Sequelae of long COVID, known and unknown: A review of updated information.

Over three years have passed since the COVID-19 pandemic started. The dangerousness and impact of COVID-19 should definitely not be ignored or underestimated. Other than the symptoms of acute infection, the long-term symptoms associated with SARS-CoV-2 infection, which are referred to here as "sequelae of long COVID (LC)", are also a conspicuous global public health concern. Although such sequelae were well-documented, the understanding of and insights regarding LC-related sequelae remain inadequate due to the limitations of previous studies (the follow-up, methodological flaws, heterogeneity among studies, etc.). Notably, robust evidence regarding diagnosis and treatment of certain LC sequelae remain insufficient and has been a stumbling block to better management of these patients. This awkward situation motivated us to conduct this review. Here, we comprehensively reviewed the updated information, particularly focusing on clinical issues. We attempt to provide the latest information regarding LC-related sequelae by systematically reviewing the involvement of main organ systems. We also propose paths for future exploration based on available knowledge and the authors' clinical experience. We believe that these take-home messages will be helpful to gain insights into LC and ultimately benefit clinical practice in treating LC-related sequelae.

Role of the extracellular matrix in COVID-19.

An outbreak of coronavirus disease 2019 (COVID-19) has spread globally, with over 500 million cases and 6 million deaths to date. COVID-19 is associated with a systemic inflammatory response and abnormalities of the extracellular matrix (ECM), which is also involved in inflammatory storms. Upon viral infection, ECM proteins are involved in the recruitment of inflammatory cells and interference with target organ metabolism, including in the lungs. Additionally, serum biomarkers of ECM turnover are associated with the severity of COVID-19 and may serve as potential targets. Consequently, understanding the expression and function of ECM, particularly of the lung, during severe acute respiratory syndrome of the coronavirus 2 infection would provide valuable insights into the mechanisms of COVID-19 progression. In this review, we summarize the current findings on ECM, such as hyaluronic acid, matrix metalloproteinases, and collagen, which are linked to the severity and inflammation of COVID-19. Some drugs targeting the extracellular surface have been effective. In the future, these ECM findings could provide novel perspectives on the pathogenesis and treatment of COVID-19.

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.

Surface control approach for growth of cerium oxide on flower-like molybdenum disulfide nanosheets enables superior removal of uremic toxins

Due to the high incidence of kidney disease, there is an urgent need to develop wearable artificial kidneys. This need is further exacerbated by the coronavirus disease 2019 pandemic. However, the dialysate regeneration system of the wearable artificial kidney has a low adsorption capacity for urea, which severely limits its application. Therefore, nanomaterials that can effectively remove uremic toxins, especially urea, to regenerate dialysate are required and should be further investigated and developed. Herein, flower-like molybdenum disulphide (MoS2) nanosheets decorated with highly dispersed cerium oxide (CeO2) were prepared (MoS2/CeO2), and their adsorption performances for urea, creatinine, and uric acid were studied in detail. Due to the open interlayer structures and the combination of MoS2 and CeO2, which can provide abundant adsorption active sites, the MoS2/CeO2 nanomaterials present excellent uremic toxin adsorption activities. Further, uremic toxin adsorption capacities were also assessed using a self-made fixed bed device under dynamic conditions, with the aim of developing MoS2/CeO2 for the practical adsorption of uremic toxins. In addition, the biocompatibility of MoS2/CeO2 was systematically analyzed using hemocompatibility and cytotoxicity assays. Our data suggest that MoS2/CeO2 can be safely used for applications requiring close contact with blood. Our findings confirm that novel 2-dimensional nanomaterial adsorbents have significant potential for dialysis fluid regeneration.

The Effect of the Coronavirus Pandemic on the Prediction Accuracy of Stock Price

In late 2019, the coronavirus began to spread around the world and impact international politics and economies significantly. In the face of the pandemic, stock markets around the world fluctuated sharply. The study aims to investigate the impact of the pandemic on the predictive variables of a stock prediction model, formed using chip-based variables and sentiment variables derived from comments posted on a social media platform. This study first performs feature engineering analysis to identify the indicators suitable for constructing the prediction model. The analysis then establishes a set of phrase rules to assign sentiment scores to the opinions expressed in replies and evaluates the effect on the accuracy of predictions. The results show that the major chip-based indicators affecting changes in the stock market differ before and after the pandemic. Hence, prediction models should be established separately for analysis in either period. In addition, the results indicate that the model relying on reply-based sentiment scores as a predictive variable provides more accurate predictions of stock price change.

