Background: Transarterial chemoembolization (TACE) is an important treatment modality for hepatocellular carcinoma (HCC). However, some patients may develop TACE refractoriness during treatment. We aimed to construct a prediction model incorporating computed tomography (CT) body composition and clinical factors to preoperatively predict the risk of developing TACE refractoriness in patients with HCC, enabling the rapid identification of patients at high risk of TACE refractoriness.Methods: This study included 128 HCC patients treated with TACE who were randomly assigned to the training (n=89) and validation groups (n=39) in a 7:3 ratio. Multiple body-composition parameters were outlined from CT images of the third lumbar vertebra level of each patient. Standardized values of body-composition parameters were calculated, such as visceral-to-subcutaneous adipose tissue area ratio (VSR). Multifactor logistic regression analysis was performed to identify independent predictors of TACE-refractoriness in patients and to develop predictive models. High-and low-risk subgroup analyses were performed for the predictive model.Results: Alpha-fetoprotein (AFP) level (P=0.041), tumor size (P=0.00 1), and VSR (P=0.04 3) were independent risk factors for TACE refractoriness. The combined clinical-body composition model had an area under the curve (AUC) value of 0.875 in the training cohort and an AUC value of 0.837 in the validation cohort. Calibration curves and decision curves revealed the specific optimal performance and clinical utility of the combined model. Subgroup analysis showed differences in predicted TACE refractoriness between the high-and low-risk groups (P<0.001).Conclusions: The combined clinical-body fat distribution model has the good performance in predicting a patient's risk of TACE refractoriness preoperatively and can help clinicians make the best clinical decisions in advance for the treatment of high-risk patients.

Viruses encode strategies to degrade cellular proteins to promote infection and pathogenesis. Here, we revealed that the non-structural protein NSs of Rift Valley fever virus forms a filamentous E3 ligase to trigger efficient degradation of targeted proteins. Reconstitution in vitro and cryoelectron microscopy analysis with the 2.9-Å resolution revealed that NSs forms right-handed helical fibrils. The NSs filamentous oligomers associate with the cellular FBXO3 to form a remodeled E3 ligase. The NSs-FBXO3 E3 ligase targets the cellular TFIIH complex through the NSs-P62 interaction, leading to ubiquitination and proteasome-dependent degradation of the TFIIH complex. NSs-FBXO3-triggered TFIIH complex degradation resulted in robust inhibition of antiviral immunity and promoted viral pathogenesis in vivo. Furthermore, it is demonstrated that NSs can be programmed to target additional proteins for proteasome-dependent degradation, serving as a versatile targeted protein degrader. These results showed that a virulence factor forms a filamentous and programmable degradation machinery to induce organized degradation of cellular proteins to promote viral infection.

SARS-CoV-2 infection can trigger strong inflammatory responses and cause severe lung damage in COVID-19 patients with critical illness. However, the molecular mechanisms by which the infection induces excessive inflammatory responses are not fully understood. Here, we report that SARS-CoV-2 infection results in the formation of viral Z-RNA in the cytoplasm of infected cells and thereby activates the ZBP1-RIPK3 pathway. Pharmacological inhibition of RIPK3 by GSK872 or genetic deletion of MLKL reduced SARS-CoV-2-induced IL-1β release. ZBP1 or RIPK3 deficiency leads to reduced production of both inflammatory cytokines and chemokines during SARS-CoV-2 infection both in vitro and in vivo. Furthermore, deletion of ZBP1 or RIPK3 alleviated SARS-CoV-2 infection-induced immune cell infiltration and lung damage in infected mouse models. These results suggest that the ZBP1-RIPK3 pathway plays a critical role in SARS-CoV-2-induced inflammatory responses and lung damage. Our study provides novel insights into how SARS-CoV-2 infection triggers inflammatory responses and lung pathology, and implicates the therapeutic potential of targeting ZBP1-RIPK3 axis in treating COVID-19.

