Chest computed tomography radiomics to predict the outcome for patients with COVID-19 at an early stage

PURPOSE: Early monitoring and intervention for patients with novel coronavirus disease-2019 (COVID-19) will benefit both patients and the medical system. Chest computed tomography (CT) radiomics provide more information regarding the prognosis of COVID-19. METHODS: A total of 833 quantitative features of 157 COVID-19 patients in the hospital were extracted. By filtering unstable features using the least absolute shrinkage and selection operator algorithm, a radiomic signature was built to predict the prognosis of COVID-19 pneumonia. The main outcomes were the area under the curve (AUC) of the prediction models for death, clinical stage, and complications. Internal validation was performed using the bootstrapping validation technique. RESULTS: The AUC of each model demonstrated good predictive accuracy [death, 0.846; stage, 0.918; complication, 0.919; acute respiratory distress syndrome (ARDS), 0.852]. After finding the optimal cut-off for each outcome, the respective accuracy, sensitivity, and specificity were 0.854, 0.700, and 0.864 for the prediction of the death of COVID-19 patients; 0.814, 0.949, and 0.732 for the prediction of a higher stage of COVID-19; 0.846, 0.920, and 0.832 for the prediction of complications of COVID-19 patients; and 0.814, 0.818, and 0.814 for ARDS of COVID-19 patients. The AUCs after bootstrapping were 0.846 [95% confidence interval (CI): 0.844-0.848] for the death prediction model, 0.919 (95% CI: 0.917-0.922) for the stage prediction model, 0.919 (95% CI: 0.916-0.921) for the complication prediction model, and 0.853 (95% CI: 0.852-0.0.855) for the ARDS prediction model in the internal validation. Based on the decision curve analysis, the radiomics nomogram was clinically significant and useful. CONCLUSION: The radiomic signature from the chest CT was significantly associated with the prognosis of COVID-19. A radiomic signature model achieved maximum accuracy in the prognosis prediction. Although our results provide vital insights into the prognosis of COVID-19, they need to be verified by large samples in multiple centers.

Small molecules in the treatment of COVID-19.

The outbreak of COVID-19 has become a global crisis, and brought severe disruptions to societies and economies. Until now, effective therapeutics against COVID-19 are in high demand. Along with our improved understanding of the structure, function, and pathogenic process of SARS-CoV-2, many small molecules with potential anti-COVID-19 effects have been developed. So far, several antiviral strategies were explored. Besides directly inhibition of viral proteins such as RdRp and Mpro, interference of host enzymes including ACE2 and proteases, and blocking relevant immunoregulatory pathways represented by JAK/STAT, BTK, NF-κB, and NLRP3 pathways, are regarded feasible in drug development. The development of small molecules to treat COVID-19 has been achieved by several strategies, including computer-aided lead compound design and screening, natural product discovery, drug repurposing, and combination therapy. Several small molecules representative by remdesivir and paxlovid have been proved or authorized emergency use in many countries. And many candidates have entered clinical-trial stage. Nevertheless, due to the epidemiological features and variability issues of SARS-CoV-2, it is necessary to continue exploring novel strategies against COVID-19. This review discusses the current findings in the development of small molecules for COVID-19 treatment. Moreover, their detailed mechanism of action, chemical structures, and preclinical and clinical efficacies are discussed.

Albumin Infusion May Improve the Prognosis of Critical COVID-19 Patients with Hypoalbuminemia in the Intensive Care Unit: A Retrospective Cohort Study.

