Genetic predisposition to subjective well-being, depression, and suicide in relation to COVID-19 susceptibility and severity.

BACKGROUND: Epidemiological studies have reported associations between subjective well-being (SWB), depression, and suicide with COVID-19 illness, but the causality has not been established. We performed a two-sample Mendelian randomization (MR) analysis to investigate the causal link between SWB, depression, suicide and COVID-19 susceptibility and severity. METHODS: Summary statistics for SWB (298,420 cases), depression (113,769 cases) and suicide (52,208 cases) were obtained from three large-scale GWAS. Data on the associations between the Single Nucleotide Polymorphisms (SNPs) and COVID-19 (159,840 cases), hospitalized COVID-19 (44,986 cases), and severe COVID-19 (18,152 cases) were collected from the COVID-19 host genetics initiative. The causal estimate was calculated by the Inverse Variance Weighted, MR Egger and Weighted Median methods. Sensitivity tests were used to evaluate the validity of the causal relationship. RESULTS: Our results showed that genetically predicted SWB (OR = 0.98, 95 % CI: 0.86-1.10, P = 0.69), depression (OR = 0.76, 95 % CI: 0.54-1.06, P = 0.11), and suicide (OR = 0.99, 95 % CI: 0.96-1.02, P = 0.56) were not causally related to COVID-19 susceptibility. Similarly, we did not find a potential causal relationship between SWB, depression, suicide and COVID-19 severity. CONCLUSIONS: This indicated that positive or negative emotions would not make COVID-19 better or worse, and strategies that attempted to use positive emotions to improve COVID-19 symptoms may be useless. Improving knowledge about the SARS-CoV-2 and timely medical intervention to reduce panic during a pandemic is one of the effective measures to deal with the current decrease in well-being and increase in depression and suicide rates.

Symptom Burden among Older COVID-19 Survivors Two Years after Hospital Discharge.

To study the long-term symptom burden among older COVID-19 survivors 2 years after hospital discharge and identify associated risk factors. The current cohort study included COVID-19 survivors aged 60 years and above, who were discharged between February 12 and April 10, 2020, from two designated hospitals in Wuhan, China. All patients were contacted via telephone and completed a standardized questionnaire assessing self-reported symptoms, the Checklist Individual Strength (CIS)-fatigue subscale, and two subscales of the Hospital Anxiety and Depression Scale (HADS). Of the 1,212 patients surveyed, the median (IQR) age was 68.0 (64.0-72.0), and 586 (48.3%) were male. At the two-year follow-up, 259 patients (21.4%) still reported at least one symptom. The most frequently self-reported symptoms were fatigue, anxiety, and dyspnea. Fatigue or myalgia, which was the most common symptom cluster (11.8%; 143/1212), often co-occurred with anxiety and chest symptoms. A total of 89 patients (7.7%) had CIS-fatigue scores ≥ 27, with older age (odds ratio [OR], 1.08; 95% CI: 1.05-1.11, P < 0.001) and oxygen therapy (OR, 2.19; 95% CI: 1.06-4.50, P= 0.03) being risk factors. A total of 43 patients (3.8%) had HADS-Anxiety scores ≥ 8, and 130 patients (11.5%) had HADS-Depression scores ≥ 8. For the 59 patients (5.2%) who had HADS total scores ≥ 16, older age, serious illness during hospitalization and coexisting cerebrovascular diseases were risk factors. Cooccurring fatigue, anxiety, and chest symptoms, as well as depression, were mainly responsible for long-term symptom burden among older COVID-19 survivors 2 years after discharge.

SS-TBN: A Semi-Supervised Tri-Branch Network for COVID-19 Screening and Lesion Segmentation.