PURPOSE:To investigate the mechanism of action underlying the effective treatment of New Coronavirus Pneumonia Agreement Prescription (NCPAP) on 2019 Novel Coronavirus-Infected Pneumonia (2019-NCIP) using network pharmacology.METHODS:In this retrospective study, 50 patients with 2019-NCIP were recruited, including 16 who received symptomatic treatment and 34 that received NCPAP formula treatment on the basis of symptomatic treatment. Hospitalization and lymphocyte percentages were served as efficacy evaluation indicators. Moreover, pharmacological analysis was performed to identify the target disease of NCPAP. Active ingredients in herbs were screened using the Traditional Chinese Medications Systems Pharmacology (TCMSP) database, and related target genes were identified. We then queried therapeutic target data for coronavirus-associated genes. The protein-protein interaction network was constructed to examine the relationships between these targets. Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) network enrichment analyses were conducted using the Database for Annotation, Visualization and Integrated Discovery (DAVID) database.RESULTS:NCPAP significantly reduced hospitalization time and increased both the absolute value and percentage of lymphocytes. Bioinformatics and cytokine analysis suggested that preventing cytokine storm syndrome and regulating immune response are the key mechanisms of NCPAP in treating 2019-NCIP.CONCLUSIONS:The possible mechanisms of NCPAP in the treatment of 2019-NCIP are reduction of cytokine storms and regulation of the immune response.

Background Macrotrabecular-massive (MTM) subtype of hepatocellular carcinoma (HCC) is an aggressive variant associated with angiogenesis and immunosuppressive tumor microenvironment, which is expected to be noninvasively identified using radiomics approaches. Purpose To construct a CT radiomics model to predict the MTM subtype and to investigate the underlying immune infiltration patterns. Materials and Methods This study included five retrospective data sets and one prospective data set from three academic medical centers between January 2015 and December 2021. The preoperative liver contrast-enhanced CT studies of 365 adult patients with resected HCC were evaluated. The Third Xiangya Hospital of Central South University provided the training set and internal test set, while Yueyang Central Hospital and Hunan Cancer Hospital provided the external test sets. Radiomic features were extracted and used to develop a radiomics model with machine learning in the training set, and the performance was verified in the two test sets. The outcomes cohort, including 58 adult patients with advanced HCC undergoing transarterial chemoembolization and antiangiogenic therapy, was used to evaluate the predictive value of the radiomics model for progression-free survival (PFS). Bulk RNA sequencing of tumors from 41 patients in The Cancer Genome Atlas (TCGA) and single-cell RNA sequencing from seven prospectively enrolled participants were used to investigate the radiomics-related immune infiltration patterns. Area under the receiver operating characteristics curve of the radiomics model was calculated, and Cox proportional regression was performed to identify predictors of PFS. Results Among 365 patients (mean age, 55 years ± 10 [SD]; 319 men) used for radiomics modeling, 122 (33%) were confirmed to have the MTM subtype. The radiomics model included 11 radiomic features and showed good performance for predicting the MTM subtype, with AUCs of 0.84, 0.80, and 0.74 in the training set, internal test set, and external test set, respectively. A low radiomics model score relative to the median value in the outcomes cohort was independently associated with PFS (hazard ratio, 0.4; 95% CI: 0.2, 0.8; P = .01). The radiomics model was associated with dysregulated humoral immunity involving B-cell infiltration and immunoglobulin synthesis. Conclusion Accurate prediction of the macrotrabecular-massive subtype in patients with hepatocellular carcinoma was achieved using a CT radiomics model, which was also associated with defective humoral immunity. Published under a CC BY 4.0 license. Supplemental material is available for this article. See also the editorial by Yoon and Kim in this issue.