Background: The coronavirus disease 2019 (COVID-19) pandemic has caused enormous mortality worldwide. Low albumin level is a risk factor for increasing mortality among patients in the intensive care unit (ICU). This study investigated the effect of albumin infusion on critical COVID-19 patients with hypoalbuminemia. Methods: A total of 114 COVID-19 ICU patients with hypoalbuminemia were recruited from Wuhan Leishenshan Hospital and Zhongnan Hospital of Wuhan University. Clinical features and laboratory variables were collected through electronic medical records. The cohorts were divided into two groups: albumin infusion and non-albumin infusion. Propensity-matched analysis was used to compare patients who received albumin to controls. Statistical analyses were used to investigate the survival time and inflammation-related blood biomarkers between groups. Results: Lactate dehydrogenase, interleukin (IL)-6, IL-2 receptor, and IL-8 levels were significantly downregulated in the albumin infusion group. Significant upregulations of lymphocyte counts and IL-10 were found in the albumin infusion group. There was a negative association between albumin level and D-dimer or procalcitonin levels after treatment. The albumin infusion group had a significantly longer survival time and shorter hospitalization time than control patients. Notably, a 1g increase in albumin level reduced the risk of death by approximately 7.3% after adjusting for age and sex. Patients with increased albumin levels after treatment had better prognoses than those without. Conclusion: Albumin administration can regulate COVID-19-related biomarkers and reduce the risk of death in critical patients with hypoalbuminemia. Clinicians should pay more attention to these risk factors. Targeted clinical interventions should be implemented to minimize the negative impacts of hypoalbuminemia and improve disease outcomes.

Identification of CKD, bedridden history and cancer as higher-risk comorbidities and their impact on prognosis of hospitalized Omicron patients: a multi-centre cohort study.

To further describe the effect of the "fragile population" and their "higher-risk" comorbidities on prognosis among hospitalized Omicron patients, this observational cohort study enrolled hospitalized patients confirmed with SARS-CoV-2 during the 2022 Omicron wave in Shanghai, China. The primary outcome was progression to severe or critical cases. The secondary outcome was viral shedding time from the first positive SARS-CoV-2 detection. A total of 847 participants were enrolled, most of whom featured as advanced age (>70 years old: 30.34%), not fully vaccinated (55.84%), combined with at least 1 comorbidity (65.41%). Multivariate cox regression suggested age >70 years old (aHR[95%CI] 0.78[0.61-0.99]), chronic kidney disease (CKD) stage 4-5 (aHR[95%CI] 0.61[0.46-0.80]), heart conditions (aHR[95%CI] 0.76[0.60-0.97]) would elongate viral shedding time and fully/booster vaccination (aHR[95%CI] 1.4 [1.14-1.72]) would shorten this duration. Multivariate logistic regression suggested CKD stage 4-5 (aHR[95%CI] 3.21[1.45-7.27]), cancer (aHR[95%CI] 9.52[4.19-22.61]), and long-term bedridden status (aHR[95%CI] 4.94[2.36-10.44]) were the "higher" risk factor compared with the elderly, heart conditions, metabolic disorders, isolated hypertension, etc. for severity while female (aHR[95%CI] 0.34[0.16-0.68]) and fully/booster Vaccination (aHR[95%CI] 0.35[0.12-0.87]) could provide protection from illness progression. CKD stage 4-5, cancer and long-term bedridden history were "higher-risk" factors among hospitalized Omicron patients for severity progression while full vaccination could provide protection from illness progression.

Single-cell transcriptome landscape and antigen receptor dynamic during SARS-CoV-2 vaccination.

Vaccination by inactivated vaccine is an effective strategy to prevent the COVID-19 pandemic. However, the detailed molecular immune response at single-cell level is poorly understood. In this study, we systematically delineated the landscape of the pre- and post-vaccination single-cell transcriptome, TCR (T cell antigen receptor) and BCR (B cell antigen receptor) expression profile of vaccinated candidates. The bulk TCR sequencing analysis of COVID-19 patients was also performed. Enrichment of a clonal CD8+ T cell cluster expressing specific TCR was identified in both vaccination candidates and COVID-19 patients. These clonal CD8+ T cells showed high expression of cytotoxicity, phagosome and antigen presentation related genes. The cell-cell interaction analysis revealed that monocytes and dendritic cells could interact with these cells and initiate phagocytosis via ICAM1-ITGAM and ITGB2 signaling. Together, our study systematically deciphered the detailed immunological response during SARS-CoV-2 vaccination and infection. It may facilitate understanding the immune response and the T-cell therapy against COVID-19.