High-fidelity Cas13 variants for targeted RNA degradation with minimal collateral effects.

CRISPR-Cas13 systems have recently been used for targeted RNA degradation in various organisms. However, collateral degradation of bystander RNAs has limited their in vivo applications. Here, we design a dual-fluorescence reporter system for detecting collateral effects and screening Cas13 variants in mammalian cells. Among over 200 engineered variants, several Cas13 variants including Cas13d and Cas13X exhibit efficient on-target activity but markedly reduced collateral activity. Furthermore, transcriptome-wide off-targets and cell growth arrest induced by Cas13 are absent for these variants. High-fidelity Cas13 variants show similar RNA knockdown activity to wild-type Cas13 but no detectable collateral damage in transgenic mice or adeno-associated-virus-mediated somatic cell targeting. Thus, high-fidelity Cas13 variants with minimal collateral effects are now available for targeted degradation of RNAs in basic research and therapeutic applications.

Work-family conflict and posttraumatic stress symptoms among college teachers during the COVID-19 pandemic.

The study aimed to examine the indirect factors underlying the association between work-family conflict and posttraumatic stress symptoms (PTSS) in college teachers during the COVID-19 pandemic. Three potential indirect factors were examined: perceived stress, basic psychological needs, and rumination. A total of 274 college teachers were recruited. All participants completed an electronic questionnaire that assessed their exposure to the pandemic, work-family conflict, perceived stress, basic psychological needs, rumination, and PTSS. The results showed that after controlling for pandemic exposure, gender, and age, work-family conflict was associated with PTSS via perceived stress alone, rumination alone, a path from perceived stress to basic psychological needs, and a path from perceived stress to rumination. These results indicate that work-family conflict is positively associated with PTSS indirectly via perceived stress, rumination, and basic psychological needs during the COVID-19 pandemic. These three mediators may completely explain the relation of work-family conflict to PTSS.

Aspirin Therapy on Prophylactic Anticoagulation for Patients Hospitalized With COVID-19: A Propensity Score-Matched Cohort Analysis of the HOPE-COVID-19 Registry.

Background COVID-19 is an infectious illness, featured by an increased risk of thromboembolism. However, no standard antithrombotic therapy is currently recommended for patients hospitalized with COVID-19. The aim of this study was to evaluate safety and efficacy of additional therapy with aspirin over prophylactic anticoagulation (PAC) in patients hospitalized with COVID-19 and its impact on survival. Methods and Results A total of 8168 patients hospitalized for COVID-19 were enrolled in a multicenter-international prospective registry (HOPE COVID-19). Clinical data and in-hospital complications, including mortality, were recorded. Study population included patients treated with PAC or with PAC and aspirin. A comparison of clinical outcomes between patients treated with PAC versus PAC and aspirin was performed using an adjusted analysis with propensity score matching. Of 7824 patients with complete data, 360 (4.6%) received PAC and aspirin and 2949 (37.6%) PAC. Propensity-score matching yielded 298 patients from each group. In the propensity score-matched population, cumulative incidence of in-hospital mortality was lower in patients treated with PAC and aspirin versus PAC (15% versus 21%, Log Rank P=0.01). At multivariable analysis in propensity matched population of patients with COVID-19, including age, sex, hypertension, diabetes, kidney failure, and invasive ventilation, aspirin treatment was associated with lower risk of in-hospital mortality (hazard ratio [HR], 0.62; [95% CI 0.42-0.92], P=0.018). Conclusions Combination PAC and aspirin was associated with lower mortality risk among patients hospitalized with COVID-19 in a propensity score matched population compared to PAC alone.

Chronic Oral Anticoagulation Therapy and Prognosis of Patients Admitted to Hospital for COVID-19: Insights from the HOPE COVID-19 Registry.