Insufficient annotated data and minor lung lesions pose big challenges for computed tomography (CT)-aided automatic COVID-19 diagnosis at an early outbreak stage. To address this issue, we propose a Semi-Supervised Tri-Branch Network (SS-TBN). First, we develop a joint TBN model for dual-task application scenarios of image segmentation and classification such as CT-based COVID-19 diagnosis, in which pixel-level lesion segmentation and slice-level infection classification branches are simultaneously trained via lesion attention, and individual-level diagnosis branch aggregates slice-level outputs for COVID-19 screening. Second, we propose a novel hybrid semi-supervised learning method to make full use of unlabeled data, combining a new double-threshold pseudo labeling method specifically designed to the joint model and a new inter-slice consistency regularization method specifically tailored to CT images. Besides two publicly available external datasets, we collect internal and our own external datasets including 210,395 images (1,420 cases versus 498 controls) from ten hospitals. Experimental results show that the proposed method achieves state-of-the-art performance in COVID-19 classification with limited annotated data even if lesions are subtle, and that segmentation results promote interpretability for diagnosis, suggesting the potential of the SS-TBN in early screening in insufficient labeled data situations at the early stage of a pandemic outbreak like COVID-19.

Two-Year Health Outcomes in Hospitalized COVID-19 Survivors in China.

Importance: Relatively little is known about the persistence of symptoms in patients with COVID-19 for more than 1 year after their acute illness. Objective: To assess the health outcomes among hospitalized COVID-19 survivors over 2 years and to identify factors associated with increased risk of persistent symptoms. Design, Setting, and Participants: This was a longitudinal cohort study of patients who survived COVID-19 at 2 COVID-19-designated hospitals in Wuhan, China, from February 12 to April 10, 2020. All patients were interviewed via telephone at 1 year and 2 years after discharge. The 2-year follow-up study was conducted from March 1 to April 6, 2022. Statistical analysis was conducted from April 20 to May 5, 2022. The severity of disease was defined by World Health Organization guideline for COVID-19. Exposures: COVID-19. Main Outcomes and Measures: The main outcome was symptom changes over 2 years after hospital discharge. All patients completed a symptom questionnaire for evaluation of symptoms, along with a chronic obstructive pulmonary disease assessment test (CAT) at 1-year and 2-year follow-up visits. Results: Of 3988 COVID-19 survivors, a total of 1864 patients (median [IQR] age, 58.5 [49.0-68.0] years; 926 male patients [49.7%]) were available for both 1-year and 2-year follow-up visits. The median (IQR) time from discharge to follow-up at 2 years was 730 (719-743) days. At 2 years after hospital discharge, 370 patients (19.8%) still had symptoms, including 224 (12.0%) with persisting symptoms and 146 (7.8%) with new-onset or worsening of symptoms. The most common symptoms were fatigue, chest tightness, anxiety, dyspnea, and myalgia. Most symptoms resolved over time, but the incidence of dyspnea showed no significant change (1-year vs 2-year, 2.6% [49 patients] vs 2.0% [37 patients]). A total of 116 patients (6.2%) had CAT total scores of at least 10 at 2 years after discharge. Patients who had been admitted to the intensive care unit had higher risks of persistent symptoms (odds ratio, 2.69; 95% CI, 1.02-7.06; P = .04) and CAT scores of 10 or higher (odds ratio, 2.83; 95% CI, 1.21-6.66; P = .02). Conclusions and Relevance: In this cohort study, 2 years after hospital discharge, COVID-19 survivors had a progressive decrease in their symptom burden, but those with severe disease during hospitalization, especially those who required intensive care unit admission, had higher risks of persistent symptoms. These results are related to the original strain of the virus, and their relevance to infections with the Omicron variant is not known.

RNA-Seq Analysis Reveals an Essential Role of the Tyrosine Metabolic Pathway and Inflammation in Myopia-Induced Retinal Degeneration in Guinea Pigs.