SARS-CoV-2 induced marked lymphopenia in severe patients with COVID-19. However, whether lymphocytes are targets of viral infection is yet to be determined, although SARS-CoV-2 RNA or antigen has been identified in T cells from patients. Here, we confirmed that SARS-CoV-2 viral antigen could be detected in patient peripheral blood cells (PBCs) or postmortem lung T cells, and the infectious virus could also be detected from viral antigen-positive PBCs. We next prove that SARS-CoV-2 infects T lymphocytes, preferably activated CD4 + T cells in vitro. Upon infection, viral RNA, subgenomic RNA, viral protein or viral particle can be detected in the T cells. Furthermore, we show that the infection is spike-ACE2/TMPRSS2-independent through using ACE2 knockdown or receptor blocking experiments. Next, we demonstrate that viral antigen-positive T cells from patient undergone pronounced apoptosis. In vitro infection of T cells induced cell death that is likely in mitochondria ROS-HIF-1a-dependent pathways. Finally, we demonstrated that LFA-1, the protein exclusively expresses in multiple leukocytes, is more likely the entry molecule that mediated SARS-CoV-2 infection in T cells, compared to a list of other known receptors. Collectively, this work confirmed a SARS-CoV-2 infection of T cells, in a spike-ACE2-independent manner, which shed novel insights into the underlying mechanisms of SARS-CoV-2-induced lymphopenia in COVID-19 patients.

OBJECTIVESMicrovascular invasion (MVI) is an important predictor of postoperative recurrence or poor outcomes of hepatocellular carcinoma (HCC). Radiomics is able to predict MVI in HCC preoperatively. This study aims to investigate the influence of different region of interest (ROI) sizes on CT-based radiomics model for MVI prediction in HCC.METHODSPatients with HCC with or without MVI confirmed by pathology and those who underwent preoperative plain or enhanced abdominal CT scans in the Third Xiangya Hospital of Central South University from January 2010 to December 2020 were retrospectively and consecutively included. According to the ratio of 7 to 3, the patients were randomly assigned into a training set and a validation set. Clinical data were collected from medical records, and radiomics features were extracted from the arterial phase (AP) and portal venous phase (PVP) of preoperatively acquired CT in all patients. Six different ROI sizes were employed. The original ROI (OROI) was manually delineated along the visible borders of the tumor layer-by-layer. The OROI was expanded out by 1-5 mm. The OROI was combined with 5 different peritumoral regions to generate the other 5 ROIs, named Plus1-Plus5. Feature extraction, dimension reduction, and model development were conducted in 6 different ROIs separately. Supporter vector machine (SVM) was used for model construction. Model performance was assessed via receiver operating characteristic (ROC) curve.RESULTSA total of 172 HCC patients were included, in which 83 (48.3%) were MVI positive, and 89 (51.7%) were MVI negative. Three hundred and ninety-six features based on AP or PVP images were extracted from each ROI. After feature selection and dimension reduction, 4, 5, 15, 11, 6, and 3 features of OROI, Plus1, Plus2, Plus 3, Plus4, and Plus5 were selected for model construction, respectively. In the training set, the sensitivity, specificity, and area under the curve (AUC) of OROI were 0.759, 0.806, and 0.855, respectively. The AUC values of Plus2 (0.979) and Plus3 (0.954) were higher than that of OROI. The AUC values of Plus1 (0.802), Plus4 (0.792), and Plus5 (0.774) were not significantly different from those of OROI. In the validation set, the sensitivity, specificity, and AUC value of OROI were 0.640, 0.630, and 0.664, respectively. The AUC value of Plus3 was 0.903, which was higher than that of OROI. The AUC values of Plus1 (0.679), Plus2 (0.536), Plus4 (0.708), and Plus5 (0.757) were not significantly different from that of OROI (P>0.05).CONCLUSIONSThe size of ROI significantly inflluences on the performance of CT-based radiomics model for MVI prediction in HCC. Including appropriate area around the tumor into ROI could improve the predictive performance of the model, and 3 mm might be appropriate distance.

