Chest CT Severity Score in COVID-19 at the Time of Admission and Relationship with Outcome and Duration of Admission-an Early Promising Prognostic Indicator (original) (raw)
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Chest CT score in COVID-19 patients: correlation with disease severity and short-term prognosis
European Radiology, 2020
Objectives To correlate a CT-based semi-quantitative score of pulmonary involvement in COVID-19 pneumonia with clinical staging of disease and laboratory findings. We also aimed to investigate whether CT findings may be predictive of patients' outcome. Methods From March 6 to March 22, 2020, 130 symptomatic SARS-CoV-2 patients were enrolled for this single-center analysis and chest CT examinations were retrospectively evaluated. A semi-quantitative CT score was calculated based on the extent of lobar involvement (0:0%; 1, < 5%; 2:5-25%; 3:26-50%; 4:51-75%; 5, > 75%; range 0-5; global score 0-25). Data were matched with clinical stages and laboratory findings. Survival curves and univariate and multivariate analyses were performed to evaluate the role of CT score as a predictor of patients' outcome. Results Ground glass opacities were predominant in early-phase (≤ 7 days since symptoms' onset), while crazy-paving pattern, consolidation, and fibrosis characterized late-phase disease (> 7 days). CT score was significantly higher in critical and severe than in mild stage (p < 0.0001), and among late-phase than early-phase patients (p < 0.0001). CT score was significantly correlated with CRP (p < 0.0001, r = 0.6204) and D-dimer (p < 0.0001, r = 0.6625) levels. A CT score of ≥ 18 was associated with an increased mortality risk and was found to be predictive of death both in univariate (HR, 8.33; 95% CI, 3.19-21.73; p < 0.0001) and multivariate analysis (HR, 3.74; 95% CI, 1.10-12.77; p = 0.0348). Conclusions Our preliminary data suggest the potential role of CT score for predicting the outcome of SARS-CoV-2 patients. CT score is highly correlated with laboratory findings and disease severity and might be beneficial to speed-up diagnostic workflow in symptomatic cases. Key Points • CT score is positively correlated with age, inflammatory biomarkers, severity of clinical categories, and disease phases. • A CT score ≥ 18 has shown to be highly predictive of patient's mortality in short-term follow-up. • Our multivariate analysis demonstrated that CT parenchymal assessment may more accurately reflect short-term outcome, providing a direct visualization of anatomic injury compared with non-specific inflammatory biomarkers. Keywords Severe acute respiratory syndrome coronavirus 2. COVID-19. Pneumonia. Tomography, X-ray computed Marco Francone and Franco Iafrate contributed equally to this work.
Chest Computed Tomography Severity Score to Predict Adverse Outcomes of Patients with COVID-19
Infection and Chemotherapy, 2021
Background: The novel coronavirus disease 2019 (COVID-19) continues to wreak havoc worldwide. This study assessed the ability of chest computed tomography (CT) severity score (CSS) to predict intensive care unit (ICU) admission and mortality in patients with COVID-19 pneumonia. Materials and Methods: A total of 192 consecutive patients with COVID-19 pneumonia aged more than 20 years and typical CT findings and reverse-transcription polymerase chain reaction positive admitted in a tertiary hospital were included. Clinical symptoms at admission and short-term outcome were obtained. A semi-quantitative scoring system was used to evaluate the parenchymal involvement. The association between CSS, disease severity, and outcomes were evaluated. Prediction of CSS was assessed with the area under the receiver-operating characteristic (ROC) curves. Results: The incidence of admission to ICU was 22.8% in men and 14.1% in women. CSS was related to ICU admission and mortality. Areas under the ROC curves were 0.764 for total CSS. Using a stepwise binary logistic regression model, gender, age, oxygen saturation, and CSS had a significant independent relationship with ICU admission and death. Patients with CSS ≥12.5 had about four-time risk of ICU admission and death (odds ratio 1.66, 95% confidence interval 1.66-9.25). The multivariate regression analysis showed the superiority of CSS over other clinical information and co-morbidities. Conclusion: CSS was a strong predictor of progression to ICU admission and death and there was a substantial role of non-contrast chest CT imaging in the presence of typical features for COVID-19 pneumonia as a reliable predictor of clinical severity and patient's outcome.
Comparison of chest CT severity scoring systems for COVID-19
European Radiology, 2022
To 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. This 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. Two 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 accura...
