Multicenter Study of Temporal Changes and Prognostic Value of a CT Visual Severity Score in Hospitalized Patients With Coronavirus Disease (COVID-19).

BACKGROUND. Chest CT findings have the potential to guide treatment of hospitalized patients with coronavirus disease (COVID-19). OBJECTIVE. The purpose of this study was to assess a CT visual severity score in hospitalized patients with COVID-19, with attention to temporal changes in the score and the role of the score in a model for predicting in-hospital complications. METHODS. This retrospective study included 161 inpatients with COVID-19 from three hospitals in China who underwent serial chest CT scans during hospitalization. CT examinations were evaluated using a visual severity scoring system. The temporal pattern of the CT visual severity score across serial CT examinations during hospitalization was characterized using a generalized spline regression model. A prognostic model to predict major complications, including in-hospital mortality, was created using the CT visual severity score and clinical variables. External model validation was evaluated by two independent radiologists in a cohort of 135 patients from a different hospital. RESULTS. The cohort included 91 survivors with nonsevere disease, 55 survivors with severe disease, and 15 patients who died during hospitalization. Median CT visual lung severity score in the first week of hospitalization was 2.0 in survivors with non-severe disease, 4.0 in survivors with severe disease, and 11.0 in nonsurvivors. CT visual severity score peaked approximately 9 and 12 days after symptom onset in survivors with nonsevere and severe disease, respectively, and progressively decreased in subsequent hospitalization weeks in both groups. In the prognostic model, in-hospital complications were independently associated with a severe CT score (odds ratio [OR], 31.28), moderate CT score (OR, 5.86), age (OR, 1.09 per 1-year increase), and lymphocyte count (OR, 0.03 per 1 × 109/L increase). In the validation cohort, the two readers achieved C-index values of 0.92-0.95, accuracy of 85.2-86.7%, sensitivity of 70.7-75.6%, and specificity of 91.4-91.5% for predicting in-hospital complications. CONCLUSION. A CT visual severity score is associated with clinical disease severity and evolves in a characteristic fashion during hospitalization for COVID-19. A prognostic model based on the CT visual severity score and clinical variables shows strong performance in predicting in-hospital complications. CLINICAL IMPACT. The prognostic model using the CT visual severity score may help identify patients at highest risk of poor outcomes and guide early intervention.

Temporal radiographic changes in COVID-19 patients: relationship to disease severity and viral clearance.

COVID-19 is "public enemy number one" and has placed an enormous burden on health authorities across the world. Given the wide clinical spectrum of COVID-19, understanding the factors that can predict disease severity will be essential since this will help frontline clinical staff to stratify patients with increased confidence. To investigate the diagnostic value of the temporal radiographic changes, and the relationship to disease severity and viral clearance in COVID-19 patients. In this retrospective cohort study, we included 99 patients admitted to the Renmin Hospital of Wuhan University, with laboratory confirmed moderate or severe COVID-19. Temporal radiographic changes and viral clearance were explored using appropriate statistical methods. Radiographic features from HRCT scans included ground-glass opacity, consolidation, air bronchogram, nodular opacities and pleural effusion. The HRCT scores (peak) during disease course in COVID-19 patients with severe pneumonia (median: 24.5) were higher compared to those with pneumonia (median: 10) (p = 3.56 × 10 -12), with more frequency of consolidation (p = 0.025) and air bronchogram (p = 7.50 × 10-6). The median values of days when the peak HRCT scores were reached in pneumonia or severe pneumonia patients were 12 vs. 14, respectively (p = 0.048). Log-rank test and Spearman's Rank-Order correlation suggested temporal radiographic changes as a valuable predictor for viral clearance. In addition, follow up CT scans from 11 pneumonia patients showed full recovery. Given the values of HRCT scores for both disease severity and viral clearance, a standardised HRCT score system for COVID-19 is highly demanded.

Predictive factors of severe coronavirus disease 2019 in previously healthy young adults: a single-center, retrospective study.

