Home quarantine during COVID-19 blunted childhood trauma-related psychiatric symptoms in Chinese college students.

Background: Childhood trauma confers risks to mental health. However, little is known about whether home quarantine (HQ) during the coronavirus disease 2019 (COVID-19) pandemic exaggerated or mitigated the effect of childhood trauma on mental health. Objective: To examine the modulating effects of prior childhood traumas on the longitudinal changes of psychiatric symptoms in college students before and after HQ during the pandemic. Methods: This was a two-wave longitudinal study on the mental health of 2,887 college students before and after HQ during the COVID-19 pandemic. The relationships between the changes in the Patient Health Questionnaire-9 (PHQ-9), Symptom Checklist-90 (SCL-90), 16-item Prodromal Questionnaire (PQ-16), Childhood Trauma Questionnaire (CTQ), and Social Support Rating Scale (SSRS) scores were analyzed. Results: The students with childhood trauma showed a significantly greater decrement in psychiatric symptoms after HQ (F = 17.21, 14.11, 18.87, and 17.42 for PHQ-9, PQ-16 objective and distress, and SCL-90, respectively). The correlation coefficients between the CTQ and these symptoms scales were significant at baseline (r = 0.42, 0.34, 0.37, and 0.39), and decreased after HQ (r = 0.17, 0.20, 0.18, and 0.19). The decrement of depressive, psychotic, and overall symptoms was positively correlated with the scores of the CTQ (r = 0.08-0.27) but negatively correlated with SSRS (r = -0.08--0.14). Multilinear regression analysis confirmed the results of the CTQ and SSRS regarding the modulation of the dynamic changes in psychiatric symptoms. A constructed structural equation model indicated that the total effects of childhood trauma on decreased psychiatric symptoms were partly mediated by lower baseline social support. Conclusion: Home quarantine during the COVID-19 pandemic could blunt the adverse effects of childhood trauma on mental health, especially for prodromal psychotic symptoms in college students. Changes in relative deprivation and social support may be mediating factors.

Clinical observation of neutralizing antibody DXP-604 for treatment critical COVID-19 patients infected with SARS-CoV-2 Delta variant.

From January to March 2022, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Delta (B.1.617.2) infection was prevalent in Yuzhou and Zhengzhou. DXP-604 is a broad-spectrum antiviral monoclonal antibody, which has excellent viral neutralization ability in vitro and a long half-life in vivo, with good biosafety and tolerability. Preliminary results showed that DXP-604 can accelerate recovery from Coronavirus disease 2019 (COVID-19) caused by SARS-CoV-2 Delta variant in hospitalized patients with mild to moderate clinical symptoms. However, the efficacy of DXP-604 has not been fully studied in high-risk severe patients. Here, we prospectively enrolled 27 high-risk patients, two groups were divided, in addition to receiving standard of care (SOC), 14 of them additionally received the neutralizing antibody DXP-604 therapy, and another 13 intensive care unit (ICU) patients simultaneously underwent SOC as a control group matched for age, gender, and clinical type. The results revealed lower C-reactive protein, interleukin-6, lactic dehydrogenase and neutrophil counts, and higher lymphocyte and monocyte counts from Day 3 post-DXP-604 treatment compared with SOC treatment. Besides, thoracic CT images showed improvements in lesion areas and degrees, along with changes in blood inflammatory factors. Moreover, DXP-604 reduced the invasive mechanical ventilation and mortality of high-risk SARS-CoV-2 infected patients. The ongoing clinical trials of DXP-604 neutralizing antibody will clarify its utility as a new attractive countermeasure for high-risk COVID-19.

