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Coronavirus disease 2019 (COVID-19) is an acute respiratory infectious disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. It is highly contagious and can cause death in severe cases. As reported by the World Health Organization (WHO), as of 6:36 pm Central European Summer Time (CEST), 12 August 2022, there had been 585 950 285 confirmed cases of COVID-19, including 6 425 422 deaths (WHO, 2022).

Predictive Risk Factors at Admission and a "Burning Point" During Hospitalization Serve as Sequential Alerts for Critical Illness in Patients With COVID-19.

Background: We intended to establish a novel critical illness prediction system combining baseline risk factors with dynamic laboratory tests for patients with coronavirus disease 2019 (COVID-19). Methods: We evaluated patients with COVID-19 admitted to Wuhan West Union Hospital between 12 January and 25 February 2020. The data of patients were collected, and the illness severity was assessed. Results: Among 1,150 enrolled patients, 296 (25.7%) patients developed into critical illness. A baseline nomogram model consists of seven variables including age [odds ratio (OR), 1.028; 95% confidence interval (CI), 1.004-1.052], sequential organ failure assessment (SOFA) score (OR, 4.367; 95% CI, 3.230-5.903), neutrophil-to-lymphocyte ratio (NLR; OR, 1.094; 95% CI, 1.024-1.168), D-dimer (OR, 1.476; 95% CI, 1.107-1.968), lactate dehydrogenase (LDH; OR, 1.004; 95% CI, 1.001-1.006), international normalised ratio (INR; OR, 1.027; 95% CI, 0.999-1.055), and pneumonia area interpreted from computed tomography (CT) images (medium vs. small [OR, 4.358; 95% CI, 2.188-8.678], and large vs. small [OR, 9.567; 95% CI, 3.982-22.986]) were established to predict the risk for critical illness at admission. The differentiating power of this nomogram scoring system was perfect with an area under the curve (AUC) of 0.960 (95% CI, 0.941-0.972) in the training set and an AUC of 0.958 (95% CI, 0.936-0.980) in the testing set. In addition, a linear mixed model (LMM) based on dynamic change of seven variables consisting of SOFA score (value, 2; increase per day [I/d], +0.49), NLR (value, 10.61; I/d, +2.07), C-reactive protein (CRP; value, 46.9 mg/L; I/d, +4.95), glucose (value, 7.83 mmol/L; I/d, +0.2), D-dimer (value, 6.08 µg/L; I/d, +0.28), LDH (value, 461 U/L; I/d, +13.95), and blood urea nitrogen (BUN value, 6.51 mmol/L; I/d, +0.55) were established to assist in predicting occurrence time of critical illness onset during hospitalization. Conclusion: The two-checkpoint system could assist in accurately and dynamically predicting critical illness and timely adjusting the treatment regimen for patients with COVID-19.

Recovery of functional fitness, lung function, and immune function in healthcare workers with nonsevere and severe COVID-19 at 13 months after discharge from the hospital: a prospective cohort study.

OBJECTIVES: This study aimed to evaluate the recovery of functional fitness, lung function, and immune function in healthcare workers (HCWs) with nonsevere and severe COVID-19 at 13 months after discharge from the hospital. METHODS: The participants of "Rehabilitation Care Project for Medical Staff Infected with COVID-19" underwent a functional fitness test (muscle strength, flexibility, and agility/dynamic balance), lung function test, and immune function test (including cytokines and lymphocyte subsets) at 13 months after discharge. RESULTS: The project included 779 HCWs (316 nonsevere COVID-19 and 463 severe COVID-19). This study found that 29.1% (130/446) of the HCWs have not yet recovered their functional fitness. The most affected lung function indicator was lung perfusion capacity (34% with diffusion capacity for carbon monoxide-single breath <80%). The increase of interleukin-6 (64/534, 12.0%) and natural killer cells (44/534, 8.2%) and the decrease of CD3+ T cells (58/534, 10.9%) and CD4+ T cells (26/534, 4.9%) still existed at 13 months after discharge. No significant difference was found in the HCWs with nonsevere and severe COVID-19 regarding recovery of functional fitness, lung function, and immune function at 13 months after discharge. CONCLUSION: The majority of Chinese HCWs with COVID-19 had recovered their functional fitness, lung function, and immune function, and the recovery status in HCWs with severe COVID-19 is no worse than that in HCWs with nonsevere COVID-19 at 13 months after discharge from the hospital.

