Well-Aerated Lung and Mean Lung Density Quantified by CT at Discharge to Predict Pulmonary Diffusion Function 5 Months after COVID-19.

Background: The aim of this study was to explore the predictive values of quantitative CT indices of the total lung and lung lobe tissue at discharge for the pulmonary diffusion function of coronavirus disease 2019 (COVID-19) patients at 5 months after symptom onset. Methods: A total of 90 patients with moderate and severe COVID-19 underwent CT scans at discharge, and pulmonary function tests (PFTs) were performed 5 months after symptom onset. The differences in quantitative CT and PFT results between Group 1 (patients with abnormal diffusion function) and Group 2 (patients with normal diffusion function) were compared by the chi-square test, Fisher's exact test or Mann−Whitney U test. Univariate analysis, stepwise linear regression and logistic regression were used to determine the predictors of diffusion function in convalescent patients. Results: A total of 37.80% (34/90) of patients presented diffusion dysfunction at 5 months after symptom onset. The mean lung density (MLD) of the total lung tissue in Group 1 was higher than that in Group 2, and the percentage of the well-aerated lung (WAL) tissue volume (WAL%) of Group 1 was lower than that of Group 2 (all p < 0.05). Multiple stepwise linear regression identified only WAL and WAL% of the left upper lobe (LUL) as parameters that positively correlated with the percent of the predicted value of diffusion capacity of the lungs for carbon monoxide (WAL: p = 0.002; WAL%: p = 0.004), and multiple stepwise logistic regression identified MLD and MLDLUL as independent predictors of diffusion dysfunction (MLD: OR (95%CI): 1.011 (1.001, 1.02), p = 0.035; MLDLUL: OR (95%CI): 1.016 (1.004, 1.027), p = 0.008). Conclusion: At five months after symptom onset, more than one-third of moderate and severe COVID-19 patients presented with diffusion dysfunction. The well-aerated lung and mean lung density quantified by CT at discharge could be predictors of diffusion function in convalesce.

Association of anemia and COVID-19 in hospitalized patients.

Aim: COVID-19 is a major threat to public health worldwide. A large proportion of COVID-19 patients is proved to develop anemia. Herein, we investigate the association between anemia and severe pneumonia. Materials & methods: 137 of COVID-19-confirmed patients admitted to Wuhan Union Hospital (Wuhan, China) from 13 February to 17 March 2020 were included. Their clinical characteristics and laboratory data were studied, and multivariable logistic regression analyses were performed. Results: The anemic patients were less likely to develop fever in the early stage of COVID-19. Elevated IL-6 levels were found in anemic COVID-19 patients compared with those without anemia. COVID-19 patients with anemia had an 8.2 times greater possibility of developing severe pneumonia compared with their counterparts without anemia. Conclusion: This study comprehensively describes the clinical characteristics of anemic patients with ordinary, severe and critical COVID-19 and demonstrates the close relationship between the anemia and severe COVID-19.

Total Lung and Lobar Quantitative Assessment Based on Paired Inspiratory-Expiratory Chest CT in Healthy Adults: Correlation with Pulmonary Ventilatory Function.