Occupational stress and its influencing factors of primary health care workers during COVID-19

Background Since the outbreak of COVID-19, primary health care workers have been facing unprecedented work pressure, and their occupational stress should be taken seriously. Objective To analyze the occupational stress situation and its influencing factors of primary health care workers in Guangdong Province, and to propose targeted interventions. Methods Using a multi-stage stratified random sampling method, each prefecture-level city in Guangdong Province was classified into "good", "medium", or "poor" category based on its gross domestic product (GDP) in 2019 released by the Guangdong Provincial Bureau of Statistics. In September 2021, four primary health care institutions were randomly selected from each stratum, and a total of 1327 staff members were selected for the study. The Core Occupational Stress Scale (COSS) and a basic information questionnaire designed by the authors were used. Mann-Whitney U test was used to compare the means between two groups, and Kruskal-Walis H test was used to compare the means among multiple groups. The comparison of categorical data was performed by trend χ2 test or Pearson χ2 test;the analysis of factors influencing occupational stress was performed by dichotomous multiple logistic regression analysis. Results There were 365 health care workers reporting occupational stress in this survey, and the positive rate of occupational stress was 27.5%. The total occupational stress score in M (P25, P75) and the scores of social support, organization and reward, demand and effort, and control were 45.0 (40.0, 50.0), 20.0 (17.0, 21.0), 14.0 (12.0, 17.0), 12.0 (10.0, 15.0), and 5.0 (4.0, 6.0), respectively. The results of dichotomous multiple logistic regression analysis showed that high education, low income, doctor positions, long working hours in a day, and shift work were associated with the occurrence of reporting occupational stress (P<0.05). Conclusion Education, average monthly income, job category, daily working hours, and shifts are factors influencing the occurrence of reporting occupational stress in primary health care workers;targeted interventions should be implemented to reduce their occupational stress levels.

COVID-19 Vaccination and Financial Frictions

We study the COVID-19 epidemic in emerging markets that face financial frictions and its mitigation through social distancing and vaccination. We find that restricted vaccine availability in emerging markets, as captured by limited quantities and high prices, renders the pandemic exceptionally costly in these countries, compared with economies without financial frictions. Improved access to financial markets enables a better response to the delay in vaccine supplies, as it supports more stringent social distancing measures before wider vaccine availability. We show that financial assistance programs to such financially constrained countries can increase vaccinations and lower fatalities, at no present-value cost to the international community.

Long-Term Follow-Up Study of COVID-19: Evaluation on Thin-Slice CT.

Purpose: To retrospectively analyse the CT imaging during the long-term follow-up of COVID-19 patients after discharge. Patients and Methods: A total of 122 patients entered the study group. All patients underwent CT examinations. The CT images, which included distribution and imaging signs, were evaluated by two chest radiologists. Laboratory examinations included routine blood work, biochemical testing, and SARS-CoV-2 antibody screening. Statistical methods include chi-square, Fisher's exact test, one-way analysis of variance, rank sum test and logistic regression by SPSS 17.0. Results: There were 22 (18.0%) patients in the mild group, 74 (60.7%) patients in the moderate group, and 26 (21.3%) patients in the severe-critical group. The median follow-up interval was 405 days (378.0 days, 462.8 days). Only monocytes, prothrombin activity, and γ-glutamyltransferase showed significant differences among the three groups. We found that the more severe the patient's condition, the more SARS-CoV-2 IgG antibodies existed. Only 11 patients (11.0%) showed residual lesions on CT. The CT manifestations included irregular linear opacities in nine cases (9.0%), reticular patterns in six cases (6.0%), and GGOs in five cases (5.0%). Conclusion: The proportion of residual lesions on CT in COVID-19 patients was significantly reduced after long-term follow-up. The patients' age and disease conditions were positively correlated with residual lesions.

Understanding metabolic alterations after SARS-CoV-2 infection: insights from the patients' oral microenvironmental metabolites.