Evaluating the ability of the NLHA2 and artificial neural network models to predict COVID-19 severity, and comparing them with the four existing scoring systems.

To improve the identification and subsequent intervention of COVID-19 patients at risk for ICU admission, we constructed COVID-19 severity prediction models using logistic regression and artificial neural network (ANN) analysis and compared them with the four existing scoring systems (PSI, CURB-65, SMARTCOP, and MuLBSTA). In this prospective multi-center study, 296 patients with COVID-19 pneumonia were enrolled and split into the General-Ward-Care group (N = 238) and the ICU-Admission group (N = 58). The PSI model (AUC = 0.861) had the best results among the existing four scoring systems, followed by SMARTCOP (AUC = 0.770), motified-MuLBSTA (AUC = 0.761), and CURB-65 (AUC = 0.712). Data from 197 patients (training set) were analyzed for modeling. The beta coefficients from logistic regression were used to develop a severity prediction model and risk score calculator. The final model (NLHA2) included five covariates (consumes alcohol, neutrophil count, lymphocyte count, hemoglobin, and AKP). The NLHA2 model (training: AUC = 0.959; testing: AUC = 0.857) had similar results to the PSI model, but with fewer variable items. ANN analysis was used to build another complex model, which had higher accuracy (training: AUC = 1.000; testing: AUC = 0.907). Discrimination and calibration were further verified through bootstrapping (2000 replicates), Hosmer-Lemeshow goodness of fit testing, and Brier score calculation. In conclusion, the PSI model is the best existing system for predicting ICU admission among COVID-19 patients, while two newly-designed models (NLHA2 and ANN) performed better than PSI, and will provide a new approach for the development of prognostic evaluation system in a novel respiratory viral epidemic.

Development of a Handheld Nano-centrifugal Device for Visual Virus Detection.

Gold nanoparticles (AuNPs) colorimetric assays based on distance-dependent optical characteristics have been widely employed for bioanalysis. However, this assay is not effective for visually detecting low-concentration targets due to the faint color change. Here, we developed a handheld nano-centrifugal device which could separate the crosslinked and non-crosslinked AuNPs. Results showed that the handheld nano-centrifugal device could easily reach more than 6000 r/min within 10 s simply by stretching and tightening the coiled rope in an appropriate rhythm. Further, combined with the CRISPR/Cas12a nucleic acids recognition system, a field-deployable colorimetric platform termed handheld nano-centrifugal device assisted CRISPR/Cas12a (Hand-CRISPR) has been validated. Moreover, clinical diagnostics applications for Epstein-Barr virus (EBV) and severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) detection with high sensitivity and accuracy (100% consistency with reverse transcription quantitative real-time polymerase chain reaction (RT-qPCR) test results) have been demonstrated. Overall, the Hand-CRISPR platform showed great promise in point-of-care-test (POCT) application, expected to become a powerful supplement to the standard nucleic acid testing method in remote or poverty-stricken areas. Supplementary Information: The online version contains supplementary material available at 10.1007/s41664-022-00232-0.

Geriatric risk and protective factors for serious COVID-19 outcomes among older adults in Shanghai Omicron wave.