Background: Most evidence regarding anticoagulation and COVID-19 refers to the hospitalization setting, but the role of oral anticoagulation (OAC) before hospital admission has not been well explored. We compared clinical outcomes and short-term prognosis between patients with and without prior OAC therapy who were hospitalized for COVID-19. Methods: Analysis of the whole cohort of the HOPE COVID-19 Registry which included patients discharged (deceased or alive) after hospital admission for COVID-19 in 9 countries. All-cause mortality was the primary endpoint. Study outcomes were compared after adjusting variables using propensity score matching (PSM) analyses. Results: 7698 patients were suitable for the present analysis (675 (8.8%) on OAC at admission: 427 (5.6%) on VKAs and 248 (3.2%) on DOACs). After PSM, 1276 patients were analyzed (638 with OAC; 638 without OAC), without significant differences regarding the risk of thromboembolic events (OR 1.11, 95% CI 0.59-2.08). The risk of clinically relevant bleeding (OR 3.04, 95% CI 1.92-4.83), as well as the risk of mortality (HR 1.22, 95% CI 1.01-1.47; log-rank p value = 0.041), was significantly increased in previous OAC users. Amongst patients on prior OAC only, there were no differences in the risk of clinically relevant bleeding, thromboembolic events, or mortality when comparing previous VKA or DOAC users, after PSM. Conclusion: Hospitalized COVID-19 patients on prior OAC therapy had a higher risk of mortality and worse clinical outcomes compared to patients without prior OAC therapy, even after adjusting for comorbidities using a PSM. There were no differences in clinical outcomes in patients previously taking VKAs or DOACs. This trial is registered with NCT04334291/EUPAS34399.

Emerging early diagnostic methods for acute kidney injury.

Many factors such as trauma and COVID-19 cause acute kidney injury (AKI). Late AKI have a very high incidence and mortality rate. Early diagnosis of AKI provides a critical therapeutic time window for AKI treatment to prevent progression to chronic renal failure. However, the current clinical detection based on creatinine and urine output isn't effective in diagnosing early AKI. In recent years, the early diagnosis of AKI has made great progress with the advancement of information technology, nanotechnology, and biomedicine. These emerging methods are mainly divided into two aspects: First, predicting AKI through models construct by machine learning; Second, early diagnosis of AKI through detection of newly-discovered early biomarkers. Currently, these methods have shown great potential and become an attractive tool for the early diagnosis of AKI. Therefore, it is very important to discuss and summarize these methods for the early diagnosis of AKI. In this review, we first systematically summarize the application of machine learning in AKI prediction algorithms and specific scenarios. In addition, we introduce the key role of early biomarkers in the progress of AKI, and then comprehensively summarize the application of emerging detection technologies for early AKI. Finally, we discuss current challenges and prospects of machine learning and biomarker detection. The review is expected to provide new insights for early diagnosis of AKI, and provided important inspiration for the design of early diagnosis of other major diseases.

The Short- and Long-Term Impact of COVID-19 Lockdown on Child Maltreatment.

BACKGROUND: The COVID-19 pandemic has brought a new threat to child health and safety. Some studies suggest that social isolation and economic stress have exacerbated child abuse and neglect, whereas other studies argue that orders to stay at home are likely to promote parent-child relationships during this stressful time. Due to a lack of prospective studies including before-during-after lockdown assessments, the impacts of lockdown measures on child maltreatment are unclear. METHODS: This study retrospectively investigated child maltreatment of 2821 Chinese children and adolescents from 12 to 18 (female, 59%) before, during and after lockdown, and identified risk factors. Potential predictors including socio-economic and individual mental health status were collected. RESULTS: During Chinese lockdown, children and adolescents reported that the proportions of decrease (range 18-47.5%) in emotional abuse and neglect, physical abuse and neglect, sexual abuse, and witnessing domestic violence were greater than that of increase (range 5.1-9.1%). Compared with before lockdown (1.6%), the prevalence of sexual abuse significantly increased 8 months (2.9%) after the lifting of lockdown (p = 0.002). Being male, suffering from depression, state anhedonia, and experiencing psychotic symptoms at baseline were associated with increased sexual abuse after lockdown. CONCLUSIONS: The impact of lockdown on child maltreatment was beneficial in the short-term but detrimental in the long-term in China.