Myopia is the second leading cause of visual impairment globally. Myopia can induce sight-threatening retinal degeneration and the underlying mechanism remains poorly defined. We generated a model of myopia-induced early-stage retinal degeneration in guinea pigs and investigated the mechanism of action. Methods: The form-deprivation-induced myopia (FDM) was induced in the right eyes of 2~3-week-old guinea pigs using a translucent balloon for 15 weeks. The left eye remained untreated and served as a self-control. Another group of untreated age-matched animals was used as naïve controls. The refractive error and ocular biometrics were measured at 3, 7, 9, 12 and 15 weeks post-FDM induction. Visual function was evaluated by electroretinography. Retinal neurons and synaptic structures were examined by confocal microscopy of immunolabelled retinal sections. The total RNAs were extracted from the retinas and processed for RNA sequencing analysis. Results: The FDM eyes presented a progressive axial length elongation and refractive error development. After 15 weeks of intervention, the average refractive power was -3.40 ± 1.85 D in the FDM eyes, +2.94 ± 0.59 D and +2.69 ± 0.56 D in the self-control and naïve control eyes, respectively. The a-wave amplitude was significantly lower in FDM eyes and these eyes had a significantly lower number of rods, secretagogin+ bipolar cells, and GABAergic amacrine cells in selected retinal areas. RNA-seq analysis showed that 288 genes were upregulated and 119 genes were downregulated in FDM retinas compared to naïve control retinas. In addition, 152 genes were upregulated and 12 were downregulated in FDM retinas compared to self-control retinas. The KEGG enrichment analysis showed that tyrosine metabolism, ABC transporters and inflammatory pathways were upregulated, whereas tight junction, lipid and glycosaminoglycan biosynthesis were downregulated in FDM eyes. Conclusions: The long-term (15-week) FDM in the guinea pig models induced an early-stage retinal degeneration. The dysregulation of the tyrosine metabolism and inflammatory pathways may contribute to the pathogenesis of myopia-induced retinal degeneration.

The way of SARS-CoV-2 vaccine development: success and challenges.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the causative agent of coronavirus disease 2019 (COVID-19). To halt the pandemic, multiple SARS-CoV-2 vaccines have been developed and several have been allowed for emergency use and rollout worldwide. With novel SARS-CoV-2 variants emerging and circulating widely, whether the original vaccines that were designed based on the wild-type SARS-CoV-2 were effective against these variants has been a contentious discussion. Moreover, some studies revealed the long-term changes of immune responses post SARS-CoV-2 infection or vaccination and the factors that might impact the vaccine-induced immunity. Thus, in this review, we have summarized the influence of mutational hotspots on the vaccine efficacy and characteristics of variants of interest and concern. We have also discussed the reasons that might result in discrepancies in the efficacy of different vaccines estimated in different trials. Furthermore, we provided an overview of the duration of immune responses after natural infection or vaccination and shed light on the factors that may affect the immunity induced by the vaccines, such as special disease conditions, sex, and pre-existing immunity, with the aim of aiding in combating COVID-19 and distributing SARS-CoV-2 vaccines under the prevalence of diverse SARS-CoV-2 variants.

Myoglobin Offers Higher Accuracy Than Other Cardiac-Specific Biomarkers for the Prognosis of COVID-19.

Although sporadic studies have shown that myoglobin may have better prognostic performance than other cardiac markers in COVID-19, a comprehensive comparative study is lacking. Herein, we retrospectively analyzed the clinical and laboratory data of COVID-19 patients admitted to the Guanggu Campus of Wuhan Tongji Hospital from February 9, 2020 to March 30, 2020, intending to compare the prognostic accuracy of three commonly used cardiac markers on COVID-19 mortality. Our results revealed that abnormal increases in myocardial biomarkers were associated with a significantly increased risk of in-hospital mortality with COVID-19. Interestingly, myoglobin, a non-cardiac-specific biomarker, also expressed in skeletal myocytes, had even higher prognostic accuracy than cardiac-specific biomarkers such as high-sensitivity troponin I (hs-TnI) and creatine kinase-MB (CK-MB). More importantly, multivariate Cox analysis showed that myoglobin, rather than hs-TnI or CK-MB, was independently prognostic for in-hospital mortality in COVID-19. These results were further confirmed by subgroup analyses of patients with severe and critical illnesses and those without a history of cardiovascular disease. Our findings suggest that myoglobin may be a reliable marker of illness reflecting general physiological disturbance and help to assess prognosis and treatment response in patients with COVID-19.

Health-Related Quality of Life and Influencing Factors of Pediatric Medical Staff During the COVID-19 Outbreak.