Egyptian Journal of Radiology and Nuclear Medicine, 2022
Background: Since November 2019, the rapid outbreak of coronavirus disease 2019 (COVID-19) has become a public health emergency of international concern. COVID-19 disease is caused by a new variant of coronavirus, named as 'severe acute respiratory syndrome coronavirus 2. ' Chest CT has a potential role in the diagnosis, detection of complications and in predicting clinical recovery of patients or progression of coronavirus disease 2019. Degree and severity of lung involvement can be assessed by 25 point CT severity score. This quantification plays an important role to modify the treatment plan at times in critically ill patient of COVID-19. Hence, the purpose of present study was to describe and quantify the severity of COVID-19 infection on chest computed tomography (CT) by 25-point CT severity score and to determine the relationship of CT severity score with clinical and laboratory parameters. Results: A total of 150 patients with COVID-19 disease were assessed. Mean age of the study group was 54.46 years (62.7% males and 37.3% females). The most common comorbidity present in the study group was diabetes mellitus, which was present in 17.3% cases. Severity of disease was significantly associated with age of the patient. CT severity score was positively correlated with lymphopenia and raised CRP, D-dimer and serum ferritin levels. A significant statistical correlation was found between CT severity grade and patient survival. Conclusions: This is a large comprehensive study, collecting data from 150 cases of COVID-19 pneumonia patients, in a tertiary care hospital in India to describe the correlation of CT severity score with clinical land laboratory parameters. Chest CT severity score correlates well with laboratory parameters and can aid in predicting COVID-19 disease outcome.
La radiologia medica
Purpose Lung severity score (LSS) and quantitative chest CT (QCCT) analysis could have a relevant impact to stratify patients affected by COVID-19 pneumonia at the hospital admission. The study aims to assess LSS and QCCT performances in severity stratification of COVID-19 patients. Materials and methods From April 19, 2020, until May 3, 2020, patients with chest CT suggestive for interstitial pneumonia and tested positive for COVID-19 were retrospectively enrolled and stratified for hospital admission as Group 1, 2 and 3 (home isolation, low intensive care and intensive care, respectively). For LSS, lungs were divided in 20 regions and visually assessed by two radiologists who scored for each region from non-lung involvement as 0, < 50% assigned as 1 and > 50% as 2. QCCT was performed with a dedicated software that extracts pulmonary involvement expressed in liters and percentage. LSS and QCCT were analyzed with ROC curve analysis to predict the performance of both methods. P...
Predictors of The Chest CT Score in COVID-19 Patients: A Cross-Sectional Study
Background: Since the COVID-19 outbreak, pulmonary involvement was one of the most significant concerns in assessing patients. In the current study, we evaluated patient’s signs, symptoms, and laboratory data on the first visit to predict the severity of pulmonary involvement and their outcome regarding their initial findings.Methods: All referred patients to the CODID-19 clinic of a tertiary referral university hospital were evaluated from April to August 2020. Four hundred seventy-eight COVID-19 patients with positive real-time reverse-transcriptase-polymerase chain reaction (RT-PCR) or highly suggestive symptoms with computed tomography(CT) imaging results with typical findings of COVID-19 were enrolled in the study. The clinical features, initial laboratory, CT findings, and short-term outcomes (ICU admission, mortality, length of hospitalization, and recovery time) were recorded. In addition, the severity of pulmonary involvement was assessed using a semi-quantitative scoring s...
2021
OBJECTIVE To identify utility of chest computed tomography severity score (CT-SS) as an additional tool to COVID-19 pneumonia imaging classification in assessing severity of COVID-19. STUDY DESIGN Descriptive analytical study Place and Duration of Study: Armed Forces Institute of Radiology and Imaging, (AFIRI) Rawalpindi, from April 2020 to June 2020. METHODOLOGY Five hundred suspected COVID-19 cases referred for high resolution computed tomography - chest were included in the study. Cases were categorised by radiological findings using COVID-19 pneumonia imaging classification, proposed in the radiological society of North America expert consensus statement on reporting chest CT findings related to COVID-19. CT-SS was calculated for all scans. Patients were clinically classified according to disease severity as per 'Diagnosis And Treatment Program of Pneumonia of New Coronavirus Infection' recommended by China's National Health Commission. The relationships between ra...
Iranian Journal of Radiology
Background: Studies have shown that computed tomography (CT) could be valuable for prognostic issues in COVID-19. Objectives: To investigate the prognostic factors of early chest CT findings in COVID-19 patients. Patients and Methods: This retrospective study included 91 patients (34 women, and 57 men) of real-time reverse transcription polymerase chain reaction (RT-PCR) positive COVID-19 from three hospitals in Iran between February 25, 2020, to March 15, 2020. Patients were divided into two groups as good prognosis, discharged from the hospital and alive without symptoms (48 patients), and poor prognosis, died or needed ICU care (43 patients). The first CT images of both groups that were obtained during the first 8 days of the disease presentation were evaluated considering the pattern, distribution, and underlying disease. The total CT-score was calculated for each patient. Univariate and multivariate analysis with IBM SPSS Statistics v.26 was used to find the prognostic factors....