Network pharmacology and molecular docking analysis reveals the mechanism of asiaticoside on COVID-19.

Background: Asiaticoside (AS) is a saponin extracted from the traditional Chinese herbal medicine Centella Asiatica, which has the effects of reducing inflammatory infiltration and anti-oxidation in pneumonia and combating pulmonary fibrosis. We hypothesize that AS might have therapeutic potential for the treatment of the coronavirus disease 2019 (COVID-19). With the help of network pharmacology and molecular docking techniques, this study discussed the underlying molecular mechanism of AS in the treatment of COVID-19. Methods: The molecular structure of AS was obtained from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) system. The targets of AS were achieved using PharmMapper, SwissTargetPrediction, and the Comparative Toxicogenomics Database (CTD). The targets corresponding to COVID-19 were obtained using GeneCards, Online Mendelian Inheritance in Man (OMIM), and CTD database. Then, a target protein-protein interaction (PPI) network was formed using the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) database. A network of AS, COVID-19, and their co-targets was built using Cytoscape. Afterwards, the co-targets were analyzed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment. Moreover, the predictions of crucial targets were further investigated by performing molecular docking with AS. Results: A total of 45 core targets of AS were found to be engaged in the pathogenesis of COVID-19. The KEGG enrichment analysis indicated that AS might be protective against COVID-19 through inflammation- and immune-related signaling pathways, including interleukin-17 (IL-17) signaling, T helper 17 (Th17) cell differentiation pathway, Coronavirus disease-COVID-19, MAPK, the PI3K-Akt signaling pathway, and so on. The results of molecular docking showed that AS had a high affinity with those core targets. Conclusions: The beneficial effect of AS on COVID-19 might be through regulating multiple immune or inflammation-related targets and signaling pathways.

Toward Urease-free Wearable Artificial Kidney: Widened Interlayer Spacing MoS2 Nanosheets with Highly Effective Adsorption for Uremic Toxins

The high incidence of kidney disease caused by various factors (such as COVID-19) has triggered an extreme desire for wearable artificial kidney (WAK). Nevertheless, the dialysate regeneration system in WAK presents a very low adsorption capacity of urea, and must rely on the help of urease and zirconium compounds, which make the device too complex and costly, thus limiting their application. In this study, we employ the adsorption activity of defect-rich MoS2 nanosheets with widened interlayer spacing (WDR-MoS2) for the elimination of three crucial uremic toxins (urea, creatinine, and uric acid). The high adsorption performances of WDR-MoS2 are owing to the presence of abundant S atoms between the two MoS2 sheets that can efficiently adsorb uremic toxins through the unique S-N bond. Furthermore, widening the layer spacing of MoS2 is similar to adjusting the aperture of a filter, which can not only speed up the transport of uremic toxins but also prevent the passage of large molecules (such as proteins). Thus, the WDR-MoS2 can neither affect cell viability nor produce hemolysis and coagulation in the blood. Finally, a home-made WDR-MoS2 fixed-bed system without urease and zirconium compounds is used to efficiently remove uremic toxins in the dialysate. WDR-MoS2 is expected to fundamentally solve the materials science challenges in WAK and provide a new design idea for the development of high-performance 2D material-based adsorbents.

Analysis of Continuous Mutation and Evolution on Circulating SARS-CoV-2

Monitoring the mutation and evolution of the virus is important for tracing its ongoing transmission and facilitating effective vaccine development. A total of 342 complete genomic sequences of SARS-CoV-2 were analyzed in this study. Compared to the reference genome reported in December 2019, 465 mutations were found, among which, 347 occurred in only 1 sequence, while 26 occurred in more than 5 sequences. For these 26 further identified as SNPs, 14 were closely linked and were grouped into 5 profiles. Phylogenetic analysis revealed the sequences formed 2 major groups. Most of the sequences in late period (March and April) constituted the Cluster II, while the sequences before March in this study and the reported S/L and A/B/C types in previous studies were all in Cluster I. The distributions of some mutations were specific geographically or temporally, the potential effect of which on the transmission and pathogenicity of SARS-CoV-2 deserves further evaluation and monitoring. Two mutations were found in the receptor-binding domain (RBD) but outside the receptor-binding motif (RBM), indicating that mutations may only have marginal biological effects but merit further attention. The observed novel sequence divergence is of great significance to the study of the transmission, pathogenicity, and development of an effective vaccine for SARS-CoV-2.