Predictive Risk Factors at Admission and a “Burning Point” During Hospitalization Serve as Sequential Alerts for Critical Illness in Patients With COVID-19

Background We intended to establish a novel critical illness prediction system combining baseline risk factors with dynamic laboratory tests for patients with coronavirus disease 2019 (COVID-19). Methods We evaluated patients with COVID-19 admitted to Wuhan West Union Hospital between 12 January and 25 February 2020. The data of patients were collected, and the illness severity was assessed. Results Among 1,150 enrolled patients, 296 (25.7%) patients developed into critical illness. A baseline nomogram model consists of seven variables including age [odds ratio (OR), 1.028;95% confidence interval (CI), 1.004–1.052], sequential organ failure assessment (SOFA) score (OR, 4.367;95% CI, 3.230–5.903), neutrophil-to-lymphocyte ratio (NLR;OR, 1.094;95% CI, 1.024–1.168), D-dimer (OR, 1.476;95% CI, 1.107–1.968), lactate dehydrogenase (LDH;OR, 1.004;95% CI, 1.001–1.006), international normalised ratio (INR;OR, 1.027;95% CI, 0.999–1.055), and pneumonia area interpreted from computed tomography (CT) images (medium vs. small [OR, 4.358;95% CI, 2.188–8.678], and large vs. small [OR, 9.567;95% CI, 3.982–22.986]) were established to predict the risk for critical illness at admission. The differentiating power of this nomogram scoring system was perfect with an area under the curve (AUC) of 0.960 (95% CI, 0.941–0.972) in the training set and an AUC of 0.958 (95% CI, 0.936–0.980) in the testing set. In addition, a linear mixed model (LMM) based on dynamic change of seven variables consisting of SOFA score (value, 2;increase per day [I/d], +0.49), NLR (value, 10.61;I/d, +2.07), C-reactive protein (CRP;value, 46.9 mg/L;I/d, +4.95), glucose (value, 7.83 mmol/L;I/d, +0.2), D-dimer (value, 6.08 μg/L;I/d, +0.28), LDH (value, 461 U/L;I/d, +13.95), and blood urea nitrogen (BUN value, 6.51 mmol/L;I/d, +0.55) were established to assist in predicting occurrence time of critical illness onset during hospitalization. Conclusion The two-checkpoint system could assist in accurately and dynamically predicting critical illness and timely adjusting the treatment regimen for patients with COVID-19.

Plasma Metabolomic Profiling of Patients Recovered From Coronavirus Disease 2019 (COVID-19) With Pulmonary Sequelae 3 Months After Discharge.

BACKGROUND: Elucidation of the molecular mechanisms involved in the pathogenesis of coronavirus disease 2019 (COVID-19) may help to discover therapeutic targets. METHODS: To determine the metabolomic profile of circulating plasma from COVID-19 survivors with pulmonary sequelae 3 months after discharge, a random, outcome-stratified case-control sample was analyzed. We enrolled 103 recovered COVID-19 patients as well as 27 healthy donors, and performed pulmonary function tests, computerized tomography (CT) scans, laboratory examinations, and liquid chromatography-mass spectrometry. RESULTS: Plasma metabolite profiles of COVID-19 survivors with abnormal pulmonary function were different from those of healthy donors or subjects with normal pulmonary function. These alterations were associated with disease severity and mainly involved amino acid and glycerophospholipid metabolic pathways. Furthermore, increased levels of triacylglycerols, phosphatidylcholines, prostaglandin E2, arginine, and decreased levels of betain and adenosine were associated with pulmonary CO diffusing capacity and total lung capacity. The global plasma metabolomic profile differed between subjects with abnormal and normal pulmonary function. CONCLUSIONS: Further metabolite-based analysis may help to identify the mechanisms underlying pulmonary dysfunction in COVID-19 survivors, and provide potential therapeutic targets in the future.

Inflammatory Profiles and Clinical Features of Coronavirus 2019 Survivors 3 Months After Discharge in Wuhan, China.

BACKGROUND: Postdischarge immunity and its correlation with clinical features among patients recovered from coronavirus disease 2019(COVID-19) are poorly described. This prospective cross-sectional study explored the inflammatory profiles and clinical recovery of patients with COVID-19 at 3 months after hospital discharge. METHODS: Patients with COVID-19 discharged from 4 hospitals in Wuhan, recovered asymptomatic patients (APs) from an isolation hotel, and uninfected healthy controls (HCs) were recruited. Viral nucleic acid and antibody detection, laboratory examination, computed tomography, pulmonary function assessment, multiplex cytokine assay, and flow cytometry were performed. RESULTS: The72 age-, sex- and body mass index-matched participants included 19 patients with severe/critical COVID-19 (SPs), 20 patients with mild/moderate COVID-19 (MPs), 16 APs, and 17 HCs. At 3 months after discharge, levels of proinflammatory cytokines and factors related to vascular injury/repair in patients recovered from COVID-19 had not returned to those of the HCs, especially among recovered SPs compared with recovered MPs and APs. These cytokines were significantly correlated with impaired pulmonary function and chest computed tomographic abnormalities. However, levels of immune cells had returned to nearly normal levels and were not significantly correlated with abnormal clinical features. CONCLUSION: Vascular injury, inflammation, and chemotaxis persisted in patients with COVID-19 and were correlated with abnormal clinical features 3 months after discharge, especially in recovered SPs.