BACKGROUND: Coronavirus disease 2019 is a type of acute infectious pneumonia and frequently confused with influenza since the initial symptoms. When the virus colonized the patient's mouth, it will cause changes of the oral microenvironment. However, few studies on the alterations of metabolism of the oral microenvironment affected by SARS-CoV-2 infection have been reported. In this study, we explored metabolic alterations of oral microenvironment after SARS-CoV-2 infection. METHODS: Untargeted metabolomics (UPLC-MS) was used to investigate the metabolic changes between oral secretion samples of 25 COVID-19 and 30 control participants. To obtain the specific metabolic changes of COVID-19, we selected 25 influenza patients to exclude the metabolic changes caused by the stress response of the immune system to the virus. Multivariate analysis (PCA and PLS-DA plots) and univariate analysis (students' t-test) were used to compare the differences between COVID-19 patients and the controls. Online hiplot tool was used to perform heatmap analysis. Metabolic pathway analysis was conducted by using the MetaboAnalyst 5.0 web application. RESULTS: PLS-DA plots showed significant separation of COVID-19 patients and the controls. A total of 45 differential metabolites between COVID-19 and control group were identified. Among them, 35 metabolites were defined as SARS-CoV-2 specific differential metabolites. Especially, the levels of cis-5,8,11,14,17-eicosapentaenoic acid and hexanoic acid changed dramatically based on the FC values. Pathway enrichment found the most significant pathways were tyrosine-related metabolism. Further, we found 10 differential metabolites caused by the virus indicating the body's metabolism changes after viral stimulation. Moreover, adenine and adenosine were defined as influenza virus-specific differential metabolites. CONCLUSIONS: This study revealed that 35 metabolites and tyrosine-related metabolism pathways were significantly changed after SARS-CoV-2 infection. The metabolic alterations of oral microenvironment in COVID-19 provided new insights into its molecular mechanisms for research and prognostic treatment.

Analysis of CT signs, radiomic features and clinical characteristics for delta variant COVID-19 patients with different vaccination status.

OBJECTIVE: To explore the characteristics of peripheral blood, high resolution computed tomography (HRCT) imaging and the radiomics signature (RadScore) in patients infected with delta variant virus under different coronavirus disease (COVID-19) vaccination status. METHODS: 123 patients with delta variant virus infection collected from November 1, 2021 to March 1, 2022 were analyzed retrospectively. According to COVID-19 vaccination Status, they were divided into three groups: Unvaccinated group, partially vaccinated group and full vaccination group. The peripheral blood, chest HRCT manifestations and RadScore of each group were analyzed and compared. RESULTS: The mean lymphocyte count 1.22 ± 0.49 × 10^9/L, CT score 7.29 ± 3.48, RadScore 0.75 ± 0.63 in the unvaccinated group; The mean lymphocyte count 1.55 ± 0.70 × 10^9/L, CT score 5.27 ± 2.72, RadScore 1.03 ± 0.46 in the partially vaccinated group; The mean lymphocyte count 1.87 ± 0.70 × 10^9/L, CT score 3.59 ± 3.14, RadScore 1.23 ± 0.29 in the fully vaccinated group. There were significant differences in lymphocyte count, CT score and RadScore among the three groups (all p < 0.05); Compared with the other two groups, the lung lesions in the unvaccinated group were more involved in multiple lobes, of which 26 cases involved the whole lung. CONCLUSIONS: Through the analysis of clinical features, pulmonary imaging features and radiomics, we confirmed the positive effect of COVID-19 vaccine on pulmonary inflammatory symptoms and lymphocyte count (immune system) during delta mutant infection.

