radiomics technique: A multicenter study.Frontiers in oncology · 2022Article
- Article
- Radiomics Is Effective for Distinguishing Coronavirus Disease 2019 Pneumonia From Influenza Virus Pneumonia.Frontiers in public health · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
23 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
With the continued transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) throughout the world, identification of highly suspected COVID-19 patients remains an urgent priority. In this study, we developed and validated COVID-19 risk scores to identify patients with COVID-19. In this study, for patient-wise analysis, three signatures, including the risk score using radiomic features only, the risk score using clinical factors only, and the risk score combining radiomic features and clinical variables, show an excellent performance in differentiating COVID-19 from other viral-induced pneumonias in the validation set. For lesion-wise analysis, the risk score using three radiomic features only also achieved an excellent AUC value. In contrast, the performance of 130 radiologists based on the chest CT images alone without the clinical characteristics included was moderate as compared to the risk scores developed. The risk scores depicting the correlation of CT radiomics and clinical factors with COVID-19 could be used to accurately identify patients with COVID-19, which would have clinically translatable diagnostic and therapeutic implications from a precision medicine perspective.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.