Long-Term Effects of COVID-19 on Health Care Workers 1-Year Post-Discharge in Wuhan.

INTRODUCTION: To assess the long-term consequences of coronavirus disease (COVID-19) among health care workers (HCWs) in China (hereafter surviving HCWs). METHODS: A total of 303 surviving HCWs were included. Lung (pulmonary function test, 6-min walk test [6MWT], chest CT), physical (St. George's Respiratory Questionnaire [SGRQ], Modified Medical Research Council dyspnea scale [mMRC], and Borg scale), and psychiatric functions (Essen Trauma Inventory) were evaluated during the 1-year follow-up. RESULTS: Surviving HCWs had an abnormal diffusion capacity 1 year post-discharge. Participants with a reduced carbon monoxide diffusing capacity (DLCO) comprised 43.48%. The proportion of HCWs with a median 6MWT distance below the lower limit of the normal was 19.4%. An abnormal CT pattern was observed in 37.5% of the HCWs. The SGRQ, mMRC, and Borg scores of surviving HCWs, especially those with critical/severe disease, were significantly higher than those in the normal population. Probable post-traumatic stress disorder (PTSD) was reported in 21.9% of the surviving HCWs. Diffusion capacity impairment was associated with women. Critical/severe illness and nurses were associated with impaired physical function. CONCLUSIONS: Most surviving HCWs, especially female HCWs, still had an abnormal diffusion capacity at 1 year. The physical and psychiatric functions of surviving HCWs were significantly worse than those of the healthy population. Long-term follow-up of pulmonary, physical, and psychiatric functions for surviving HCWs is required.

Changes in glomerular filtration rate and metabolomic differences in severely ill coronavirus disease survivors 3 months after discharge.

To explore the recovery of renal function in severely ill coronavirus disease (COVID-19) survivors and determine the plasma metabolomic profile of patients with different renal outcomes 3 months after discharge, we included 89 severe COVID-19 survivors who had been discharged from Wuhan Union Hospital for 3 months. All patients had no underlying kidney disease before admission. At patient recruitment, renal function assessment, laboratory examination, chest computed tomography (CT) were performed. Liquid chromatography-mass spectrometry was used to detect metabolites in the plasma. We analyzed the longitudinally change in the estimated glomerular filtration rate (eGFR) based on serum creatinine and cystatin-c levels using the CKD-EPI equation and explored the metabolomic differences in patients with different eGFR change patterns from hospitalization to 3 months after discharge. Lung CT showed good recovery; however, the median eGFR significantly decreased at the 3-month follow-up. Among the 89 severely ill COVID-19 patients, 69 (77.5%) showed abnormal eGFR (<90 mL/min per 1.73 m2) at 3 months after discharge. Age (odds ratio [OR] = 1.26, 95% confidence interval [CI] = 1.08-1.47, p = 0.003), body mass index (OR = 1.97, 95% CI = 1.20-3.22, p = 0.007), and cystatin-c level (OR = 1.22, 95% CI = 1.07-1.39, p = 0.003) at discharge were independent risk factors for post-discharge abnormal eGFR. Plasma metabolomics at the 3-months follow-up revealed that ß-pseudouridine, uridine, and 2-(dimethylamino) guanosine levels gradually increased with an abnormal degree of eGFR. Moreover, the kynurenine pathway in tryptophan metabolism, vitamin B6 metabolism, cysteine and methionine metabolism, and arginine biosynthesis were also perturbed in survivors with abnormal eGFR.

Plasma Metabolomic Profiles in Recovered COVID-19 Patients without Previous Underlying Diseases 3 Months After Discharge.

