Dataset Information

Chest CT severity score and radiological patterns as predictors of disease severity, ICU admission, and viral positivity in COVID-19 patients.

ABSTRACT:

Background

Chest computed tomography (CT) is a useful tool for the diagnosis of coronavirus disease-2019 (COVID-19), although its exact value for predicting critical illness remains unclear. This study evaluated the efficacy of chest CT to predict disease progression, pulmonary complications, and viral positivity duration.

Methods

A single-center cohort study was conducted by consecutively including hospitalized patients with confirmed COVID-19. The chest CT patterns were described and a total severity score was calculated. The predictive accuracy of the severity score was evaluated using the receiver operating characteristic analysis, while a Cox proportional hazards regression model was implemented to identify the radiological features that are linked to prolonged duration of viral positivity.

Results

Overall, 42 patients were included with 10 of them requiring intensive care unit admission. The most common lesions were ground glass opacities (92.9%), consolidation (66.7%), and crazy-paving patterns (61.9%). The total severity score significantly correlated with inflammatory and respiratory distress markers, as well as with admission CURB-65 and PSI/PORT scores. It was estimated to predict critical illness with a sensitivity and specificity of 75% and 70%, respectively. Time-to-event analysis indicated that patients without ground-glass opacities presented significantly shorter median viral positivity (16 vs. 27 days).

Conclusions

Chest CT severity score positively correlates with markers of COVID-19 severity and presents promising efficacy in predicting critical illness. It is suggested that ground-glass opacities are linked to prolonged viral positivity. Further studies should confirm the efficacy of the severity score and elucidate the long-term pulmonary effects of COVID-19.

SUBMITTER: Bellos I

PROVIDER: S-EPMC7972804 | biostudies-literature | 2021 Jul

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Chest CT severity score and radiological patterns as predictors of disease severity, ICU admission, and viral positivity in COVID-19 patients.

Bellos Ioannis I Tavernaraki Kyriaki K Stefanidis Konstantinos K Michalopoulou Olympia O Lourida Giota G Korompoki Eleni E Thanou Ioanna I Thanos Loukas L Pefanis Angelos A Argyraki Aikaterini A

Respiratory investigation 20210319 4

<h4>Background</h4>Chest computed tomography (CT) is a useful tool for the diagnosis of coronavirus disease-2019 (COVID-19), although its exact value for predicting critical illness remains unclear. This study evaluated the efficacy of chest CT to predict disease progression, pulmonary complications, and viral positivity duration.<h4>Methods</h4>A single-center cohort study was conducted by consecutively including hospitalized patients with confirmed COVID-19. The chest CT patterns were describe ...[more]

PMID: 33820751

Similar Datasets

Project description:PurposeTo compare the diagnostic performance and inter-observer agreement of five different CT chest severity scoring systems for COVID-19 to find the most precise one with the least interpretation time.Methods and materialsThis retrospective study included 85 patients (54 male and 31 female) with PCR-confirmed COVID-19. They underwent CT to assess the severity of pulmonary involvement. Three readers were asked to assess the pulmonary abnormalities and score the severity using five different systems, including chest CT severity score (CT-SS), chest CT score, total severity score (TSS), modified total severity score (m-TSS), and 3-level chest CT severity score. Time consumption on reporting of each system was calculated.ResultsTwo hundred fifty-five observations were reported for each system. There was a statistically significant inter-observer agreement in assessing qualitative lung involvement using the m-TSS and the other four quantitative systems. The ROC curves revealed excellent and very good diagnostic accuracy for all systems when cutoff values for detection severe cases were > 22, > 17, > 12, and > 26 for CT-SS, chest CT score, TSS, and 3-level CT severity score. The AUC was very good (0.86), excellent (0.90), very good (0.89), and very good (0.86), respectively. Chest CT score showed the highest specificity (95.2%) in discrimination of severe cases. Time consumption on reporting was significantly different (< 0.001): CT-SS > 3L-CT-SS > chest CT score > TSS.ConclusionAll chest CT severity scoring systems in this study demonstrated excellent inter-observer agreement and reasonable performance to assess COVID-19 in relation to the clinical severity. CT-SS and TSS had the highest specificity and least time for interpretation.Key points• All chest CT severity scoring systems discussed in this study revealed excellent inter-observer agreement and reasonable performance to assess COVID-19 in relation to the clinical severity. • Chest CT scoring system and TSS had the highest specificity. • Both TSS and m-TSS consumed the least time compared to the other three scoring systems.

Dataset Information

Chest CT severity score and radiological patterns as predictors of disease severity, ICU admission, and viral positivity in COVID-19 patients.

Background

Methods

Results

Conclusions

Publications

Chest CT severity score and radiological patterns as predictors of disease severity, ICU admission, and viral positivity in COVID-19 patients.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets