Enhancing Multi-disease Diagnosis of Chest X-rays with Advanced Deep-learning Networks in Real-world Data.

The current artificial intelligence (AI) models are still insufficient in multi-disease diagnosis for real-world data, which always present a long-tail distribution. To tackle this issue, a long-tail public dataset, "ChestX-ray14," which involved fourteen (14) disease labels, was randomly divided into the train, validation, and test sets with ratios of 0.7, 0.1, and 0.2. Two pretrained state-of-the-art networks, EfficientNet-b5 and CoAtNet-0-rw, were chosen as the backbones. After the fully-connected layer, a final layer of 14 sigmoid activation units was added to output each disease's diagnosis. To achieve better adaptive learning, a novel loss (Lours) was designed, which coalesced reweighting and tail sample focus. For comparison, a pretrained ResNet50 network with weighted binary cross-entropy loss (LWBCE) was used as a baseline, which showed the best performance in a previous study. The overall and individual areas under the receiver operating curve (AUROC) for each disease label were evaluated and compared among different models. Group-score-weighted class activation mapping (Group-CAM) is applied for visual interpretations. As a result, the pretrained CoAtNet-0-rw + Lours showed the best overall AUROC of 0.842, significantly higher than ResNet50 + LWBCE (AUROC: 0.811, p = 0.037). Group-CAM presented that the model could pay the proper attention to lesions for most disease labels (e.g., atelectasis, edema, effusion) but wrong attention for the other labels, such as pneumothorax; meanwhile, mislabeling of the dataset was found. Overall, this study presented an advanced AI diagnostic model achieving a significant improvement in the multi-disease diagnosis of chest X-rays, particularly in real-world data with challenging long-tail distributions.

Inhaled Lipid Nanoparticles Alleviate Established Pulmonary Fibrosis.

Pulmonary fibrosis, a sequela of lung injury resulting from severe infection such as severe acute respiratory syndrome-like coronavirus (SARS-CoV-2) infection, is a kind of life-threatening lung disease with limited therapeutic options. Herein, inhalable liposomes encapsulating metformin, a first-line antidiabetic drug that has been reported to effectively reverse pulmonary fibrosis by modulating multiple metabolic pathways, and nintedanib, a well-known antifibrotic drug that has been widely used in the clinic, are developed for pulmonary fibrosis treatment. The composition of liposomes made of neutral, cationic or anionic lipids, and poly(ethylene glycol) (PEG) is optimized by evaluating their retention in the lung after inhalation. Neutral liposomes with suitable PEG shielding are found to be ideal delivery carriers for metformin and nintedanib with significantly prolonged retention in the lung. Moreover, repeated noninvasive aerosol inhalation delivery of metformin and nintedanib loaded liposomes can effectively diminish the development of fibrosis and improve pulmonary function in bleomycin-induced pulmonary fibrosis by promoting myofibroblast deactivation and apoptosis, inhibiting transforming growth factor 1 (TGFß1) action, suppressing collagen formation, and inducing lipogenic differentiation. Therefore, this work presents a versatile platform with promising clinical translation potential for the noninvasive inhalation delivery of drugs for respiratory disease treatment.

Higher socioeconomic status strengthens confidence facing the COVID-19 pandemic for the males rather than females: the predictive role of left hippocampus (preprint)

Socioeconomic status (SES) has a large impact on the way individuals respond to environmental threats. However, less is known about how SES links to personal confidence in confronting COVID-19 and its underlying neural mechanisms. To this end, we assessed self-confidence in coping with pandemic on 606 participants during its peak in China from 21th, February, 2020 to 28th, February, 2020, who underwent magnetic resonance imaging (MRI) scanning before the outbreak from 17th, September, 2019 to 11th, January, 2020. We found that males, rather than females, showed heightened confidence levels as SES increased. Similarly, greater gray matter volumes (GMV) in the left hippocampus, which were identified as SES-related brain correlates using whole-brain voxel-based morphometry (VBM) method, predicted higher confidence level for males, whilst such association was not found among females. Moreover, an independent moderation analysis replicated the predictive role of GMV based on the pre-defined anatomical structure (i.e., left hippocampus). These findings suggested that relative to females, a less threat-biased evaluation style shaped by greater hippocampal volumes might account for the males’ adequate psychological resources for coping with the pandemic. Overall, evidence highlighted the importance to focus on specific populations like females, and people from lower SES in the era of pandemic.

Chest CT Patterns from Diagnosis to 1 Year of Follow-up in Patients with COVID-19.

Background The chest CT manifestations of COVID-19 from hospitalization to convalescence after 1 year are unknown. Purpose To assess chest CT manifestations of COVID-19 up to 1 year after symptom onset. Materials and Methods Patients were enrolled if they were admitted to the hospital because of COVID-19 and underwent CT during hospitalization at two isolation centers between January 27, 2020, and March 31, 2020. In a prospective study, three serial chest CT scans were obtained at approximately 3, 7, and 12 months after symptom onset and were longitudinally analyzed. The total CT score of pulmonary lobe involvement, ranging from 0 to 25, was assessed (score of 1-5 for each lobe). Univariable and multivariable logistic regression analyses were performed to explore independent risk factors for residual CT abnormalities after 1 year. Results A total of 209 study participants (mean age, 49 years ± 13 [standard deviation]; 116 women) were evaluated. CT abnormalities had resolved in 61% of participants (128 of 209) at 3 months and in 75% of participants (156 of 209) at 12 months. Among participants with chest CT abnormalities that had not resolved, there were residual linear opacities in 25 of the 209 participants (12%) and multifocal reticular or cystic lesions in 28 of the 209 participants (13%). Age 50 years or older, lymphopenia, and severe or aggravation of acute respiratory distress syndrome were independent risk factors for residual CT abnormalities at 1 year (odds ratios = 15.9, 18.9, and 43.9, respectively; P < .001 for each comparison). In 53 participants with residual CT abnormalities at 12 months, reticular lesions (41 of 53 participants [77%]) and bronchial dilation (39 of 53 participants [74%]) were observed at discharge and were persistent in 28 (53%) and 24 (45%) of the 53 participants, respectively. Conclusion One year after COVID-19 diagnosis, chest CT scans showed abnormal findings in 53 of the 209 study participants (25%), with 28 of the 209 participants (13%) showing subpleural reticular or cystic lesions. Older participants with severe COVID-19 or acute respiratory distress syndrome were more likely to develop lung sequelae that persisted at 1 year. © RSNA, 2021 Online supplemental material is available for this article. See also the editorial by Lee and Wi et al in this issue.

The association of obesity with the progression and outcome of COVID-19: The insight from an artificial-intelligence-based imaging quantitative analysis on computed tomography.

AIMS: To explore the association of obesity with the progression and outcome of coronavirus disease 2019 (COVID-19) at the acute period and 5-month follow-up from the perspectives of computed tomography (CT) imaging with artificial intelligence (AI)-based quantitative evaluation, which may help to predict the risk of obese COVID-19 patients progressing to severe and critical disease. MATERIALS AND METHODS: This retrospective cohort enrolled 213 hospitalized COVID-19 patients. Patients were classified into three groups according to their body mass index (BMI): normal weight (from 18.5 to <24 kg/m2 ), overweight (from 24 to <28 kg/m2 ) and obesity (≥28 kg/m2 ). RESULTS: Compared with normal-weight patients, patients with higher BMI were associated with more lung involvements in lung CT examination (lung lesions volume [cm3 ], normal weight vs. overweight vs. obesity; 175.5[34.0-414.9] vs. 261.7[73.3-576.2] vs. 395.8[101.6-1135.6]; p = 0.002), and were more inclined to deterioration at the acute period. At the 5-month follow-up, the lung residual lesion was more serious (residual total lung lesions volume [cm3 ], normal weight vs. overweight vs. obesity; 4.8[0.0-27.4] vs. 10.7[0.0-55.5] vs. 30.1[9.5-91.1]; p = 0.015), and the absorption rates were lower for higher BMI patients (absorption rates of total lung lesions volume [%], normal weight vs. overweight vs. obesity; 99.6[94.0-100.0] vs. 98.9[85.2-100.0] vs. 88.5[66.5-95.2]; p = 0.013). The clinical-plus-AI parameter model was superior to the clinical-only parameter model in the prediction of disease deterioration (areas under the ROC curve, 0.884 vs. 0.794, p < 0.05). CONCLUSIONS: Obesity was associated with severe pneumonia lesions on CT and adverse clinical outcomes. The AI-based model with combinational use of clinical and CT parameters had incremental prognostic value over the clinical parameters alone.

Investigation of the impact of SARS-CoV infection on the immunologic status and lung function after 15 years.

BACKGROUND: We investigate the long-term effects of SARS-CoV on patients' lung and immune systems 15 years post-infection. SARS-CoV-2 pandemic is ongoing however, another genetically related beta-coronavirus SARS-CoV caused an epidemic in 2003-2004. METHODS: We enrolled 58 healthcare workers from Peking University People's Hospital who were infected with SARS-CoV in 2003. We evaluated lung damage by mMRC score, pulmonary function tests, and chest CT. Immune function was assessed by their serum levels of globin, complete components, and peripheral T cell subsets. ELISA was used to detect SARS-CoV-specific IgG antibodies in sera. RESULTS: After 15 years of disease onset, 19 (36.5%), 8 (34.6%), and 19 (36.5%) subjects had impaired DL (CO), RV, and FEF25-75, respectively. 17 (30.4%) subjects had an mMRC score ≥ 2. Fourteen (25.5%) cases had residual CT abnormalities. T regulatory cells were a bit higher in the SARS survivors. IgG antibodies against SARS S-RBD protein and N protein were detected in 11 (18.97%) and 12 (20.69%) subjects, respectively. Subgroup analysis revealed that small airway dysfunction and CT abnormalities were more common in the severe group than in the non-severe group (57.1% vs 22.6%, 54.5% vs 6.1%, respectively, p < 0.05). CONCLUSIONS: SARS-CoV could cause permanent damage to the lung, which requires early pulmonary rehabilitation. The long-lived immune memory response against coronavirus requires further studies to assess the potential benefit. Trial registration ClinicalTrials.gov, NCT03443102. Registered prospectively on 25 January 2018.

Correction: Long-term bone and lung consequences associated with hospital-acquired severe acute respiratory syndrome: a 15-year follow-up from a prospective cohort study.

[This corrects the article DOI: 10.1038/s41413-020-0084-5.].

Long-term bone and lung consequences associated with hospital-acquired severe acute respiratory syndrome: a 15-year follow-up from a prospective cohort study.

The most severe sequelae after rehabilitation from SARS are femoral head necrosis and pulmonary fibrosis. We performed a 15-year follow-up on the lung and bone conditions of SARS patients. We evaluated the recovery from lung damage and femoral head necrosis in an observational cohort study of SARS patients using pulmonary CT scans, hip joint MRI examinations, pulmonary function tests and hip joint function questionnaires. Eighty medical staff contracted SARS in 2003. Two patients died of SARS, and 78 were enrolled in this study from August 2003 to March 2018. Seventy-one patients completed the 15-year follow-up. The percentage of pulmonary lesions on CT scans diminished from 2003 (9.40 ± 7.83)% to 2004 (3.20 ± 4.78)% (P < 0.001) and remained stable thereafter until 2018 (4.60 ± 6.37)%. Between 2006 and 2018, the proportion of patients with interstitial changes who had improved pulmonary function was lower than that of patients without lesions, as demonstrated by the one-second ratio (FEV1/FVC%, t = 2.21, P = 0.04) and mid-flow of maximum expiration (FEF25%-75%, t = 2.76, P = 0.01). The volume of femoral head necrosis decreased significantly from 2003 (38.83 ± 21.01)% to 2005 (30.38 ± 20.23)% (P = 0.000 2), then declined slowly from 2005 to 2013 (28.99 ± 20.59)% and plateaued until 2018 (25.52 ± 15.51)%. Pulmonary interstitial damage and functional decline caused by SARS mostly recovered, with a greater extent of recovery within 2 years after rehabilitation. Femoral head necrosis induced by large doses of steroid pulse therapy in SARS patients was not progressive and was partially reversible.

Inhalable nanocatchers for SARS-CoV-2 inhibition.

The global coronavirus disease 2019 (COVID-19) pandemic, caused by severe acute respiratory syndrome (SARS)-like coronavirus (SARS-CoV-2), presents an urgent health crisis. More recently, an increasing number of mutated strains of SARS-CoV-2 have been identified globally. Such mutations, especially those on the spike glycoprotein to render its higher binding affinity to human angiotensin-converting enzyme II (hACE2) receptors, not only resulted in higher transmission of SARS-CoV-2 but also raised serious concerns regarding the efficacies of vaccines against mutated viruses. Since ACE2 is the virus-binding protein on human cells regardless of viral mutations, we design hACE2-containing nanocatchers (NCs) as the competitor with host cells for virus binding to protect cells from SARS-CoV-2 infection. The hACE2-containing NCs, derived from the cellular membrane of genetically engineered cells stably expressing hACE2, exhibited excellent neutralization ability against pseudoviruses of both wild-type SARS-CoV-2 and the D614G variant. To prevent SARS-CoV-2 infections in the lung, the most vulnerable organ for COVID-19, we develop an inhalable formulation by mixing hACE2-containing NCs with mucoadhesive excipient hyaluronic acid, the latter of which could significantly prolong the retention of NCs in the lung after inhalation. Excitingly, inhalation of our formulation could lead to potent pseudovirus inhibition ability in hACE2-expressing mouse model, without imposing any appreciable side effects. Importantly, our inhalable hACE2-containing NCs in the lyophilized formulation would allow long-term storage, facilitating their future clinical use. Thus, this work may provide an alternative tactic to inhibit SARS-CoV-2 infections even with different mutations, exhibiting great potential for treatment of the ongoing COVID-19 epidemic.

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.

Facing coronavirus disease 2019: What do we know so far? (Review).

Although the World Health Organization declared the outbreak of coronavirus disease 2019 (COVID-19), which originated in China, as a public health emergency of international concern as early as January 30, 2020, the current COVID-19 epidemic is spreading rapidly. As of April 19, 2020, total of 2,392,165 confirmed cases had been reported in 211 countries and regions, with 614,421 (25.68%) cured cases and 164,391 (6.87%) deaths. Scientists and clinicians have made great efforts to learn much about COVID-19 so that it can be controlled as soon as possible. Herein, this review will discuss the epidemiology, pathology, clinical features, diagnosis and treatment of COVID-19 based on the current evidence.

A novel deep learning-based quantification of serial chest computed tomography in Coronavirus Disease 2019 (COVID-19).

This study aims to explore and compare a novel deep learning-based quantification with the conventional semi-quantitative computed tomography (CT) scoring for the serial chest CT scans of COVID-19. 95 patients with confirmed COVID-19 and a total of 465 serial chest CT scans were involved, including 61 moderate patients (moderate group, 319 chest CT scans) and 34 severe patients (severe group, 146 chest CT scans). Conventional CT scoring and deep learning-based quantification were performed for all chest CT scans for two study goals: (1) Correlation between these two estimations; (2) Exploring the dynamic patterns using these two estimations between moderate and severe groups. The Spearman's correlation coefficient between these two estimation methods was 0.920 (p < 0.001). predicted pulmonary involvement (CT score and percent of pulmonary lesions calculated using deep learning-based quantification) increased more rapidly and reached a higher peak on 23rd days from symptom onset in severe group, which reached a peak on 18th days in moderate group with faster absorption of the lesions. The deep learning-based quantification for COVID-19 showed a good correlation with the conventional CT scoring and demonstrated a potential benefit in the estimation of disease severities of COVID-19.

Glycemic status affects the severity of coronavirus disease 2019 in patients with diabetes mellitus: an observational study of CT radiological manifestations using an artificial intelligence algorithm.

AIMS: Increasing evidence suggests that poor glycemic control in diabetic individuals is associated with poor coronavirus disease 2019 (COVID-19) pneumonia outcomes and influences chest computed tomography (CT) manifestations. This study aimed to explore the impact of diabetes mellitus (DM) and glycemic control on chest CT manifestations, acquired using an artificial intelligence (AI)-based quantitative evaluation system, and COVID-19 disease severity and to investigate the association between CT lesions and clinical outcome. METHODS: A total of 126 patients with COVID-19 were enrolled in this retrospective study. According to their clinical history of DM and glycosylated hemoglobin (HbA1c) level, the patients were divided into 3 groups: the non-DM group (Group 1); the well-controlled blood glucose (BG) group, with HbA1c < 7% (Group 2); and the poorly controlled BG group, with HbA1c ≥ 7% (Group 3). The chest CT images were analyzed with an AI-based quantitative evaluation system. Three main quantitative CT features representing the percentage of total lung lesion volume (PLV), percentage of ground-glass opacity volume (PGV) and percentage of consolidation volume (PCV) in bilateral lung fields were used to evaluate the severity of pneumonia lesions. RESULTS: Patients in Group 3 had the highest percentage of severe or critical illness, with 12 (32%) cases, followed by 6 (11%) and 7 (23%) cases in Groups 1 and 2, respectively (p = 0.042). The composite endpoints, including death or using mechanical ventilation or admission to the intensive care unit (ICU), were 3 (5%), 5 (16%) and 10 (26%) in Groups 1, 2 and 3, respectively (p = 0.013). The PLV, PGV and PCV in bilateral lung fields were significantly different among the three groups (all p < 0.001): the median PLVs were 12.5% (Group 3), 3.8% (Group 2) and 2.4% (Group 1); the median PGVs were 10.2% (Group 3), 3.6% (Group 2) and 1.9% (Group 1); and the median PCVs were 1.8% (Group 3), 0.3% (Group 2) and 0.1% (Group 1). In the linear regression analyses, which were adjusted for age, sex, BMI, and comorbidities, HbA1c remained positively associated with PLV (ß = 0.401, p < 0.001), PGV (ß = 0.364, p = 0.001) and PCV (ß = 0.472, p < 0.001); this relationship was also observed between fasting blood glucose (FBG) and the three CT quantitative parameters. In the logistic regression analyses, PLV [OR 1.067 (1.032, 1.103)], PGV [OR 1.076 (1.034, 1.120)] and PCV [OR 1.280 (1.110, 1.476)] levels were independent predictors of the composite endpoints, as well as the areas under the ROC (AUCs) for PLV [AUC 0.796 (0.691, 0.900)], PGV [AUC 0.783 (0.678, 0.889)] and PCV [AUC 0.816 (0.722, 0.911)]; the ORs were still significant for CT lesions after adjusting for age, sex and poorly controlled diabetes. CONCLUSIONS: Increased blood glucose level was correlated with the severity of lung involvement, as evidenced by certain chest CT parameters, and clinical prognosis in diabetic COVID-19 patients. There was a positive correlation between blood glucose level (both HbA1c and FBG) on admission and lung lesions. Moreover, the CT lesion severity by AI quantitative analysis was correlated with clinical outcomes.

Impaired spermatogenesis in COVID-19 patients.