BACKGROUND: It remains unclear whether discharged COVID-19 patients have fully recovered from severe complications, including the differences in the post-infection metabolomic profiles of patients with different disease severities. METHODS: COVID-19-recovered patients, who had no previous underlying diseases and were discharged from Wuhan Union Hospital for 3 months, and matched healthy controls (HCs) were recruited in this prospective cohort study. We examined the blood biochemical indicators, cytokines, lung computed tomography scans, including 39 HCs, 18 recovered asymptomatic (RAs), 34 recovered moderate (RMs), and 44 recovered severe/ critical patients (RCs). A liquid chromatography-mass spectrometry-based metabolomics approach was employed to profile the global metabolites of fasting plasma of these participants. RESULTS: Clinical data and metabolomic profiles suggested that RAs recovered well, but some clinical indicators and plasma metabolites in RMs and RCs were still abnormal as compared with HCs, such as decreased taurine, succinic acid, hippuric acid, some indoles, and lipid species. The disturbed metabolic pathway mainly involved the tricarboxylic cycle, purine, and glycerophospholipid metabolism. Moreover, metabolite alterations differ between RMs and RCs when compared with HCs. Correlation analysis revealed that many differential metabolites were closely associated with inflammation and the renal, pulmonary, heart, hepatic, and coagulation system functions. CONCLUSION: We uncovered metabolite clusters pathologically relevant to the recovery state in discharged COVID-19 patients which may provide new insights into the pathogenesis of potential organ damage in recovered patients.

Dynamic changes of functional fitness, antibodies to SARS-CoV-2 and immunological indicators within 1 year after discharge in Chinese health care workers with severe COVID-19: a cohort study.

BACKGROUND: Few studies had described the health consequences of patients with coronavirus disease 2019 (COVID-19) especially in those with severe infections after discharge from hospital. Moreover, no research had reported the health consequences in health care workers (HCWs) with COVID-19 after discharge. We aimed to investigate the health consequences in HCWs with severe COVID-19 after discharge from hospital in Hubei Province, China. METHODS: We conducted an ambidirectional cohort study in "Rehabilitation Care Project for Medical Staff Infected with COVID-19" in China. The participants were asked to complete three physical examinations (including the tests of functional fitness, antibodies to SARS-CoV-2 and immunological indicators) at 153.4 (143.3, 164.8), 244.3 (232.4, 259.1), and 329.4 (319.4, 339.3) days after discharge, respectively. Mann-Whitney U test, Kruskal-Wallis test, t test, one-way ANOVA, χ2, and Fisher's exact test were used to assess the variance between two or more groups where appropriate. RESULTS: Of 333 HCWs with severe COVID-19, the HCWs' median age was 36.0 (31.0, 43.0) years, 257 (77%) were female, and 191 (57%) were nurses. Our research found that 70.4% (114/162), 48.9% (67/137), and 29.6% (37/125) of the HCWs with severe COVID-19 were considered to have not recovered their functional fitness in the first, second, and third functional fitness tests, respectively. The HCWs showed improvement in muscle strength, flexibility, and agility/dynamic balance after discharge in follow-up visits. The seropositivity of IgM (17.0% vs. 6.6%) and median titres of IgM (3.0 vs. 1.4) and IgG (60.3 vs. 45.3) in the third physical examination was higher than that in the first physical examination. In the third physical examination, there still were 42.1% and 45.9% of the HCWs had elevated levels of IL-6 and TNF-α, and 11.9% and 6.3% of the HCWs had decreased relative numbers of CD3+ T cells and CD4+ T cells. CONCLUSION: The HCWs with severe COVID-19 showed improvement in functional fitness within 1 year after discharge, active intervention should be applied to help their recovery if necessary. It is of vital significance to continue monitoring the functional fitness, antibodies to SARS-CoV-2 and immunological indicators after 1 year of discharge from hospital in HCWs with severe COVID-19.

Comparison of Residual Pulmonary Abnormalities 3 Months After Discharge in Patients Who Recovered From COVID-19 of Different Severity.

Background and Objectives: To investigate whether coronavirus disease 2019 (COVID-19) survivors who had different disease severities have different levels of pulmonary sequelae at 3 months post-discharge. Methods: COVID-19 patients discharged from four hospitals 3 months previously, recovered asymptomatic patients from an isolation hotel, and uninfected healthy controls (HCs) from the community were prospectively recruited. Participants were recruited at Wuhan Union Hospital and underwent examinations, including quality-of-life evaluation (St. George Respiratory Questionnaire [SGRQ]), laboratory examination, chest computed tomography (CT) imaging, and pulmonary function tests. Results: A total of 216 participants were recruited, including 95 patients who had recovered from severe/critical COVID-19 (SPs), 51 who had recovered from mild/moderate disease (MPs), 28 who had recovered from asymptomatic disease (APs), and 42 HCs. In total, 154 out of 174 (88.5%) recovered COVID-19 patients tested positive for serum SARS-COV-2 IgG, but only 19 (10.9%) were still positive for IgM. The SGRQ scores were highest in the SPs, while APs had slightly higher SGRQ scores than those of HCs; 85.1% of SPs and 68.0% of MPs still had residual CT abnormalities, mainly ground-glass opacity (GGO) followed by strip-like fibrosis at 3 months after discharge, but the pneumonic lesions were largely absorbed in the recovered SPs or MPs relative to findings in the acute phase. Pulmonary function showed that the frequency of lung diffusion capacity for carbon monoxide abnormalities were comparable in SPs and MPs (47.1 vs. 41.7%), while abnormal total lung capacity (TLC) and residual volume (RV) were more frequent in SPs than in MPs (TLC, 18.8 vs. 8.3%; RV, 11.8 vs. 0%). Conclusions: Pulmonary abnormalities remained after recovery from COVID-19 and were more frequent and conspicuous in SPs at 3 months after discharge.