Spherical Neutralizing Aptamer Inhibits SARS-CoV-2 Infection and Suppresses Mutational Escape.

New neutralizing agents against SARS-CoV-2 and associated mutant strains are urgently needed for the treatment and prophylaxis of COVID-19. Herein, we develop a spherical cocktail neutralizing aptamer-gold nanoparticle (SNAP) to block the interaction between the receptor-binding domain (RBD) of SARS-CoV-2 and host ACE2. With the multivalent aptamer assembly as well as the steric hindrance effect of the gold scaffold, SNAP exhibits exceptional binding affinity against the RBD with a dissociation constant of 3.90 pM and potent neutralization against authentic SARS-CoV-2 with a half-maximal inhibitory concentration of 142.80 fM, about 2 or 3 orders of magnitude lower than that of the reported neutralizing aptamers and antibodies. More importantly, the synergetic blocking strategy of multivalent multisite binding and steric hindrance ensures broad neutralizing activity of SNAP, almost completely blocking the infection of three mutant pseudoviruses. Overall, the SNAP strategy provides a new direction for the development of antivirus agents against SARS-CoV-2 and other emerging coronaviruses.

NK cell receptor and ligand composition influences the clearance of SARS-CoV-2.

To explore how the immune system controls clearance of SARS-CoV-2, we used a single-cell, mass cytometry-based proteomics platform to profile the immune systems of 21 patients who had recovered from SARS-CoV-2 infection without need for admission to an intensive care unit or for mechanical ventilation. We focused on receptors involved in interactions between immune cells and virus-infected cells. We found that the diversity of receptor repertoires on natural killer (NK) cells was negatively correlated with the viral clearance rate. In addition, NK subsets expressing the receptor DNAM1 were increased in patients who more rapidly recovered from infection. Ex vivo functional studies revealed that NK subpopulations with high DNAM1 expression had cytolytic activities in response to target cell stimulation. We also found that SARS-CoV-2 infection induced the expression of CD155 and nectin-4, ligands of DNAM1 and its paired coinhibitory receptor TIGIT, which counterbalanced the cytolytic activities of NK cells. Collectively, our results link the cytolytic immune responses of NK cells to the clearance of SARS-CoV-2 and show that the DNAM1 pathway modulates host-pathogen interactions during SARS-CoV-2 infection.

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.

Antiplatelet therapy and outcome in COVID-19: the Health Outcome Predictive Evaluation Registry.

BACKGROUND: Standard therapy for COVID-19 is continuously evolving. Autopsy studies showed high prevalence of platelet-fibrin-rich microthrombi in several organs. The aim of the study was therefore to evaluate the safety and efficacy of antiplatelet therapy (APT) in hospitalised patients with COVID-19 and its impact on survival. METHODS: 7824 consecutive patients with COVID-19 were enrolled in a multicentre international prospective registry (Health Outcome Predictive Evaluation-COVID-19 Registry). Clinical data and in-hospital complications were recorded. Data on APT, including aspirin and other antiplatelet drugs, were obtained for each patient. RESULTS: During hospitalisation, 730 (9%) patients received single APT (93%, n=680) or dual APT (7%, n=50). Patients treated with APT were older (74±12 years vs 63±17 years, p<0.01), more frequently male (68% vs 57%, p<0.01) and had higher prevalence of diabetes (39% vs 16%, p<0.01). Patients treated with APT showed no differences in terms of in-hospital mortality (18% vs 19%, p=0.64), need for invasive ventilation (8.7% vs 8.5%, p=0.88), embolic events (2.9% vs 2.5% p=0.34) and bleeding (2.1% vs 2.4%, p=0.43), but had shorter duration of mechanical ventilation (8±5 days vs 11±7 days, p=0.01); however, when comparing patients with APT versus no APT and no anticoagulation therapy, APT was associated with lower mortality rates (log-rank p<0.01, relative risk 0.79, 95% CI 0.70 to 0.94). On multivariable analysis, in-hospital APT was associated with lower mortality risk (relative risk 0.39, 95% CI 0.32 to 0.48, p<0.01). CONCLUSIONS: APT during hospitalisation for COVID-19 could be associated with lower mortality risk and shorter duration of mechanical ventilation, without increased risk of bleeding. TRIAL REGISTRATION NUMBER: NCT04334291.