Objective: To evaluate the health-related quality of life (HRQoL) status and explore its associated factors in pediatric medical staff during the COVID-19 epidemic so as to provide fundamental evidence for clinicians and administrators to formulate targeted intervention measures to improve the HRQoL and mental health status in pediatric medical staff during this, and future pandemics. Methods: A cross-sectional study was conducted to investigate the HRQoL of pediatric medical staff. Univariable and multivariable logistic regression were used to analyze the associated factors. Results: A total of 2,997 participants were recruited. Females scored worse than males in terms of emotional functioning (OR = 1.6, 95% CI: 1.2-2.1) and cognitive functioning (OR = 1.4, 95% CI: 1.1-1.8). The respondents aged 30-39 and 40-49 years scored worse in nearly all domains of HRQoL compared health care professionals under 30 years old. Respondents with high education had lower scores in physical functioning (OR = 1.3, 95% CI: 1.0-1.7) and emotional functioning (OR = 1.5, 95% CI: 1.2-1.9). Compared with doctors, nurses had higher scores in all domains except for summary score and worry. The respondents whose working places had not set up pediatric fever clinics and isolated observation areas independently had lower scores in all domains except for worry. The respondents who had ever treated patients with COVID-19 had lower scores in all domains. Conclusion: During the COVID-19 outbreak, the HRQoL of pediatric medical staff decreased. The factors associated with HRQoL can be used to develop intervention to improve HRQoL in pediatric medical staff.

Inflammation-associated factors for predicting in-hospital mortality in patients with COVID-19.

The aim is to explore the relation between inflammation-associated factors and in-hospital mortality and investigate which factor is an independent predictor of in-hospital death in patients with coronavirus disease-2019. This study included patients with coronavirus disease-2019, who were hospitalized between February 9, 2020, and March 30, 2020. Univariate Cox regression analysis and least absolute shrinkage and selection operator regression (LASSO) were used to select variables. Multivariate Cox regression analysis was applied to identify independent risk factors in coronavirus disease-2019. A total of 1135 patients were analyzed during the study period. A total of 35 variables were considered to be risk factors after the univariate regression analysis of the clinical characteristics and laboratory parameters (p < .05), and LASSO regression analysis screened out seven risk factors for further study. The six independent risk factors revealed by multivariate Cox regression were myoglobin (HR, 5.353; 95% CI, 2.633-10.882; p < .001), C-reactive protein (HR, 2.063; 95% CI, 1.036-4.109; p = .039), neutrophil count (HR, 2.015; 95% CI, 1.154-3.518; p = .014), interleukin 6 (Il-6; HR, 9.753; 95% CI, 2.952-32.218; p < .001), age (HR, 2.016; 95% CI, 1.077-3.773; p = .028), and international normalized ratio (HR, 2.595; 95% CI, 1.412-4.769; p = .002). Our results suggested that inflammation-associated factors were significantly associated with in-hospital mortality in coronavirus disease-2019 patients. C-reactive protein, neutrophil count, and interleukin 6 were independent factors for predicting in-hospital mortality and had a better independent predictive ability. We believe these findings may allow early identification of the patients at high risk for death, and can also assist in better management of these patients.

Short-term developmental outcomes in neonates born to mothers with COVID-19 from Wuhan, China.

BACKGROUND: Coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is an emerging disease. The consequences of SARS-CoV-2 exposure in infants remain unknown. Therefore, this study aims to investigate whether neonates born to mothers with COVID-19 have adverse brain development. METHODS: This multicenter observational study was conducted at two designated maternal and children's hospitals in Hubei Province, mainland China from February 1, 2020 to May 15, 2020. Neonates born to mothers with COVID-19 were enrolled. Brain magnetic resonance imaging (MRI) findings, and volumes of grey and white matters, and physical growth parameters were observed at 44 weeks corrected gestational age. RESULTS: Of 72 neonates born to mothers with COVID-19, 8 (11%) were diagnosed with COVID-19, 8 (11%) were critically ill, and no deaths were reported. Among the eight neonates that underwent brain MRI at corrected gestational age of 44 weeks, five neonates were diagnosed with COVID-19. Among these five neonates, three presented abnormal MRI findings including abnormal signal in white matter and delayed myelination in newborn 2, delayed myelination and brain dysplasia in newborn 3, and abnormal signal in the bilateral periventricular in newborn 5. The other three neonates without COVID-19 presented no significantly changes of brain MRI findings and the volumes of grey matter and white matter compared to those of healthy newborns at the equivalent age (P > 0.05). Physical growth parameters for weight, length, and head circumference at gestational age of 44 weeks were all above the 3rd percentile for all neonates. CONCLUSIONS: Some of the neonates born to mothers with COVID-19 had abnormal brain MRI findings but these neonates did not appear to have poor physical growth. These findings may provide the information on the follow-up schedule on the neonates exposed to SARS-CoV-2, but further study is required to evaluate the association between the abnormal MRI findings and the exposure to SARS-CoV-2.