Long-Term Follow-Up Study of COVID-19: Evaluation on Thin-Slice CT

Purpose To retrospectively analyse the CT imaging during the long-term follow-up of COVID-19 patients after discharge. Patients and Methods A total of 122 patients entered the study group. All patients underwent CT examinations. The CT images, which included distribution and imaging signs, were evaluated by two chest radiologists. Laboratory examinations included routine blood work, biochemical testing, and SARS-CoV-2 antibody screening. Statistical methods include chi-square, Fisher’s exact test, one-way analysis of variance, rank sum test and logistic regression by SPSS 17.0. Results There were 22 (18.0%) patients in the mild group, 74 (60.7%) patients in the moderate group, and 26 (21.3%) patients in the severe–critical group. The median follow-up interval was 405 days (378.0 days, 462.8 days). Only monocytes, prothrombin activity, and γ-glutamyltransferase showed significant differences among the three groups. We found that the more severe the patient’s condition, the more SARS-CoV-2 IgG antibodies existed. Only 11 patients (11.0%) showed residual lesions on CT. The CT manifestations included irregular linear opacities in nine cases (9.0%), reticular patterns in six cases (6.0%), and GGOs in five cases (5.0%). Conclusion The proportion of residual lesions on CT in COVID-19 patients was significantly reduced after long-term follow-up. The patients’ age and disease conditions were positively correlated with residual lesions.

COVID-19 Vaccination and Financial Frictions

We study the COVID-19 epidemic in emerging markets that face financial frictions and its mitigation through social distancing and vaccination. We find that restricted vaccine availability in emerging markets, as captured by limited quantities and high prices, renders the pandemic exceptionally costly in these countries, compared with economies without financial frictions. Improved access to financial markets enables a better response to the delay in vaccine supplies, as it supports more stringent social distancing measures before wider vaccine availability. We show that financial assistance programs to such financially constrained countries can increase vaccinations and lower fatalities, at no present-value cost to the international community.

A bibliometric and visualized analysis of early mobilization in intensive care unit from 2000 to 2021

Background Early mobilization in the intensive care unit (ICU) is a hotspot. This study aims to provide a bibliometric perspective of the progress in this field. Methods We extracted publications on ICU early mobilization published in the Web of Science Core Collection database from 2000 to 2021. VOSviewer was used to construct co-occurrence and co-citation relationships for authors, references, and keywords;Citespace was used to visualize knowledge mapping of subject categories, countries, and keywords with the strongest citation bursts. Results A total of 4,570 publications were analyzed, with a steady increase in publications in the field of ICU early mobilization. From a macro perspective, research on ICU early mobilization involves multidisciplinary involvement, including critical care medicine, neurology, and nursing;as for the meso perspective, the United States is the major contributor. Needham DM and Schweickert WD are the key researchers in this field. Moreover, the core journal is Critical Care Medicine, with the most publications and citations. The microscopic level, dominated by references and keywords, illustrates that the hotspot and frontier of research on ICU early mobilization focus on ICU-acquired weakness, delirium, the prognosis of critical illness, and severe COVID-19. Conclusion This study presents a research landscape of ICU early mobilization from different perspectives. These findings will contribute to a better understanding of the current state of research in critical care medicine and provide the available information for future research ideas.

Retail prices of nutritious food rose more in countries with higher COVID-19 case counts.

The COVID-19 pandemic has curtailed lives and livelihoods, leading to price spikes for some foods and declines for others. We compare monthly retail food prices in up to 181 countries from January 2019 to June 2021, test for differences over time and find that average prices rose significantly, especially for more nutritious food groups in countries with higher COVID-19 case counts. Analysis of retail prices by food group complements data on farm commodity prices and overall consumer price indexes, helping to guide policy for resilience and response to shocks.

Identifying the individual metabolic abnormities from a systemic perspective using whole-body PET imaging.

INTRODUCTION: Distinct physiological states arise from complex interactions among the various organs present in the human body. PET is a non-invasive modality with numerous successful applications in oncology, neurology, and cardiology. However, while PET imaging has been applied extensively in detecting focal lesions or diseases, its potential in detecting systemic abnormalities is seldom explored, mostly because total-body imaging was not possible until recently. METHODS: In this context, the present study proposes a framework capable of constructing an individual metabolic abnormality network using a subject's whole-body 18F-FDG SUV image and a normal control database. The developed framework was evaluated in the patients with lung cancer, the one discharged after suffering from Covid-19 disease, and the one that had gastrointestinal bleeding with the underlying cause unknown. RESULTS: The framework could successfully capture the deviation of these patients from healthy subjects at the level of both system and organ. The strength of the altered network edges revealed the abnormal metabolic connection between organs. The overall deviation of the network nodes was observed to be highly correlated to the organ SUV measures. Therefore, the molecular connectivity of glucose metabolism was characterized at a single subject level. CONCLUSION: The proposed framework represents a significant step toward the use of PET imaging for identifying metabolic dysfunction from a systemic perspective. A better understanding of the underlying biological mechanisms and the physiological interpretation of the interregional connections identified in the present study warrant further research.