Patients with COVID-19 generally raise antibodies against SARS-CoV-2 following infection, and the antibody level is positively correlated to the severity of disease. Whether the viral antibodies exacerbate COVID-19 through antibody-dependent enhancement (ADE) is still not fully understood. Here, we conducted in vitro assessment of whether convalescent serum enhanced SARS-CoV-2 infection or induced excessive immune responses in immune cells. Our data revealed that SARS-CoV-2 infection of primary B cells, macrophages and monocytes, which express variable levels of FcγR, could be enhanced by convalescent serum from COVID-19 patients. We also determined the factors associated with ADE, and found which showed a time-dependent but not viral-dose dependent manner. Furthermore, the ADE effect is not associated with the neutralizing titer or RBD antibody level when testing serum samples collected from different patients. However, it is higher in a medium level than low or high dilutions in a given sample that showed ADE effect, which is similar to dengue. Finally, we demonstrated more viral genes or dysregulated host immune gene expression under ADE conditions compared to the no-serum infection group. Collectively, our study provides insight into the understanding of an association of high viral antibody titer and severe lung pathology in severe patients with COVID-19.

To develop and validate a machine learning model for the prediction of adverse outcomes in hospitalized patients with COVID-19. We included 424 patients with non-severe COVID-19 on admission from January 17, 2020, to February 17, 2020, in the primary cohort of this retrospective multicenter study. The extent of lung involvement was quantified on chest CT images by a deep learning–based framework. The composite endpoint was the occurrence of severe or critical COVID-19 or death during hospitalization. The optimal machine learning classifier and feature subset were selected for model construction. The performance was further tested in an external validation cohort consisting of 98 patients. There was no significant difference in the prevalence of adverse outcomes (8.7% vs. 8.2%, p = 0.858) between the primary and validation cohorts. The machine learning method extreme gradient boosting (XGBoost) and optimal feature subset including lactic dehydrogenase (LDH), presence of comorbidity, CT lesion ratio (lesion%), and hypersensitive cardiac troponin I (hs-cTnI) were selected for model construction. The XGBoost classifier based on the optimal feature subset performed well for the prediction of developing adverse outcomes in the primary and validation cohorts, with AUCs of 0.959 (95% confidence interval [CI]: 0.936–0.976) and 0.953 (95% CI: 0.891–0.986), respectively. Furthermore, the XGBoost classifier also showed clinical usefulness. We presented a machine learning model that could be effectively used as a predictor of adverse outcomes in hospitalized patients with COVID-19, opening up the possibility for patient stratification and treatment allocation. • Developing an individually prognostic model for COVID-19 has the potential to allow efficient allocation of medical resources. • We proposed a deep learning–based framework for accurate lung involvement quantification on chest CT images. • Machine learning based on clinical and CT variables can facilitate the prediction of adverse outcomes of COVID-19.