Effects of SARS-CoV-2 infection on neuroimaging and neurobehavior in neonates.

BACKGROUND: We collected neonatal neurological, clinical, and imaging data to study the neurological manifestations and imaging characteristics of neonates with coronavirus disease 2019 (COVID-19). METHODS: This case-control study included newborns diagnosed with COVID-19 in Wuhan, China from January 2020 to July 2020. All included newborns had complete neurological evaluations and head magnetic resonance imaging. We normalized the extracted T2-weighted imaging data to a standard neonate template space, and segmented them into gray matter, white matter, and cerebrospinal fluid. The comparison of gray matter volume was conducted between the two groups. RESULTS: A total of five neonates with COVID-19 were included in this study. The median reflex scores were 2 points lower in the infected group than in the control group (P = 0.0094), and the median orientation and behavior scores were 2.5 points lower in the infected group than in the control group (P = 0.0008). There were also significant differences between the two groups in the total scale score (P = 0.0426). The caudate nucleus, parahippocampal gyrus, and thalamus had the strongest correlations with the Hammersmith neonatal neurologic examination (HNNE) score, and the absolute correlation coefficients between the gray matter volumes and each part of the HNNE score were all almost greater than 0.5. CONCLUSIONS: We first compared the neurological performance of neonates with and without COVID-19 by quantitative neuroimaging and neurological examination methods. Considering the limited numbers of patients, more studies focusing on the structural or functional aspects of the virus in the central nervous system in different age groups will be carried out in the future.

Cardiac Biomarker Levels and Their Prognostic Values in COVID-19 Patients With or Without Concomitant Cardiac Disease.

The coronavirus disease 2019 (COVID-19) pandemic has become a global threat. Increases in cardiac biomarkers are common and are associated with adverse outcomes in patients with COVID-19. Although these increases are more likely to occur in cases with concomitant cardiac disease, the differences in cardiac biomarker levels between patients with and without cardiac disease and their associations with in-hospital mortality are largely unknown. A consecutive serial of laboratory-confirmed COVID-19 cases was retrospectively enrolled. Clinical characteristics, laboratory results, and outcome data were collected. The levels of cardiac biomarkers were evaluated and compared by stratifying patients according to concomitant cardiac conditions and clinical classifications. The prognostic efficacy of cardiac biomarker levels on admission was also assessed. Among the overall study population and survived patients, the cardiac biomarker levels at both the early and late stages in cardiac patients were significantly higher than those in non-cardiac patients. However, their concentrations in cardiac patients were comparable to non-cardiac ones among non-survivors. The cardiac biomarker levels at the late stage of the disease were significantly decreased compared to those at the early stage among patients who were alive. Whereas, the late-stage biomarker levels were significantly increased in patients who ultimately died. Subgroup analysis illustrated that increases in cardiac biomarkers were closely related to the severity of the disease, and were prognostic for high risks of in-hospital mortality in non-cardiac, rather than in cardiac patients. Myo and NT-proBNP, rather than Hs-TnI and CK-MB, were independently associated with in-hospital mortality in the overall population and non-cardiac patients. However, these associations were not significant among cardiac patients. In conclusion, our results helped better understand the release pattern and prognostic performance of cardiac biomarkers in patients with COVID-19. Increased levels of Myo and NT-proBNP on admission could be useful markers for early identifying high-risk patients. However, special attention must be paid when implementing the prognostic function for cardiac patients.

Dual-branch combination network (DCN): Towards accurate diagnosis and lesion segmentation of COVID-19 using CT images.