Deadly Debt Crises: COVID-19 in Emerging Markets

The coronavirus pandemic has severely impacted emerging markets by generating a large death toll, deep recessions, and a wave of sovereign defaults. We study this compound health, economic, and debt crisis and its mitigation by integrating epidemiological dynamics into a sovereign default model. The epidemic leads to an urgent need for social distancing measures, a large drop in economic activity, and a protracted debt crisis. The presence of default risk restricts fiscal space and presents emerging markets with a trade-off between mitigation of the pandemic and fiscal distress. A quantitative analysis of our model accounts well for the dynamics of deaths, social distance measures, and sovereign spreads in Latin America. In the model, the welfare cost of the pandemic is higher because of financial market frictions: about a third of the cost comes from default risk, compared with a version of the model with perfect financial markets. We study debt relief programs through counterfactuals and find a compelling case for their implementation, as they deliver large social gains.

Epidemiological characteristics and clinical manifestations of pediatric patients with COVID-19 in China: A multicenter retrospective study.

Importance: The Coronavirus disease 2019 (COVID-19) global pandemic poses a considerable challenge for pediatricians. Objective: This study aimed to identify the epidemiological characteristics and clinical features of pediatric patients with COVID-19 in China. Methods: This multicenter retrospective study included pediatric patients from 46 hospitals in China, covering 12 provinces and two municipalities. Epidemiological, demographic, clinical, laboratory, treatment, and outcome data were analyzed. Results: In total, 211 pediatric patients with COVID-19 were included in this study. The median age was 7.0 years (range: 22 days to 18 years). Approximately 16.3% of the patients exhibited asymptomatic infections, 23.0% had upper respiratory tract infections, and 60.7% had pneumonia, including two with severe pneumonia and one with critical illness. Approximately 78.7% of the pediatric patients occurred in familial clusters. The most three common symptoms or signs at onset in children with COVID-19 were fever (54.5%), cough (49.3%), and pharyngeal congestion (20.8%). Only 17.6% of the patients presented with decreased lymphocyte count, whereas 13.6% had increased lymphocyte count. Among the patients with pneumonia who exhibited abnormal chest computed tomography findings, 18.2% (23/127) of the patients had no other symptoms. Generally, the chest radiographs showed abnormalities that affected both lungs (49.6%); ground-glass opacity (47.2%) was the most common manifestation. The cure and improvement rates were 86.7% (183/211) and 13.3% (28/211), respectively. Only one patient with an underlying condition received invasive mechanical ventilation; none of the patients died. Interpretation: Similar to adults, children of all age groups are susceptible to COVID-19. Fortunately, most pediatric patients have mild symptoms or remain asymptomatic, despite the high incidence of pneumonia. Decreased proportions of white blood cells and lymphocytes are less frequent in children than in adults.

Comparison of Clinical Characteristics Among COVID-19 and Non-COVID-19 Pediatric Pneumonias: A Multicenter Cross-Sectional Study.