Background Macrotrabecular-massive (MTM) subtype and vessels encapsulating tumor clusters (VETC) pattern of hepatocellular carcinoma (HCC) are associated with unfavorable prognosis. Purpose To estimate the potential of preoperative CT in the prediction of MTM subtype and VETC pattern. Materials and Methods Patients who underwent surgical resection or liver transplant and preoperative CT for HCC between January 2015 and June 2018 were retrospectively included in the primary cohort. CT imaging features were evaluated by two radiologists. Predictors associated with the MTM subtype or VETC pattern were determined by using logistic regression analyses and the performance was tested in a validation cohort. Prognostic factors associated with early recurrence after surgical resection were identified by using Cox regression analyses. Results The primary cohort included 170 patients (median age, 55 years; interquartile range, 48-63 years; 152 men). Serum α-fetoprotein level higher than 100 ng/mL (odds ratio [OR], 4.3; 95% CI: 2.1, 9.2; P < .001), intratumor necrosis (OR, 5.2; 95% CI: 2.5, 11.0; P < .001), and intratumor hemorrhage (OR, 5.4; 95% CI: 1.3, 23.3; P = .02) were independent predictors for MTM subtype, whereas tumor size greater than 5 cm (OR, 3.8; 95% CI: 1.7, 8.1; P = .001) and intratumor necrosis (OR, 2.1; 95% CI: 1.0, 4.4; P = .045) were independent predictors for VETC pattern. These features were used for the construction of ANH and SN scores (where A is α-fetoprotein level, N is necrosis, H is hemorrhage, and S is size), respectively, which showed comparable prediction performance in the primary and validation cohorts. Preoperative high ANH and high SN phenotype (hazard ratio, 1.9; 95% CI: 1.2, 3.0; P = .01) was independently associated with early recurrence after surgical resection. Conclusion Preoperative CT features could be used for the characterization of macrotrabecular-massive subtype and vessels that encapsulate tumor clusters pattern and were of prognostic significance for early recurrence in patients with hepatocellular carcinoma. Online supplemental material is available for this article. See also the editorial by Yoon and Kim in this issue. Published under a CC BY 4.0 license.

Abstract Novel Coronavirus disease 2019 (COVID‐19) has spread rapidly around the world. Individuals with immune dysregulation and/or on immunosuppressive therapy, such as rheumatic patients, are considered at greater risk for infections. However, the risks of patients with each subcategory of rheumatic diseases have not been reported. Here, we identified 100 rheumatic patients from 18,786 COVID‐19 patients hospitalized in 23 centers affiliated to Hubei COVID‐19 Rheumatology Alliance between January 1 and April 1, 2020. Demographic information, medical history, length of hospital stay, classification of disease severity, symptoms and signs, laboratory tests, disease outcome, computed tomography, and treatments information were collected. Compared to gout and ankylosing spondylitis (AS) patients, patients with connective tissue disease (CTD) tend to be more severe after COVID‐19 infection (p = 0.081). CTD patients also had lower lymphocyte counts, hemoglobin, and platelet counts (p values were 0.033, < 0.001, and 0.071, respectively). Hydroxychloroquine therapy and low‐ to medium‐dose glucocorticoids before COVID‐19 diagnosis reduced the progression of COVID‐19 to severe/critical conditions (p = 0.001 for hydroxychloroquine; p = 0.006 for glucocorticoids). Our data suggests that COVID‐19 in CTD patients may be more severe compared to patients with AS or gout.