Shanghai has been experiencing the Omicron wave since March 2022. Though several studies have evaluated the risk factors of severe infections, the analyses of BA.2 infection risk and protective factors among geriatric people were much limited. This multicentre cohort study described clinical characteristics, and assessed risk and protective factors for geriatric Omicron severe infections. A total of 1377 patients older than 60 were enrolled, with 75.96% having comorbidities. The median viral shedding time and hospitalization time were nine and eight days, respectively. Severe and critical were associated with longer virus clearance time (aOR [95%CI]:0.706 (0.533-0.935), P = .015), while fully vaccinated/booster and paxlovid use shortened viral shedding time (1.229 [1.076-1.402], P = .002; 1.140 [0.019-1.274], P = .022, respectively). Older age (>80), cerebrovascular disease, and chronic kidney disease were risk factors of severe/critical. Fully vaccination was a significant protective factor against severe infections (0.237 [0.071-0.793], P = .019). We found patients with more than two comorbidities were more likely to get serious outcomes. These findings demonstrated that in the elderly older than 60 years old, older age (aged over 80), cerebrovascular disease, and chronic kidney disease were risk factors for severe infection. Patients with more than two comorbidities were more likely to get serious outcomes. Fully vaccinated/booster patients were less likely to be severe and vaccinations could shorten viral shedding time. The limitation of lacking an overall spectrum of COVID-19 infections among elders could be compensated in other larger-scale studies in the future.

Safety and immunogenicity of a third-dose homologous BBIBP-CorV boosting vaccination: interim results from a prospective open-label study.

A COVID-19 booster vaccination is being comprehensively evaluated globally due to the emerging concern of reduced protection rate of previous vaccination and circulating Variants of Concern (VOC). But the safety and immunogenicity of homologous BBIBP-CorV boosting vaccination are yet to be thoroughly evaluated. We conducted this prospective, open-label study in Huashan Hospital using a third 6.5U BBIBP-CorV administered at an interval of 4-8 months following the previous two doses in healthy adults. Safety, anti-RBD response and neutralizing titers against SARS-CoV-2 and VOCs were examined. Sixty-three and forty participants entered the booster and the control group, respectively. A significant increase in IFN-γ SFU per million PBMCs was observed on day 14 against N peptide (20 vs. 5, P < 0.001). On day 14, pVNT GMTs increased over 15 folds of the baseline levels against prototype to reach 404.54 titers and over 9-13 folds against 4 VOCs and continuously increased by day 28. sVNT GMTs increased 112.51 and 127.45 folds by days 14 and 28 compared to the baseline level. Median anti-RBD antibody and IgG level significantly increased from 11.12 to 2607.50 BAU/ml and 4.07 to 619.20 BAU/ml on day 14. On day 14, females showed a significantly higher cell-mediated immune response against S1 peptide. The 7-8 months interval group had a higher humoral response than the 4-6 months interval group. No severe adverse event was reported. A third homologous BBIBP-CorV boosting vaccination was safe and highly immunogenic for healthy adults and broadened participants' immunity against VOCs.

The Negative Impact of COVID-19 on Life Insurers.

Understanding COVID-19 induced mortality risk is significant for life insurers to better analyze their financial sustainability after the outbreak of COVID-19. To capture the mortality effect caused by COVID-19 among all ages, this study proposes a temporary adverse mortality jump model to describe the dynamics of mortality in a post-COVID-19 pandemic world based on the weekly death numbers from 2015 to 2021 in the United States. As a comparative study, the Lee-Carter model is used as the base case to represent the dynamics of mortality without COVID-19. Then we compare the force of mortality, the survival probability and the liability of a life insurer by considering COVID-19 and those without COVID-19. We show that a life insurer's financial sustainability will deteriorate because of the higher mortality rates than expected in the wake of COVID-19. Our results remain unchanged when we also consider the effect of interest rate risk by adopting the Vasicek and CIR models.

Tocilizumab in the treatment of coronavirus disease 2019 pneumonia: real-world data from a case series.

