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.

Author Correction: A new coronavirus associated with human respiratory disease in China.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

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.

Analysis of factors associated with disease outcomes in hospitalized patients with 2019 novel coronavirus disease.

BACKGROUND: Since early December 2019, the 2019 novel coronavirus disease (COVID-19) has caused pneumonia epidemic in Wuhan, Hubei province of China. This study aimed to investigate the factors affecting the progression of pneumonia in COVID-19 patients. Associated results will be used to evaluate the prognosis and to find the optimal treatment regimens for COVID-19 pneumonia. METHODS: Patients tested positive for the COVID-19 based on nucleic acid detection were included in this study. Patients were admitted to 3 tertiary hospitals in Wuhan between December 30, 2019, and January 15, 2020. Individual data, laboratory indices, imaging characteristics, and clinical data were collected, and statistical analysis was performed. Based on clinical typing results, the patients were divided into a progression group or an improvement/stabilization group. Continuous variables were analyzed using independent samples t-test or Mann-Whitney U test. Categorical variables were analyzed using Chi-squared test or Fisher's exact test. Logistic regression analysis was performed to explore the risk factors for disease progression. RESULTS: Seventy-eight patients with COVID-19-induced pneumonia met the inclusion criteria and were included in this study. Efficacy evaluation at 2 weeks after hospitalization indicated that 11 patients (14.1%) had deteriorated, and 67 patients (85.9%) had improved/stabilized. The patients in the progression group were significantly older than those in the disease improvement/stabilization group (66 [51, 70] vs. 37 [32, 41] years, U = 4.932, P = 0.001). The progression group had a significantly higher proportion of patients with a history of smoking than the improvement/stabilization group (27.3% vs. 3.0%, χ = 9.291, P = 0.018). For all the 78 patients, fever was the most common initial symptom, and the maximum body temperature at admission was significantly higher in the progression group than in the improvement/stabilization group (38.2 [37.8, 38.6] vs. 37.5 [37.0, 38.4]°C, U = 2.057, P = 0.027). Moreover, the proportion of patients with respiratory failure (54.5% vs. 20.9%, χ = 5.611, P = 0.028) and respiratory rate (34 [18, 48] vs. 24 [16, 60] breaths/min, U = 4.030, P = 0.004) were significantly higher in the progression group than in the improvement/stabilization group. C-reactive protein was significantly elevated in the progression group compared to the improvement/stabilization group (38.9 [14.3, 64.8] vs. 10.6 [1.9, 33.1] mg/L, U = 1.315, P = 0.024). Albumin was significantly lower in the progression group than in the improvement/stabilization group (36.62 ±â€Š6.60 vs. 41.27 ±â€Š4.55 g/L, U = 2.843, P = 0.006). Patients in the progression group were more likely to receive high-level respiratory support than in the improvement/stabilization group (χ = 16.01, P = 0.001). Multivariate logistic analysis indicated that age (odds ratio [OR], 8.546; 95% confidence interval [CI]: 1.628-44.864; P = 0.011), history of smoking (OR, 14.285; 95% CI: 1.577-25.000; P = 0.018), maximum body temperature at admission (OR, 8.999; 95% CI: 1.036-78.147, P = 0.046), respiratory failure (OR, 8.772, 95% CI: 1.942-40.000; P = 0.016), albumin (OR, 7.353, 95% CI: 1.098-50.000; P = 0.003), and C-reactive protein (OR, 10.530; 95% CI: 1.224-34.701, P = 0.028) were risk factors for disease progression. CONCLUSIONS: Several factors that led to the progression of COVID-19 pneumonia were identified, including age, history of smoking, maximum body temperature at admission, respiratory failure, albumin, and C-reactive protein. These results can be used to further enhance the ability of management of COVID-19 pneumonia.

A new coronavirus associated with human respiratory disease in China.

Emerging infectious diseases, such as severe acute respiratory syndrome (SARS) and Zika virus disease, present a major threat to public health1-3. Despite intense research efforts, how, when and where new diseases appear are still a source of considerable uncertainty. A severe respiratory disease was recently reported in Wuhan, Hubei province, China. As of 25 January 2020, at least 1,975 cases had been reported since the first patient was hospitalized on 12 December 2019. Epidemiological investigations have suggested that the outbreak was associated with a seafood market in Wuhan. Here we study a single patient who was a worker at the market and who was admitted to the Central Hospital of Wuhan on 26 December 2019 while experiencing a severe respiratory syndrome that included fever, dizziness and a cough. Metagenomic RNA sequencing4 of a sample of bronchoalveolar lavage fluid from the patient identified a new RNA virus strain from the family Coronaviridae, which is designated here 'WH-Human 1' coronavirus (and has also been referred to as '2019-nCoV'). Phylogenetic analysis of the complete viral genome (29,903 nucleotides) revealed that the virus was most closely related (89.1% nucleotide similarity) to a group of SARS-like coronaviruses (genus Betacoronavirus, subgenus Sarbecovirus) that had previously been found in bats in China5. This outbreak highlights the ongoing ability of viral spill-over from animals to cause severe disease in humans.