BACKGROUND: The current study aimed to determine the impact of SARS-CoV-2 infection on male fertility. METHODS: This is a single-center, hospital-based observational study that included autopsied testicular and epididymal specimens of deceased COVID-19 male patients (n=6) and recruited recovering COVID-19 inpatients (n=23) with an equal number of age-matched controls, respectively. We performed histopathological examinations on testicular and epididymal specimens, and also performed TUNEL assay and immunohistochemistry. Whereas, we investigated the semen specimen for sperm parameters and immune factors. FINDINGS: Autopsied testicular and epididymal specimens of COVID-19 showed the presence of interstitial edema, congestion, red blood cell exudation in testes, and epididymides. Thinning of seminiferous tubules was observed. The number of apoptotic cells within seminiferous tubules was significantly higher in COVID-19 compared to control cases. It also showed an increased concentration of CD3+ and CD68+ in the interstitial cells of testicular tissue and the presence of IgG within seminiferous tubules. Semen from COVID-19 inpatients showed that 39.1% (n=9) of them have oligozoospermia, and 60.9% (n=14) showed a significant increase in leucocytes in semen. Decreased sperm concentration, and increased seminal levels of IL-6, TNF-α, and MCP-1 compared to control males were observed. INTERPRETATION: Impairment of spermatogenesis was observed in COVID-19 patients, which could be partially explained as a result of an elevated immune response in testis. Additionally, autoimmune orchitis occurred in some COVID-19 patients. Further research on the reversibility of impairment and developing treatment are warranted. FUNDING: This study was supported by Ministry of Science and Technology of China Plan, Hubei Science and Technology Plan, National Key Research and Development Program of China, HUST COVID-19 Rapid Response Call, China and National Natural Science Foundation of China; these funding bodies are public institutions, and they had no role in study conception, design, interpretation of results, and manuscript preparation.

Spontaneous pneumothorax and subpleural bullae in a patient with COVID-19: a 92-day observation.

This report describes a patient with COVID-19 who developed spontaneous pneumothorax and subpleural bullae during the course of the infection. Consecutive chest computed tomography images indicated that COVID-19-associated pneumonia had damaged the subpleural alveoli and distal bronchus. Coughing might have induced a sudden increase in intra-alveolar pressure, leading to the rupture of the subpleural alveoli and distal bronchus and resulting in spontaneous pneumothorax and subpleural bullae. At the 92-day follow-up, the pneumothorax and subpleural bullae had completely resolved, which indicated that these complications had self-limiting features.

Different computed tomography patterns of Coronavirus Disease 2019 (COVID-19) between survivors and non-survivors.

This study aimed to compare the chest computed tomography (CT) findings between survivors and non-survivors with Coronavirus Disease 2019 (COVID-19). Between 12 January 2020 and 20 February 2020, the records of 124 consecutive patients diagnosed with COVID-19 were retrospectively reviewed and divided into survivor (83/124) and non-survivor (41/124) groups. Chest CT findings were qualitatively compared on admission and serial chest CT scans were semi-quantitively evaluated between two groups using curve estimations. On admission, significantly more bilateral (97.6% vs. 73.5%, p = 0.001) and diffuse lesions (39.0% vs. 8.4%, p < 0.001) with higher total CT score (median 10 vs. 4, p < 0.001) were observed in non-survivor group compared with survivor group. Besides, crazy-paving pattern was more predominant in non-survivor group than survivor group (39.0% vs. 12.0%, p < 0.001). From the prediction of curve estimation, in survivor group total CT score increased in the first 20 days reaching a peak of 6 points and then gradually decreased for more than other 40 days (R2 = 0.545, p < 0.001). In non-survivor group, total CT score rapidly increased over 10 points in the first 10 days and gradually increased afterwards until ARDS occurred with following death events (R2 = 0.711, p < 0.001). In conclusion, persistent progression with predominant crazy-paving pattern was the major manifestation of COVID-19 in non-survivors. Understanding this CT feature could help the clinical physician to predict the prognosis of the patients.

Factors associated with death outcome in patients with severe coronavirus disease-19 (COVID-19): a case-control study.