Predictors of poor prognosis in healthy, young, individuals with SARS-CoV-2 infections.

OBJECTIVES: To identify predictors of poor prognosis in previously healthy young individuals admitted to hospital with coronavirus disease 2019 (COVID-19). METHODS: We studied a cohort of patients hospitalized with COVID-19. All patients without co-morbidities, without usual treatments and ≤65 years old were selected from an international registry (HOPE-COVID-19, NCT04334291). We focused on baseline variables-symptoms and signs at admission-to analyse risk factors for poor prognosis. The primary end point was a composite of major adverse clinical events during hospitalization including mortality, mechanical ventilation, high-flow nasal oxygen therapy, prone, sepsis, systemic inflammatory response syndrome and embolic events. RESULTS: Overall, 773 healthy young patients were included. The primary composite end point was observed in 29% (225/773) and the overall mortality rate was 3.6% (28/773). In the combined event group, 75% (168/225) of patients were men and the mean age was 49 (±11) years, whereas in the non-combined event group, the prevalence of male gender was 43% (238/548) and the mean age was 42 (±13) years (p < 0.001 for both). On admission, respiratory insufficiency and cough were described in 51.4% (114/222) and 76% (170/223) of patients, respectively, in the combined event group, versus 7.9% (42/533) and 56% (302/543) of patients in the other group (p < 0.001 for both). The strongest independent predictor for the combined end point was desaturation (Spo2 <92%) (OR 5.40; 95% CI 3.34-8.75; p < 0.001), followed by tachypnoea (OR 3.17; 95% CI 1.93-5.21; p < 0.001), male gender (OR 3.01; 95% CI 1.96-4.61; p < 0.001) and pulmonary infiltrates on chest X-ray at admission (OR 2.21; 95% CI 1.18-4.16; p 0.014). CONCLUSIONS: Major adverse clinical events were unexpectedly high considering the baseline characteristics of the cohort. Signs of respiratory compromise at admission and male gender, were predictive for poor prognosis among young healthy patients hospitalized with COVID-19.

CT-Based Radiomics Helps to Predict Residual Lung Lesions in COVID-19 Patients at Three Months after Discharge.

BACKGROUND: In this study, our focus was on pulmonary sequelae of coronavirus disease 2019 (COVID-19). We aimed to develop and validate CT-based radiomic models for predicting the presence of residual lung lesions in COVID-19 survivors at three months after discharge. METHODS: We retrospectively enrolled 162 COVID-19 confirmed patients in our hospital (84 patients with residual lung lesions and 78 patients without residual lung lesions, at three months after discharge). The patients were all randomly allocated to a training set (n = 114) or a test set (n = 48). Radiomic features were extracted from chest CT images in different regions (entire lung or lesion) and at different time points (at hospital admission or at discharge) to build different models, sequentially, or in combination, as follows: (1) Lesion_A model (based on the lesion region at admission CT); (2) Lesion_D model (based on the lesion region at discharge CT); (3) Δlesion model (based on the lesion region at admission CT and discharge CT); (4) Lung_A model (based on the lung region at admission CT); (5) Lung_D model (based on the lung region at discharge CT); (6) Δlung model (based on the lung region at admission CT and discharge CT). The area under the receiver operating characteristic curve (AUC), sensitivity, and specificity were used to evaluate the predictive performances of the radiomic models. RESULTS: Among the six models, the Lesion_D and the Δlesion models achieved better predictive efficacy, with AUCs of 0.907 and 0.927, sensitivity of 0.898 and 0.763, and specificity of 0.855 and 0.964 in the training set, and AUCs of 0.875 and 0.837, sensitivity of 0.920 and 0.680, and specificity of 0.826 and 0.913 in the test set, respectively. CONCLUSIONS: The CT-based radiomic models showed good predictive effects on the presence of residual lung lesions in COVID-19 survivors at three months after discharge, which may help doctors to plan follow-up work and to reduce the psychological burden of COVID-19 survivors.