Background: The pandemic of Coronavirus Disease 2019 (COVID-19) brings new challenges for pediatricians, especially in the differentiation with non-COVID-19 pneumonia in the peak season of pneumonia. We aimed to compare the clinical characteristics of pediatric patients with COVID-19 and other respiratory pathogens infected pneumonias. Methods: We conducted a multi-center, cross-sectional study of pediatric inpatients in China. Based on pathogenic test results, pediatric patients were divided into three groups, including COVID-19 pneumonia group, Non-COVID-19 viral (NCV) pneumonia group and Non-viral (NV) pneumonia group. Their clinical characteristics were compared by Kruskal-Wallis H test or chi-square test. Results: A total of 636 pediatric pneumonia inpatients, among which 87 in COVID-19 group, 194 in NCV group, and 355 in NV group, were included in analysis. Compared with NCV and NV patients, COVID-19 patients were older (median age 6.33, IQR 2.00-12.00 years), and relatively fewer COVID-19 patients presented fever (63.2%), cough (60.9%), shortness of breath (1.1%), and abnormal pulmonary auscultation (18.4%). The results were verified by the comparison of COVID-19, respiratory syncytial virus (RSV) and influenza A (IFA) pneumonia patients. Approximately 42.5%, 44.8%, and 12.6% of the COVID-19 patients presented simply ground-glass opacity (GGO), simply consolidation, and the both changes on computed tomography (CT) scans, respectively; the proportions were similar as those in NCV and NV group (p>0.05). Only 47.1% of COVID-19 patients had both lungs pneumonia, which was significantly lower than that proportion of nearly 80% in the other two groups. COVID-19 patients presented lower proportions of increased white blood cell count (16.5%) and abnormal procalcitonin (PCT) (10.7%), and a higher proportion of decreased lymphocyte count (44.0%) compared with the other two groups. Conclusion: Majority clinical characteristics of pediatric COVID-19 pneumonia patients were milder than non-COVID-19 patients. However, lymphocytopenia remained a prominent feature of COVID-19 pediatric pneumonia.

Satellite Retrieval of Air Pollution Changes in Central and Eastern China during COVID-19 Lockdown Based on a Machine Learning Model

With the implementation of the 2018–2020 Clean Air Action Plan (CAAP) the and impact from COVID-19 lockdowns in 2020, air pollution emissions in central and eastern China have decreased markedly. Here, by combining satellite remote sensing, re-analysis, and ground-based observational data, we established a machine learning (ML) model to analyze annual and seasonal changes in primary air pollutants in 2020 compared to 2018 and 2019 over central and eastern China. The root mean squared errors (RMSE) for the PM2.5, PM10, O3, and CO validation dataset were 9.027 μg/m3, 20.312 μg/m3, 10.436 μg/m3, and 0.097 mg/m3, respectively. The geographical random forest (RF) model demonstrated good performance for four main air pollutants. Notably, PM2.5, PM10, and CO decreased by 44.1%, 43.2%, and 35.9% in February 2020, which was likely influenced by the COVID-19 lockdown and primarily lasted until May 2020. Furthermore, PM2.5, PM10, O3, and CO decreased by 16.4%, 24.2%, 2.7%, and 19.8% in 2020 relative to the average values in 2018 and 2019. Moreover, the reduction in O3 emissions was not universal, with a significant increase (~20–40%) observed in uncontaminated areas.

The time and risk factors of virus nucleic acid negative conversion in 104 cases of COVID-19 in Chongqing

Objective The time and the risk factors of virus nucleic acids negative conversion of coronavirus disease 2019 (COVID-19) patients were analyzed. Methods The clinical data of patients with COVID-19 admitted to Chongqing Public Health Medical Treatment Center from February 6 to March 9, 2020 were collected retrospectively. The clinical characteristics, treatment and outcome were described. The time of turning negative of nucleic acid was counted and the risk factors of turning negative of nucleic acid were analyzed. Results There were 104 confirmed cases of COVID-19, 56 males and 48 females, with an average age of (49.9 +or- 15.5) years (12-86 years old). The average interval between clinical symptoms and medical treatment was 5.5 days. From the time point of clinical symptoms, the time needed for nucleic acid to turn negative was (19.8 +or- 7.7) days, of which 32 cases (30.8%) turned negative within 14 days, 72 cases (69.2%) turned negative more than 14 days, and 14 cases (13.5%) turned negative more than 28 days. Univariate analysis showed that the time interval from clinical symptoms to medical treatment (6.7+or-4.4) days of nucleic acid conversion group after 14 days was longer than that (2.6 +or-1.8) days of conversion group within 14 days (P < 0.05);the incidence of combined with pulmonary bacterial infection (25 cases, 34.7%), infection more than three pulmonary lobes (36 cases, 50.0%), severe patients (24 cases, 33.3%) and combined use of glucocorticoids were greater than those of conversion group within 14 days (all P < 0.05). Multivariate analysis showed that there were significant differences in the time interval from symptoms to medical treatment and the proportion of three or more lobes involved in lung lesions between the two groups (P < 0.05). Conclusions The risk factors of viral nucleic acid turning negative are the timeliness of medical treatment, combined with pulmonary bacterial infection, wide range of pulmonary lesions, clinical typing and combined use of glucocorticoids, especially the timeliness of medical treatment and the range of pulmonary lesions.