Rationale: Up to date, the exploration of clinical features in severe COVID-19 patients were mostly from the same center in Wuhan, China. The clinical data in other centers is limited. This study aims to explore the feasible parameters which could be used in clinical practice to predict the prognosis in hospitalized patients with severe coronavirus disease-19 (COVID-19). Methods: In this case-control study, patients with severe COVID-19 in this newly established isolation center on admission between 27 January 2020 to 19 March 2020 were divided to discharge group and death event group. Clinical information was collected and analyzed for the following objectives: 1. Comparisons of basic characteristics between two groups; 2. Risk factors for death on admission using logistic regression; 3. Dynamic changes of radiographic and laboratory parameters between two groups in the course. Results: 124 patients with severe COVID-19 on admission were included and divided into discharge group (n=35) and death event group (n=89). Sex, SpO2, breath rate, diastolic pressure, neutrophil, lymphocyte, C-reactive protein (CRP), procalcitonin (PCT), lactate dehydrogenase (LDH), and D-dimer were significantly correlated with death events identified using bivariate logistic regression. Further multivariate logistic regression demonstrated a significant model fitting with C-index of 0.845 (p<0.001), in which SpO2≤89%, lymphocyte≤0.64×109/L, CRP>77.35mg/L, PCT>0.20µg/L, and LDH>481U/L were the independent risk factors with the ORs of 2.959, 4.015, 2.852, 3.554, and 3.185, respectively (p<0.04). In the course, persistently lower lymphocyte with higher levels of CRP, PCT, IL-6, neutrophil, LDH, D-dimer, cardiac troponin I (cTnI), brain natriuretic peptide (BNP), and increased CD4+/CD8+ T-lymphocyte ratio and were observed in death events group, while these parameters stayed stable or improved in discharge group. Conclusions: On admission, the levels of SpO2, lymphocyte, CRP, PCT, and LDH could predict the prognosis of severe COVID-19 patients. Systematic inflammation with induced cardiac dysfunction was likely a primary reason for death events in severe COVID-19 except for acute respiratory distress syndrome.

Association of clinical and radiographic findings with the outcomes of 93 patients with COVID-19 in Wuhan, China.

Rationale: To retrospectively analyze serial chest CT and clinical features in patients with coronavirus disease 2019 (COVID-19) for the assessment of temporal changes and to investigate how the changes differ in survivors and nonsurvivors. Methods: The consecutive records of 93 patients with confirmed COVID-19 who were admitted to Wuhan Union Hospital from January 10, 2020, to February 22, 2020, were retrospectively reviewed. A series of chest CT findings and clinical data were collected and analyzed. The serial chest CT scans were scored on a semiquantitative basis according to the extent of pulmonary abnormalities. Chest CT scores in different periods (0 - 5 days, 6 - 10 days, 11 - 15 days, 16 - 20 days, and > 20 days) since symptom onset were compared between survivors and nonsurvivors, and the temporal trend of the radiographic-clinical features was analyzed. Results: The final cohort consisted of 93 patients: 68 survivors and 25 nonsurvivors. Nonsurvivors were significantly older than survivors. For both survivors and nonsurvivors, the chest CT scores were not different in the first period (0 - 5 days) but diverged afterwards. The mortality rate of COVID-19 monotonously increased with chest CT scores, which positively correlated with the neutrophil-to-lymphocyte ratio, neutrophil percentage, D-dimer level, lactate dehydrogenase level and erythrocyte sedimentation rate, while negatively correlated with the lymphocyte percentage and lymphocyte count. Conclusions: Chest CT scores correlate well with risk factors for mortality over periods, thus they may be used as a prognostic indicator in COVID-19. While higher chest CT scores are associated with a higher mortality rate, CT images taken at least 6 days since symptom onset may contain more prognostic information than images taken at an earlier period.

No evidence of severe acute respiratory syndrome-coronavirus 2 in semen of males recovering from coronavirus disease 2019.