Aim: Coronavirus disease 2019 is a life-threatening disease and how to improve survival of the patients is of great importance. Objective: To determine whether tocilizumab (TCZ) shows favorable results in coronavirus disease 2019 patients. Materials & methods: A retrospective study of four patients who received TCZ was conducted from 19 February to 31 March 2020 at Leishenshan Hospital, Wuhan, China. Clinical data of patients were compared before and after the administration of the agent. Results: There was not much difference in the clinical feature improvements and computed tomography images after TCZ administration in two mild patients. The other two severe patients died of disseminated intravascular coagulation and acute respiratory distress syndrome, respectively. Conclusion: Administration of TCZ was not shown a favorable outcome in this preliminary uncontrolled case series.

Combined chest CT and IL-6 detection for the initial diagnosis of patients with COVID-19

Objective To explore the feasibility of evaluation of patients with COVID-19 using combined chest CT presentations and interleukin-6(IL-6) levels for classification after initial diagnosis. Methods A retrospective analysis of medical records of 59 confirmed cases of COVID-19(moderate and severe) was conducted using the semi-quantitative scoring of chest CT presentation and the blood IL-6 count.The Spearman correlation was used to compare the association between the IL-6 counts and the CT scores in the moderate group with IL abnormality and in the severity group.By evaluating IL-6 count, CT scores and combined IL-6 count + CT scores, the area under curve(AUC) and the 95% confidence interval of the receiver operator characteristic(ROC) curve and logistic regression analysis were computed to predict the probability of the severe COVID-19 and to calculate the sensitivity and specificity. Results Among moderate patients, 9 showed normal IL-6 counts while 20 with abnormal values.The range of the IL-6 counts was 7.6-37.1 pg/ml with a mean of (20.07±9.79)pg/ml.The chest CT images were characterized by the domination of glass shadow of the lungs with or without consolidation.The CT scores were from 5 to 12 points with a mean of(8.85±1.71)points.For severe patients,30 demonstrated abnormal IL-6 counts.The range was(38.33-100.3)pg/ml and the mean was 58.53 pg/ml.From chest CT images,multiple presentations of both lungs could be seen.The range of CT scores was from 8 to 16 points with a mean of(13.00±2.61)points.The IL-6 counts [58.53(38.33-100.3)pg/ml]and CT scores[(13.00±2.61)points]of the severe patients were both significantly higher than that of the moderate patients.Within the group of severe patients,the IL-6 counts were positively correlated with the CT scores(r=0.658,P<0.05;r=0.397,P<0.05),whereas no correlation was found in the group of moderate patients.The results of ROC curve showed that the best cut-off values of IL-6 count and CT score were 33.9 pg/ml and 11 points,respectively,in the diagnosis for severe patients using the combination of the two measures.The sensitivity was 96.70% and the specificity was 89.70%,both of which were better than those when using IL-6 count or CT score alone. Conclusions The chest CT of moderate and severe COVID-19 patients after initial diagnosis exhibited distinct imaging features.Combining chest CT presentations and IL-6 levels is helpful for the classification of COVID-19 patients after initial diagnosis.

Myoglobin and C-reactive protein are efficient and reliable early predictors of COVID-19 associated mortality.

Since the emergence of SARS-CoV-2, numerous studies have been attempting to determine biomarkers, which could rapidly and efficiently predict COVID-19 severity, however there is lack of consensus on a specific one. This retrospective cohort study is a comprehensive analysis of the initial symptoms, comorbidities and laboratory evaluation of patients, diagnosed with COVID-19 in Huoshenshan Hospital, Wuhan, from 4th February to 12th March, 2020. Based on the data collected from 63 severely ill patients from the onset of symptoms till the full recovery or demise, we found not only age (average 70) but also blood indicators as significant risk factors associated with multiple organ failure. The blood indices of all patients showed hepatic, renal, cardiac and hematopoietic dysfunction with imbalanced coagulatory biomarkers. We noticed that the levels of LDH (85%, P < .001), HBDH (76%, P < .001) and CRP (65%, P < .001) were significantly elevated in deceased patients, indicating hepatic impairment. Similarly, increased CK (15%, P = .002), Cre (37%, P = 0.102) and CysC (74%, P = 0.384) indicated renal damage. Cardiac injury was obvious from the significantly elevated level of Myoglobin (52%, P < .01), Troponin-I (65%, P = 0.273) and BNP (50%, P = .787). SARS-CoV-2 disturbs the hemolymphatic system as WBC# (73%, P = .002) and NEUT# (78%, P < .001) were significantly elevated in deceased patients. Likewise, the level of D-dimer (80%, P < .171), PT (87%, P = .031) and TT (57%, P = .053) was elevated, indicating coagulatory imbalances. We identified myoglobin and CRP as specific risk factors related to mortality and highly correlated to organ failure in COVID-19 disease.