BACKGROUND: Several previously healthy young adults have developed Coronavirus Disease 2019 (COVID-19), and a few of them progressed to the severe stage. However, the factors are not yet determined. METHOD: We retrospectively analyzed 123 previously healthy young adults diagnosed with COVID-19 from January to March 2020 in a tertiary hospital in Wuhan. Patients were classified as having mild or severe COVID-19 based on their respiratory rate, SpO2, and PaO2/FiO2 levels. Patients' symptoms, computer tomography (CT) images, preadmission drugs received, and the serum biochemical examination on admission were compared between the mild and severe groups. Significant variables were enrolled into logistic regression model to predict the factors affecting disease severity. A receiver operating characteristic (ROC) curve was applied to validate the predictive value of predictors. RESULT: Age; temperature; anorexia; and white blood cell count, neutrophil percentage, platelet count, lymphocyte count, C-reactive protein, aspartate transaminase, creatine kinase, albumin, and fibrinogen values were significantly different between patients with mild and severe COVID-19 (P < 0.05). Logistic regression analysis confirmed that lymphopenia (P = 0.010) indicated severe prognosis in previously healthy young adults with COVID-19, with the area under the curve (AUC) was 0.791(95% Confidence Interval (CI) 0.704-0.877)(P < 0.001). CONCLUSION: For previously healthy young adults with COVID-19, lymphopenia on admission can predict severe prognosis.

Effects of Corticosteroid Treatment for Non-Severe COVID-19 Pneumonia: A Propensity Score-Based Analysis.

BACKGROUND AND OBJECTIVE: The effects of corticosteroid treatment on non-severe COVID-19 pneumonia patients are unknown. To determine the impacts of adjuvant corticosteroid administrated to patients with non-severe COVID-19 pneumonia. METHOD: A retrospective cohort study based on propensity score analysis was designed to explore the effects of corticosteroid on several clinical outcomes. RESULTS: One hundred thirty-two patients satisfied the inclusion criteria and 35 pairs were generated according to propensity score matching. Compared to non-corticosteroid group, the CT score on day 7 was significantly higher in corticosteroid group (8.6 (interquartile range [IQR], 2.8-11.5) versus 12.0 (IQR, 5.0-19.3), P = 0.046). In corticosteroid group, more patients progressed to severe cases (11.4% versus 2.9%, P = 0.353), hospital stay (23.5 days (IQR, 19-29 d) versus 20.2 days (IQR, 14-25.3 d), P = 0.079) and duration of viral shedding (20.3 days (IQR, 15.2-24.8 d) versus 19.4 days (IQR, 11.5-28.3 d), P = 0.669) were prolonged, while fever time (9.5 days (IQR, 6.5-12.2 d) versus 10.2 days (IQR, 6.8-14 d), P = 0.28) was shortened; however, all these data revealed no statistically significant differences. CONCLUSION: Corticosteroid might have a negative effect on lung injury recovery in non-severe COVID-19 pneumonia patients; however, the results of this study must be interpreted with caution because of confounding factors.

Association of radiologic findings with mortality of patients infected with 2019 novel coronavirus in Wuhan, China.

Radiologic characteristics of 2019 novel coronavirus (2019-nCoV) infected pneumonia (NCIP) which had not been fully understood are especially important for diagnosing and predicting prognosis. We retrospective studied 27 consecutive patients who were confirmed NCIP, the clinical characteristics and CT image findings were collected, and the association of radiologic findings with mortality of patients was evaluated. 27 patients included 12 men and 15 women, with median age of 60 years (IQR 47-69). 17 patients discharged in recovered condition and 10 patients died in hospital. The median age of mortality group was higher compared to survival group (68 (IQR 63-73) vs 55 (IQR 35-60), P = 0.003). The comorbidity rate in mortality group was significantly higher than in survival group (80% vs 29%, P = 0.018). The predominant CT characteristics consisted of ground glass opacity (67%), bilateral sides involved (86%), both peripheral and central distribution (74%), and lower zone involvement (96%). The median CT score of mortality group was higher compared to survival group (30 (IQR 7-13) vs 12 (IQR 11-43), P = 0.021), with more frequency of consolidation (40% vs 6%, P = 0.047) and air bronchogram (60% vs 12%, P = 0.025). An optimal cutoff value of a CT score of 24.5 had a sensitivity of 85.6% and a specificity of 84.5% for the prediction of mortality. 2019-nCoV was more likely to infect elderly people with chronic comorbidities. CT findings of NCIP were featured by predominant ground glass opacities mixed with consolidations, mainly peripheral or combined peripheral and central distributions, bilateral and lower lung zones being mostly involved. A simple CT scoring method was capable to predict mortality.