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.

Comparison of clinical characteristics among younger and elderly deceased patients with COVID-19: a retrospective study.

We aimed to compare the age-related clinical characteristics between younger and elderly deceased COVID-19 patients. This single-center retrospective study included 163 adult deceased COVID-19 patients who were admitted to Wuhan Union Hospital West Campus from January 12, 2020, to March 30, 2020. Demographic and clinical features were collected by reviewing the medical records. The median age of the 163 deceased patients was 69 (interquartile range [IQR], 62-78) years. They were classified as younger (age 18-69 years; 86/163, 52.8%) and elderly (≥70 years; 77/163, 47.2%) subjects. Younger deceased patients were more likely to develop fever (72/86 vs 54/77, P=0.039) than elderly deceased patients were while anorexia was (29/77 vs 19/86, P=0.029) more common in elderly deceased patients than in younger deceased patients. In multivariate analyses, age was a protective factor for acute cardiac injury of deceased COVID-19 patients (odds ratio [OR] 0.968, [95% confidence interval (CI), 0.940-0.997]; P=0.033) while chronic cardiac disease was a risk factor for acute cardiac injury of deceased COVID-19 patients (OR 2.660 [95%CI, 1.034-6.843]; P=0.042). Our study described the clinical characteristics of younger and elderly deceased COVID-19 patients and demonstrated that younger deceased patients were more likely to develop an acute cardiac injury.

COVID-19 diagnosed by serological antibody test

The new coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), first reported in Wuhan, China, is causing a pandemic. With an increased understanding of the disease, the diagnosis and treatment guidelines are being updated and improved. In addition to nucleic acid detection, antibody detection kits are also being developed and approved. A medical worker suspected of having COVID-19 in our hospital had fatigue and loss of appetite and pulmonary infection indicated by CT, but the nucleic acid test was negative three times. Finally, she was confirmed to have COVID-19 by a serological antibody test. After rest and oral antiviral treatment, she recovered and returned to work. This is a case report that focuses on suspected mild patients who tested negative for nucleic acids. Such a group of patients had to choose home isolation treatment during the outbreak. The majority of them did not make a definitive diagnosis or rule out COVID-19 by the time they recovered. The antibody test is of great significance to identify infected patients with multiple negative nucleic acid tests. It can complement nucleic acid testing to enhance diagnostic efficiency. We have reviewed the literature and realized that further validation and standardization of serological tests are needed for more mature application of antibody tests to clinical diagnosis and vaccine development.

SARS-CoV-2: Mechanism of infection and emerging technologies for future prospects.

The novel coronavirus severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has spread globally to over 200 countries with more than 23 million confirmed cases and at least 800,000 fatalities as of 23 August 2020. Declared a pandemic on March 11 by World Health Organization, the disease caused by SARS-CoV-2 infection, called coronavirus disease 2019 (COVID-19), has become a global public health crisis that challenged all national healthcare systems. This review summarized the current knowledge about virologic and pathogenic characteristics of SARS-CoV-2 with emphasis on potential immunomodulatory mechanism and drug development. With multiple emerging technologies and cross-disciplinary approaches proving to be crucial in our global response against COVID-19, the application of PROteolysis TArgeting Chimeras strategy, CRISPR-Cas9 gene editing technology, and Single-Nucleotide-Specific Programmable Riboregulators technology in developing antiviral drugs and detecting infectious diseases are proposed here. We also discussed the available but still limited epidemiology of COVID-19 as well as the ongoing efforts on vaccine development. In brief, we conducted an in-depth analysis of the pathogenesis of SARS-CoV-2 and reviewed the therapeutic options for COVID-19. We also proposed key research directions in the future that may help uncover more underlying molecular mechanisms governing the pathology of COVID-19.