Objective: Macrotrabecular-massive (MTM) subtype represents an aggressive form of hepatocellular carcinoma (HCC) that is associated with angiogenesis activation. We aimed to develop and validate a radiomics approach for identification of MTM subtype and explore its role in predicting response to transarterial chemoembolization (TACE) plus antiangiogenic therapy.Methods: This retrospective multicohort study consisted of five independent cohorts. XY3A cohort, XY3B cohort, and YY&HC cohort including 365 surgically resected patients with preoperative liver contrast-enhanced CT imaging data were used to train and internally and externally validate a noninvasive radiomics signature (RS). The association of the RS with angiogenesis activation gene expression was analyzed in a TCGA-LIHC cohort including 41 patients. A dataset including 58 advanced patients receiving TACE plus antiangiogenic therapy, was used to evaluate the predictive value of the RS in terms of clinical outcomes.Results: We developed the RS that included 11 radiomics features, showing good performance for identifying MTM subtype, with the AUCs of 0.837, 0.795, and 0.735 in the XY3A cohort, XY3B cohort, and YY&HC cohort, respectively. A clinical-radiomics model (CRM) that integrated the RS and high serum α-fetoprotein level showed good discrimination and calibration in the three cohorts (AUCs of 0.876, 0.817, and 0.767, respectively), though without significant improvement compared with the RS (all P > 0.05). The RS score was significantly correlated with VEGFA gene expression level (rho = -0.342, P = 0.029). In the treatment cohort, a lower baseline RS score was found in those who achieved an objective response (P = 0.008) or disease control (P = 0.033), and was independently associated with improved progression-free survival (HR, 0.478; 95% CI: 0.237, 0.963, P = 0.039).Conclusions: The preoperative CT-derived RS allows for accurate characterization of MTM subtype and helps to infer clinical outcomes in advanced patients receiving TACE plus antiangiogenic therapy.Funding: Wisdom Accumulation and Talent Cultivation Project of The Third Xiangya Hospital of Central South University.Declaration of Interest: None to declare, Ethical Approval: This retrospective study was compliant with Health Insurance Portability andAccountability Act (HIPAA) and approved by the Institutional Review Board (IRB) ofThe Third Xiangya Hospital, Central South University.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection can lead to respiratory illness and multi-organ failure in critically ill patients. Although the virus-induced lung damage and inflammatory cytokine storm are believed to be directly associated with coronavirus disease 2019 (COVID-19) clinical manifestations, the underlying mechanisms of virus-triggered inflammatory responses are currently unknown. Here we report that SARS-CoV-2 infection activates caspase-8 to trigger cell apoptosis and inflammatory cytokine processing in the lung epithelial cells. The processed inflammatory cytokines are released through the virus-induced necroptosis pathway. Virus-induced apoptosis, necroptosis, and inflammation activation were also observed in the lung sections of SARS-CoV-2-infected HFH4-hACE2 transgenic mouse model, a valid model for studying SARS-CoV-2 pathogenesis. Furthermore, analysis of the postmortem lung sections of fatal COVID-19 patients revealed not only apoptosis and necroptosis but also massive inflammatory cell infiltration, necrotic cell debris, and pulmonary interstitial fibrosis, typical of immune pathogenesis in the lung. The SARS-CoV-2 infection triggered a dual mode of cell death pathways and caspase-8-dependent inflammatory responses may lead to the lung damage in the COVID-19 patients. These discoveries might assist the development of therapeutic strategies to treat COVID-19.

AbstractObjectiveTo determine the predictive value of CT and clinical characteristics for short-term disease progression in patients with 2019 novel coronavirus pneumonia (NCP).Materials and Methods224 patients with confirmed 2019 novel coronavirus (COVID-19) infection outside Wuhan who had chest CT examinations were retrospectively screened. Clinical data were obtained from electronic medical records. CT images were reviewed and scored for lesion distribution, lobe and segment involvement, ground-glass opacities, consolidation, and interstitial thickening. All included patients with moderate NCP were observed for at least 14 days from admission to determine whether they exacerbated to severe NCP (progressive group) or not (stable group). CT and clinical characteristics between the two groups were compared, and multivariate logistic regression and sensitivity analyses were performed to identify the risk factors for developing severe NCP.ResultsA total of 141 patients with moderate NCP were included, of which 15 (10.6%) patients developed severe NCP during hospitalization and assigned to the progressive group. Multivariate logistic regression analysis showed that higher neutrophil-to-lymphocyte ratio (NLR) (odds ratio [OR] and 95% confidence interval [CI], 1.26 [1.04-1.53];P= 0.018) and CT severity score (OR and 95% CI, 1.25 [1.08-1.46];P= 0.004) on admission were independent predictors for progression to severe NCP, and sensitivity analysis confirmed the consistent results in nonimported patients but not in imported patients. However, no significant difference in lung involvement was found on CT between imported and nonimported patients (allP> 0.05). Patients who were admitted more than 4 days from symptom onset tended to have more severe lung involvement. Spearman correlation analysis showed the close association between CT severity score and inflammatory indexes (r= 0.17∼0.47, allP< 0.05).ConclusionCT severity score was associated with inflammatory levels and higher NLR and CT severity score on admission were independent risk factors for short-term progression in patients with NCP outside Wuhan. Furthermore, early admission and surveillance by CT should be recommended to improve clinical outcomes.