Prognostic analysis of neutralizing antibody levels in patients with COVID-19 (preprint)

Background: In the high incidence period of COVID-19, it is very important to quickly classify and evaluate the prognosis of patients through limited clinical antibody data. Methods Chemiluminescence immunoassay was used to detect serum IgM and IgG concentrations in 1951 patients diagnosed with COVID-19, and R language was used to analyze the influence of factors such as antibody, age, gender and concomitant diseases on the prognosis of SARS-CoV-2 patients. Results The results showed that the incidence of COVID-19 was consistent with the characteristics of the elderly, and patients with hypertension, diabetes, stroke, hypoalbuminemia and anemia were at increased risk of critical illness ( p  

The features comparison between patients in the ICU and general wards and between patients with different outcomes: a 2020 COVID-19 study.

BACKGROUND: The novel 2019 coronavirus (COVID-19) has largely abated in China; however, sporadic or imported cases are still a concern, while in other countries, the COVID-19 pandemic persists as a major health crisis. METHODS: All patients enrolled in this study were diagnosed with COVID-19 from February 21, 2020 to April 14, 2020 in Wuhan. We retrospectively analyzed the patients admitted to the ICU (137 patients) and general wards (114 patients) of Wuhan Leishenshan Hospital in China. The population characteristics, symptoms, and laboratory examination results between the patients in the ICU and those in the general wards were compared. Furthermore, the differences between the deceased patients in the ICU and those discharged from the ICU were compared. RESULTS: There were significant differences between the two groups in terms of symptoms, including fever, shortness of breath, no presence of complications, presence of 1 complication, and presence of 3 or more complications (P<0.05). There were also significant differences between the patients in terms of the laboratory examination results including elevated urea nitrogen, creatinine, direct bilirubin, aspartate aminotransferase, total protein, albumin, creatine kinase, lactate dehydrogenase, procalcitonin, erythrocyte sedimentation rate, white blood cells, C-reactive protein, prothrombin time, activated partial thromboplastin time, fibrinogen, D-dimer, interleukin 6, interleukin 8, interleukin 10, interleukin 2 receptor, tumor necrosis factor-α, troponin I, phosphokinase isoenzyme-MB, and B-type natriuretic peptide; and decreased platelets, lymphocyte absolute value, and eosinophil absolute value (<0.05). There were 45 patients who died in ICU and 57 improved and discharged patients. There were significant differences between the two groups in the number of patients that had 1 complication and 3 or more complications (P<0.05). There were also significant differences in the laboratory examination results between the patients including elevated urea nitrogen, total bilirubin, direct bilirubin, aspartate aminotransferase, procalcitonin, white blood cells, interleukin 8, interleukin 10, phosphokinase isoenzyme-MB, and B-type natriuretic peptide; and decreased platelets and eosinophil absolute value (P<0.05). CONCLUSIONS: Our findings highlight that the identified determinants may help to improve treatment of COVID-19 patients, to predict the risk of developing severe illness and to optimizing arrangement of health resources.

Thresholds of Glycemia and the Outcomes of COVID-19 Complicated With Diabetes: A Retrospective Exploratory Study Using Continuous Glucose Monitoring.