OBJECTIVE: To provide the quantitative volumetric data of the total lung and lobes in inspiration and expiration from healthy adults, and to explore the value of paired inspiratory-expiratory chest CT scan in pulmonary ventilatory function and further explore the influence of each lobe on ventilation. METHODS: A total of 65 adults (29 males and 36 females) with normal clinical pulmonary function test (PFT) and paired inspiratory-expiratory chest CT scan were retrospectively enrolled. The inspiratory and expiratory volumetric indexes of the total lung (TL) and 5 lobes (left upper lobe [LUL], left lower lobe [LLL], right upper lobe [RUL], right middle lobe [RML], and right lower lobe [RLL]) were obtained by Philips IntelliSpace Portal image postprocessing workstation, including inspiratory lung volume (LVin), expiratory lung volume (LVex), volume change (∆LV), and well-aerated lung volume (WAL, lung tissue with CT threshold between -950 and -750 HU in inspiratory scan). Spearman correlation analysis was used to explore the correlation between CT quantitative indexes of the total lung and ventilatory function indexes (including total lung capacity [TLC], residual volume [RV], and force vital capacity [FVC]). Multiple stepwise regression analysis was used to explore the influence of each lobe on ventilation. RESULTS: At end-inspiratory phase, the LVin-TL was 4664.6 (4282.7, 5916.2) mL, the WALTL was 4173 (3639.6, 5250.9) mL; both showed excellent correlation with TLC (LVin-TL: r = 0.890, p < 0.001; WALTL: r = 0.879, p < 0.001). From multiple linear regression analysis with lobar CT indexes as variables, the LVin and WAL of these two lobes, LLL and RUL, showed a significant relationship with TLC. At end-expiratory phase, the LVex-TL was 2325.2 (1969.7, 2722.5) mL with good correlation with RV (r = 0.811, p < 0.001), of which the LVex of RUL and RML had a significant relationship with RV. For the volumetric change within breathing, the ∆LVTL was 2485.6 (2169.8, 3078.1) mL with good correlation with FVC (r = 0.719, p < 0.001), moreover, WALTL showed a better correlation with FVC (r = 0.817, p < 0.001) than that of ∆LVTL. Likewise, there was also a strong association between ∆LV, WAL of these two lobes (LLL and RUL), and FVC. CONCLUSIONS: The quantitative indexes derived from paired inspiratory-expiratory chest CT could reflect the clinical pulmonary ventilatory function, LLL, and RUL give greater impact on ventilation. Thus, the pulmonary functional evaluation needs to be more precise and not limited to the total lung level.

Characteristics of mental health implications and plasma metabolomics in patients recently recovered from COVID-19.

This study aimed to explore the associations between cerebral white matter (WM) alterations, mental health status, and metabolism in recovered COVID-19 patients. We included 28 recovered COVID-19 patients and 27 healthy controls between April 2020 and June 2020. Demographic data, the mental health scores, diffusion-tensor imaging (DTI) data, and plasma metabolomics were collected and compared between the two groups. Tract-based spatial statistics and graph theory approaches were used for DTI data analysis. Untargeted metabolomics analysis of the plasma was performed. Correlation analyses were performed between these characteristics. Recovered COVID-19 patients showed decreased fractional anisotropy, increased mean diffusivity and radial diffusivity values in widespread brain regions, and significantly lower global efficiency, longer shortest path length, and less nodal local efficiency in superior occipital gyrus (all, P < 0.05, Bonferroni corrected). Our results also demonstrated significantly different plasma metabolic profiling in recovered COVID-19 patients even at 3 months after their hospital discharge, which was mainly related to purine pathways, amino acids, lipids, and amine metabolism. Certain regions with cerebral WM alterations in the recovered patients showed significant correlations with different metabolites and the mental health scores. We observed multiple alterations in both WM integrity and plasma metabolomics that may explain the deteriorated mental health of recovered COVID-19 patients. These findings may provide potential biomarkers for the mental health evaluation for the recovered COVID-19 patients and potential targets for novel therapeutics.

Corrigendum: Online Mental Health Survey in a Medical College in China During the COVID-19 Outbreak.

[This corrects the article DOI: 10.3389/fpsyt.2020.00459.].

Online Mental Health Survey in a Medical College in China During the COVID-19 Outbreak.

Background: The outbreak of coronavirus disease 2019 (COVID-19) in Wuhan, Hubei province, has led to the quarantine of many residents in their homes, in order to mitigate its spread. Some of these people developed mental health problems, and many solutions have been put in place to address the mental health issues of patients and health professionals affected by the disease. However, not much attention has been given to students, particularly those from medical school. The present study aims to conduct an online survey to investigate the mental health status of students from a medical college in Hubei province. Materials and Methods: The WeChat-based survey program Questionnaire Star, which contained questions from Patient Health Questionnaire-9 (PHQ-9) and Generalized Anxiety Disorder-7 (GAD-7), was utilized for the present study. Results: A total of 217 students participated in the survey. Among these students, 127 were female and 90 were male. Furthermore, 77 students (35.5%) who participated in the survey were in a state of depression, and 48 (22.1%) were in a state of anxiety. The majority of students who were in depressed (n=75) or anxiety (n=46) states had mild or moderate states. There were no significant differences in students in terms of gender, geographical location, and grade, for the prevalence of depression and anxiety. Conclusion: The present study implies that universities need to take measures to prevent, identify, and deal with mental health problems among students during large-scale stressors.