SynthesisJournal of medical imaging and radiation sciences2023
Computed tomography severity score as a predictor of disease severity and mortality in COVID-19 patients: A systematic review and meta-analysis.
Synthesis in Journal of medical imaging and radiation sciences, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 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
8 citing papers in PubMed.
- Diagnostic Usefulness of SP-D, CCL2/MCP-1, and IL-18 in Assessing Respiratory Function and Risk of Pulmonary Fibrosis in COVID-19 Patients.International journal of molecular sciences · 2026Article
- Phenotypic Alterations of CD8+ and CD8- CD56+ NK Cell Subsets in Moderate and Severe COVID-19 Disease.Journal of immunology research · 2026Article
- Forecasting COVID-19 inpatient mortality using fundamental parameters in resource-constrained settings: a countrywide multi-center cohort study.BMC infectious diseases · 2025Article
- Validation of Global Definition of Acute Respiratory Distress Syndrome in COVID-19 Patients: A Retrospective Study.Indian journal of critical care medicine : peer-reviewed, official publication of Indian Society of Critical Care Medicine · 2025Article
- Safe, Smart, and Scalable: A Prospective Multicenter Study on Low-Dose CT and CTSS for Emergency Risk Stratification in COVID-19.Journal of clinical medicine · 2025Article
- The severity assessment and nucleic acid turning-negative-time prediction in COVID-19 patients with COPD using a fused deep learning model.BMC pulmonary medicine · 2024Article
- Association of chest computed tomography severity score at ICU admission and respiratory outcomes in critically ill COVID-19 patients.PloS one · 2024Article
- Can there be calm during a cytokine storm? Immune checkpoint pathways affecting the severity of COVID-19 disease.Frontiers in microbiology · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundPrediction of outcomes in severe COVID-19 patients using chest computed tomography severity score (CTSS) may enable more effective clinical management and early, timely ICU admission. We conducted a systematic review and meta-analysis to determine the predictive accuracy of the CTSS for disease severity and mortality in severe COVID-19 subjects.
methodsThe electronic databases PubMed, Google Scholar, Web of Science, and the Cochrane Library were searched to find eligible studies that investigated the impact of CTSS on disease severity and mortality in COVID-19 patients between 7 January 2020 and 15 June 2021. Two independent authors looked into the risk of bias using the Quality in Prognosis Studies (QUIPS) tool.
resultsSeventeen studies involving 2788 patients reported the predictive value of CTSS for disease severity. The pooled sensitivity, specificity, and summary area under the curve (sAUC) of CTSS were 0.85 (95% CI 0.78-0.90, I DISCUSSION: Early prediction of prognosis is needed to deliver the better care to patients and stratify them as soon as possible. Because different CTSS thresholds have been reported in various studies, clinicians are still determining whether CTSS thresholds should be used to define disease severity and predict prognosis.
conclusionEarly prediction of prognosis is needed to deliver optimal care and timely stratification of patients. CTSS has strong discriminating power for the prediction of disease severity and mortality in patients with COVID-19.
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.