OBJECTIVE: To describe detection of severe acute respiratory syndrome (SARS)-coronavirus 2 (CoV-2) in seminal fluid of patients recovering from coronavirus disease 2019 (COVID-19) and to describe the expression profile of angiotensin-converting enzyme 2 (ACE2) and Transmembrane Serine Protease 2 (TMPRSS2) within the testicle. DESIGN: Observational, cross-sectional study. SETTING: Tertiary referral center. PATIENT(S): Thirty-four adult Chinese males diagnosed with COVID-19 through confirmatory quantitative reverse transcriptase-polymerase chain reaction (qRT-PCR) from pharyngeal swab samples. INTERVENTION(S): None. MAIN OUTCOME MEASURE(S): Identification of SARS-CoV-2 on qRT-PCR of single ejaculated semen samples. Semen quality was not assessed. Expression patterns of ACE2 and TMPRSS2 in the human testis are explored through previously published single-cell transcriptome datasets. RESULT(S): Six patients (19%) demonstrated scrotal discomfort suggestive of viral orchitis around the time of COVID-19 confirmation. Severe acute respiratory syndrome-CoV-2 was not detected in semen after a median of 31 days (interquartile range, 29-36 days) from COVID-19 diagnosis. Single-cell transcriptome analysis demonstrates sparse expression of ACE2 and TMPRSS2, with almost no overlapping gene expression. CONCLUSION(S): Severe acute respiratory syndrome-CoV-2 was not detected in the semen of patients recovering from COVID-19 1 month after COVID-19 diagnosis. Angiotensin-converting enzyme 2-mediated viral entry of SARS-CoV-2 into target host cells is unlikely to occur within the human testicle based on ACE2 and TMPRSS2 expression. The long-term effects of SARS-CoV-2 on male reproductive function remain unknown.

Time Course of Lung Changes at Chest CT during Recovery from Coronavirus Disease 2019 (COVID-19).

Background Chest CT is used to assess the severity of lung involvement in coronavirus disease 2019 (COVID-19). Purpose To determine the changes in chest CT findings associated with COVID-19 from initial diagnosis until patient recovery. Materials and Methods This retrospective review included patients with real-time polymerase chain reaction-confirmed COVID-19 who presented between January 12, 2020, and February 6, 2020. Patients with severe respiratory distress and/or oxygen requirement at any time during the disease course were excluded. Repeat chest CT was performed at approximately 4-day intervals. Each of the five lung lobes was visually scored on a scale of 0 to 5, with 0 indicating no involvement and 5 indicating more than 75% involvement. The total CT score was determined as the sum of lung involvement, ranging from 0 (no involvement) to 25 (maximum involvement). Results Twenty-one patients (six men and 15 women aged 25-63 years) with confirmed COVID-19 were evaluated. A total of 82 chest CT scans were obtained in these patients, with a mean interval (±standard deviation) of 4 days ± 1 (range, 1-8 days). All patients were discharged after a mean hospitalization period of 17 days ± 4 (range, 11-26 days). Maximum lung involved peaked at approximately 10 days (with a calculated total CT score of 6) from the onset of initial symptoms (R2 = 0.25, P < .001). Based on quartiles of chest CT scans from day 0 to day 26 involvement, four stages of lung CT findings were defined. CT scans obtained in stage 1 (0-4 days) showed ground-glass opacities (18 of 24 scans [75%]), with a mean total CT score of 2 ± 2; scans obtained in stage 2 (5-8 days) showed an increase in both the crazy-paving pattern (nine of 17 scans [53%]) and total CT score (mean, 6 ± 4; P = .002); scans obtained in stage 3 (9-13 days) showed consolidation (19 of 21 scans [91%]) and a peak in the total CT score (mean, 7 ± 4); and scans obtained in stage 4 (≥14 days) showed gradual resolution of consolidation (15 of 20 scans [75%]) and a decrease in the total CT score (mean, 6 ± 4) without crazy-paving pattern. Conclusion In patients recovering from coronavirus disease 2019 (without severe respiratory distress during the disease course), lung abnormalities on chest CT scans showed greatest severity approximately 10 days after initial onset of symptoms. © RSNA, 2020.