ABSTRACT IMPORTANCE Coronavirus disease 2019 (COVID-19) is a global pandemic associated with high mortality and effective treatment to prevent clinical deterioration to severe pneumonia has not yet been well clarified. OBJECTIVE To investigate the role of several adjuvant treatments in preventing severe pneumonia in patients with COVID-19. DESIGN, SETTING, AND PARTICIPANTS Multicenter, retrospective cohort study of 564 consecutively hospitalized patients with confirmed COVID-19 at Third Xiangya Hospital of Central South University, Changsha Public Health Treatment Center, First Hospital of Yueyang, Junshan People’s Hospital of Yueyang, Central Hospital of Shaoyang, Central Hospital of Xiangtan, Second Hospital of Changde, Central Hospital of Loudi, and First Affiliated Hospital of University of South China in Hunan province from January 17, 2020 to February 28, 2020; The final date of follow-up was March 15, 2020. EXPOSURES Nonspecific antivirals (arbidol, lopinavir/ritonavir, and interferon α), antihypertensives, and chloroquine. MAIN OUTCOMES AND MEASURES The development of severe COVID-19 pneumonia; Demographic, epidemiological, clinical, laboratory, radiological, and treatment data were collected and analyzed. RESULTS Of 564 patients, the median age was 47 years (interquartile range, 36-58 years), and 284 (50.4%) patients were men. Sixty-nine patients (12.2%) developed severe pneumonia. Patients who developed severe pneumonia were older (median age of 59 and 45 years, respectively), and more patients had comorbidities including hypertension (30.4% and 12.3%, respectively), diabetes (17.4% and 6.7%, respectively), and cardiovascular disease (8.7% and 3.2%, respectively) and presented with fever (84.1% and 60.4%, respectively) and shortness of breath (10.1% and 3.8%, respectively) compared with those who did not. Nonspecific antiviral therapy did not prevent clinical progression to severe pneumonia, although fewer hypertensive patients on angiotensin-converting enzyme inhibitors or angiotensin-receptor blockers (ACEI/ARB) therapy developed severe pneumonia in contrast with those on non-ACEI/ARB antihypertensive therapy (1 of 16 [6.3%] patients and 16 of 49 [32.7%] patients, respectively [difference, 26.4%; 95% CI, 1.5% to 41.3%]). Multivariate logistic regression analysis showed that hypertension without receiving ACEI/ARB therapy was an independent risk factor (odds ratio [OR], 2.07; 95% CI, 1.07 to 4.00) for developing severe pneumonia irrespective of age. Besides, none of patients treated with chloroquine developed severe pneumonia, though without significance (difference, 12.0%; 95% CI, −3.5% to 30.0%) by propensity score matching. CONCLUSIONS AND RELEVANCE Hypertensive patients on ACEI or ARB may be protective from severe pneumonia in COVID-19 and hence these therapies should not be ceased unless there is a strong indication or further epidemiological evidence. Though none of the current antiviral and immunoregulation therapy showed benefit in preventing COVID-19 progression, chloroquine deserved further investigation. KEYPOINTS Question Does the use of adjuvant therapy reduce progression to severe pneumonia in patients with coronavirus disease 2019 (COVID-19)? Findings In this retrospective, observational cohort study involving 564 patients with confirmed COVID-19, hypertension was an independent risk factor for progression to severe pneumonia irrespective of age and those on angiotensin-converting enzyme inhibitor (ACEI) or angiotensin receptor blocker (ARB) therapy were less likely to develop severe COVID-19 pneumonia, while nonspecific antivirals or chloroquine did not have significant impact on clinical progression. Meaning Hypertensive patients with COVID-19 should not have ACEI or ARB ceased, unless there is a strong indication or further epidemiological evidence, given its potential protective effects.