The recent global outbreak and spread of coronavirus disease (COVID-19) makes it an imperative to develop accurate and efficient diagnostic tools for the disease as medical resources are getting increasingly constrained. Artificial intelligence (AI)-aided tools have exhibited desirable potential; for example, chest computed tomography (CT) has been demonstrated to play a major role in the diagnosis and evaluation of COVID-19. However, developing a CT-based AI diagnostic system for the disease detection has faced considerable challenges, which is mainly due to the lack of adequate manually-delineated samples for training, as well as the requirement of sufficient sensitivity to subtle lesions in the early infection stages. In this study, we developed a dual-branch combination network (DCN) for COVID-19 diagnosis that can simultaneously achieve individual-level classification and lesion segmentation. To focus the classification branch more intensively on the lesion areas, a novel lesion attention module was developed to integrate the intermediate segmentation results. Furthermore, to manage the potential influence of different imaging parameters from individual facilities, a slice probability mapping method was proposed to learn the transformation from slice-level to individual-level classification. We conducted experiments on a large dataset of 1202 subjects from ten institutes in China. The results demonstrated that 1) the proposed DCN attained a classification accuracy of 96.74% on the internal dataset and 92.87% on the external validation dataset, thereby outperforming other models; 2) DCN obtained comparable performance with fewer samples and exhibited higher sensitivity, especially in subtle lesion detection; and 3) DCN provided good interpretability on the loci of infection compared to other deep models due to its classification guided by high-level semantic information. An online CT-based diagnostic platform for COVID-19 derived from our proposed framework is now available.

Viral sepsis is a complication in patients with Novel Corona Virus Disease (COVID-19).

BACKGROUND: Until June 23th 2020, 9,195,635 laboratory-confirmed cases of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infection have been reported worldwide, including 473,127 deaths. Bacterial infection is the main cause of sepsis, however, sepsis caused by virus is often ignored. Increased awareness, early recognition of viral sepsis, rapid administration of appropriate antiviral drugs, and urgent treatment can significantly reduce deaths of viral sepsis. OBJECTIVES: Given the rapid global spread of novel Corona Virus Disease (COVID-19), coupled with the high rate of missed diagnosis of viral sepsis caused by SARS-CoV-2 infection, it is urgent to evaluate the multiple organ failure score and viral sepsis in COVID-19 patients, so as to determine the clinical characteristics of viral sepsis more accurately and reveal the risk factors related to mortality. METHODS: Here we provide a full description of three cases of viral sepsis and subsequent multiple organ dysfunction (MODS) caused by SARS-CoV-2 infection imported to Guiyang from Wuhan. RESULTS: We analyzed complete laboratory examination, imaging data and treatment methods for the patients and assessed Sepsis-related Organ Failure Assessment score (SOFA score) and Multiple organ dysfunction scores (MOD score) daily, aimed to elucidate the clinical feature of viral sepsis and MODS and to attract enough attention by clinicians. CONCLUSIONS: Therefore, we strongly suggest to daily evaluate SOFA score and MOD score in severe and critically-ill COVID-19 patients, so as to early diagnose and prevention of sepsis and MODS.Given the rapid global spread of novel Corona Virus Disease (COVID-19), coupled with the high rate of missed diagnosis of viral sepsis caused by SARS-CoV-2 infection, it is urgent to evaluate the multiple organ failure score and viral sepsis in COVID-19 patients, so as to determine the clinical characteristics of viral sepsis more accurately and reveal the risk factors related to mortality. Here we provide a full description of three cases of viral sepsis and subsequent multiple organ dysfunction (MODS) caused by SARS-CoV-2 infection imported to Guiyang from Wuhan. We analyzed complete laboratory examination, imaging data and treatment methods for the patients and assessed Sepsis-related Organ Failure Assessment score (SOFA score) and Multiple organ dysfunction scores (MOD score) daily, aimed to elucidate the clinical feature of viral sepsis and MODS and to attract enough attention by clinicians. Therefore, we strongly suggest to daily evaluate SOFA score and MOD score in severe and critically-ill COVID-19 patients, so as to early diagnose and prevention of sepsis and MODS.

Response and Operating Room Preparation for the COVID-19 Outbreak: A Perspective From the National Heart Centre in Singapore.

The outbreak of coronavirus disease 2019 (COVID-19), a respiratory disease from a novel coronavirus that was first detected in Wuhan City, Hubei Province, China, is now a public health emergency and pandemic. Singapore, as a major international transportation hub in Asia, has been one of the worst hit countries by the disease. With the advent of local transmission, the authors share their preparation and response planning for the operating room of the National Heart Centre Singapore, the largest cardiothoracic tertiary center in Singapore. Protection of staff and patients, environmental concerns, and other logistic and equipment issues are considered.