A Deep Learning Radiomics Model to Identify Poor Outcome in COVID-19 Patients With Underlying Health Conditions: A Multicenter Study.

OBJECTIVE: Coronavirus disease 2019 (COVID-19) has caused considerable morbidity and mortality, especially in patients with underlying health conditions. A precise prognostic tool to identify poor outcomes among such cases is desperately needed. METHODS: Total 400 COVID-19 patients with underlying health conditions were retrospectively recruited from 4 centers, including 54 dead cases (labeled as poor outcomes) and 346 patients discharged or hospitalized for at least 7 days since initial CT scan. Patients were allocated to a training set (n = 271), a test set (n = 68), and an external test set (n = 61). We proposed an initial CT-derived hybrid model by combining a 3D-ResNet10 based deep learning model and a quantitative 3D radiomics model to predict the probability of COVID-19 patients reaching poor outcome. The model performance was assessed by area under the receiver operating characteristic curve (AUC), survival analysis, and subgroup analysis. RESULTS: The hybrid model achieved AUCs of 0.876 (95% confidence interval: 0.752-0.999) and 0.864 (0.766-0.962) in test and external test sets, outperforming other models. The survival analysis verified the hybrid model as a significant risk factor for mortality (hazard ratio, 2.049 [1.462-2.871], P < 0.001) that could well stratify patients into high-risk and low-risk of reaching poor outcomes (P < 0.001). CONCLUSION: The hybrid model that combined deep learning and radiomics could accurately identify poor outcomes in COVID-19 patients with underlying health conditions from initial CT scans. The great risk stratification ability could help alert risk of death and allow for timely surveillance plans.

Chest CT Evaluation of 11 Persistent Asymptomatic Patients with SARS-CoV-2 Infection.

In total, 11 asymptomatic carriers who underwent nasal or oropharyngeal swab tests for SARS-CoV-2 after being in close contact with patients who developed symptomatic 2019 coronavirus disease (COVID-19) were enrolled in this study. The chest multidetector computed tomography (CT) images of the enrolled patients were qualitatively and quantitatively analyzed. The findings of the first chest CT were normal in 3 (27.3%) patients, 2 of whom were aged below 15 years. The lesions of 2 (18.2%) patients involved 1 lobe with unifocal presence. Subpleural lesions were observed in 7 (63.6%) patients. Ground glass opacity (GGO) was the most common sign observed in 7 (63.6%) patients. Crazy-paving pattern and consolidation were detected in 2 (18.2%) and 4 (36.4%) patients, respectively. Based on deep learning and quantitative analysis, the mean volume of intrapulmonary lesions in the first CT image was 85.73 ± 84.46 cm3. In patients with positive findings on CT images, the average interval between positive real-time reverse transcriptase polymerase chain reaction assay and peak volume on CT images was 5.1 ± 3.1 days. In conclusion, typical CT findings can be detected in over 70% of asymptomatic SARS-CoV-2 carriers. The initial presentation is typically GGO along the subpleural regions and bronchi, which absorbs in approximately 5 days.