Coronavirus disease 2019 (COVID-19) is a global pandemic associated with a high mortality. Our study aimed to determine the clinical risk factors associated with disease progression and prolonged viral shedding in patients with COVID-19. Consecutive 564 hospitalized patients with confirmed COVID-19 between January 17, 2020 and February 28, 2020 were included in this multicenter, retrospective study. The effects of clinical factors on disease progression and prolonged viral shedding were analyzed using logistic regression and Cox regression analyses. 69 patients (12.2%) developed severe or critical pneumonia, with a higher incidence in the elderly and in individuals with underlying comorbidities, fever, dyspnea, and laboratory and imaging abnormalities at admission. Multivariate logistic regression analysis indicated that older age (odds ratio [OR], 1.04; 95% confidence interval [CI], 1.02-1.06), hypertension without receiving angiotensinogen converting enzyme inhibitors or angiotensin receptor blockers (ACEI/ARB) therapy (OR, 2.29; 95% CI, 1.14-4.59), and chronic obstructive pulmonary disease (OR, 7.55; 95% CI, 2.44-23.39) were independent risk factors for progression to severe or critical pneumonia. Hypertensive patients without receiving ACEI/ARB therapy showed higher lactate dehydrogenase levels and computed tomography (CT) lung scores at about 3 days after admission than those on ACEI/ARB therapy. Multivariate Cox regression analysis revealed that male gender (hazard ratio [HR], 1.22; 95% CI, 1.02-1.46), receiving lopinavir/ritonavir treatment within 7 days from illness onset (HR, 0.75; 95% CI, 0.63-0.90), and receiving systemic glucocorticoid therapy (HR, 1.79; 95% CI, 1.46-2.21) were independent factors associated with prolonged viral shedding. Our findings presented several potential clinical factors associated with developing severe or critical pneumonia and prolonged viral shedding, which may provide a rationale for clinicians in medical resource allocation and early intervention.

BackgroundIn the ongoing COVID-19 pandemic, the susceptibility of patients with rheumatic diseases to COVID-19 remains unclear. We aimed to investigate susceptibility to COVID-19 in patients with autoimmune rheumatic diseases during the ongoing COVID-19 pandemic.MethodsWe did a multicentre retrospective study of patients with autoimmune rheumatic diseases in Hubei province, the epicentre of the COVID-19 outbreak in China. Patients with rheumatic diseases were contacted through an automated telephone-based survey to investigate their susceptibility to COVID-19. Data about COVID-19 exposure or diagnosis were collected. Families with a documented history of COVID-19 exposure, as defined by having at least one family member diagnosed with COVID-19, were followed up by medical professionals to obtain detailed information, including sex, age, smoking history, past medical history, use of medications, and information related to COVID-19.FindingsBetween March 20 and March 30, 2020, 6228 patients with autoimmune rheumatic diseases were included in the study. The overall rate of COVID-19 in patients with an autoimmune rheumatic disease in our study population was 0·43% (27 of 6228 patients). We identified 42 families in which COVID-19 was diagnosed between Dec 20, 2019, and March 20, 2020, in either patients with a rheumatic disease or in a family member residing at the same physical address during the outbreak. Within these 42 families, COVID-19 was diagnosed in 27 (63%) of 43 patients with a rheumatic disease and in 28 (34%) of 83 of their family members with no rheumatic disease (adjusted odds ratio [OR] 2·68 [95% CI 1·14–6·27]; p=0·023). Patients with rheumatic disease who were taking hydroxychloroquine had a lower risk of COVID-19 infection than patients taking other disease-modifying anti-rheumatic drugs (OR 0·09 [95% CI 0·01–0·94]; p=0·044). Additionally, the risk of COVID-19 was increased with age (adjusted OR 1·04 [95%CI 1·01–1·06]; p=0·0081).InterpretationPatients with autoimmune rheumatic disease might be more susceptible to COVID-19 infection than the general population.FundingNational Natural Science Foundation of China and the Tongji Hospital Clinical Research Flagship Program.