OBJECTIVE: Although elevated glucose levels are reported to be associated with adverse outcomes of coronavirus disease 2019 (COVID-19), the optimal range of glucose in patients with COVID-19 and diabetes remains unknown. This study aimed to investigate the threshold of glycemia and its association with the outcomes of COVID-19. RESEARCH DESIGN AND METHODS: Glucose levels were assessed through intermittently scanned continuous glucose monitoring in 35 patients for an average period of 10.2 days. The percentages of time above range (TAR), time below range (TBR), time in range (TIR), and coefficient of variation (CV) were calculated. Composite adverse outcomes were defined as either the need for admission to the intensive care unit, need for mechanical ventilation, or morbidity with critical illness. RESULTS: TARs using thresholds from 160 to 200 mg/dL were significantly associated with composite adverse outcomes after adjustment of covariates. Both TBR (<70 mg/dL) and TIR (70-160 mg/dL), but not mean sensor glucose level, were significantly associated with composite adverse outcomes and prolonged hospitalization. The multivariate-adjusted odds ratios of the CV of sensor glucose across tertiles for composite adverse outcomes of COVID-19 were 1.00, 1.18, and 25.2, respectively. CONCLUSIONS: Patients with diabetes and COVID-19 have an increased risk of adverse outcomes with glucose levels >160 mg/dL and <70 mg/dL and a high CV. Therapies that improve these metrics of glycemic control may result in better prognoses for these patients.

Causal Relationship Between the Spread of the COVID-19 and Geopolitical Risks in Emerging Economies.

This study investigates the causality between the spread of the COVID-19 pandemic (measured by new cases per million and new deaths per million) and geopolitical risks (measured by the index of geopolitical risks). We use the balanced panel data framework in 18 emerging economies from January 2020 to August 2020. We run the initial tests of cross-sectional dependence and the panel unit root tests with capturing cross-sectional dependence. Then, we utilize the panel Granger non-causality tests for heterogeneous stationary panel datasets. According to the findings, there is a significant causality from both measures of spreading the COVID-19 pandemic to geopolitical risks. Further tests are performed, and potential implications are also discussed.

Detectable Serum Severe Acute Respiratory Syndrome Coronavirus 2 Viral Load (RNAemia) Is Closely Correlated With Drastically Elevated Interleukin 6 Level in Critically Ill Patients With Coronavirus Disease 2019.

BACKGROUND: Although the detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) viral load in respiratory specimens has been widely used to diagnose coronavirus disease 2019 (COVID-19), it is undeniable that serum SARS-CoV-2 nucleic acid (RNAemia) could be detected in a fraction of COVID-19 patients. However, it is not clear whether testing for RNAemia is correlated with the occurrence of cytokine storms or with the specific class of patients. METHODS: This study enrolled 48 patients with COVID-19 admitted to the General Hospital of Central Theater Command, People's Liberation Army, a designated hospital in Wuhan, China. The patients were divided into 3 groups according to the Diagnosis and Treatment of New Coronavirus Pneumonia (sixth edition) guidelines issued by the National Health Commission of China. Clinical and laboratory data were collected, and the serum viral load and interleukin 6 (IL-6) level were determined. RESULTS: Analysis of clinical characteristics of 48 cases of COVID-19 showed that RNAemia was diagnosed only in the critically ill group and seemed to reflect the severity of the disease. Furthermore, the level of the inflammatory cytokine IL-6 in critically ill patients increased significantly, almost 10 times that in other patients. More importantly, the extremely high IL-6 level was closely correlated with the detection of RNAemia (R = 0.902). CONCLUSIONS: Detectable serum SARS-CoV-2 RNA (RNAemia) in patients with COVID-19 was associated with elevated IL-6 concentration and poor prognosis. Because elevated IL-6 may be part of a larger cytokine storm that could worsen outcome, IL-6 could be a potential therapeutic target for critically ill patients with an excessive inflammatory response.