Identifying immune signatures of common exposures through co-occurrence of T-cell receptors in tens of thousands of donors (preprint)

Memory T cells are records of clonal expansion from prior immune exposures, such as infections, vaccines and chronic diseases like cancer. A subset of the receptors of these expanded T cells in a typical immune repertoire are highly public, i.e., present in many individuals exposed to the same exposure. For the most part, the exposures associated with these public T cells are unknown. To identify public T-cell receptor signatures of immune exposures, we mined the immunosequencing repertoires of tens of thousands of donors to define clusters of co-occurring T cells. We first built co-occurrence clusters of T cells responding to antigens presented by the same Human Leukocyte Antigen (HLA) and then combined those clusters across HLAs. Each cross-HLA cluster putatively represents the public T-cell signature of a single prevalent exposure. Using repertoires from donors with known serological status for 7 prevalent exposures (HSV-1, HSV-2, EBV, Parvovirus, Toxoplasma gondii, Cytomegalovirus and SARS CoV-2), we identified a single T-cell cluster strongly associated with each exposure and used it to construct a highly sensitive and specific diagnostic model for the exposure. These T-cell clusters constitute the public immune responses to prevalent exposures, 7 known and many others unknown. By learning the exposure associations for more T cell clusters, this approach could be used to derive a ledger of a person's past and present immune exposures.

In Silico Identification of Anti-SARS-CoV-2 Medicinal Plants Using Cheminformatics and Machine Learning.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative pathogen of COVID-19, is spreading rapidly and has caused hundreds of millions of infections and millions of deaths worldwide. Due to the lack of specific vaccines and effective treatments for COVID-19, there is an urgent need to identify effective drugs. Traditional Chinese medicine (TCM) is a valuable resource for identifying novel anti-SARS-CoV-2 drugs based on the important contribution of TCM and its potential benefits in COVID-19 treatment. Herein, we aimed to discover novel anti-SARS-CoV-2 compounds and medicinal plants from TCM by establishing a prediction method of anti-SARS-CoV-2 activity using machine learning methods. We first constructed a benchmark dataset from anti-SARS-CoV-2 bioactivity data collected from the ChEMBL database. Then, we established random forest (RF) and support vector machine (SVM) models that both achieved satisfactory predictive performance with AUC values of 0.90. By using this method, a total of 1011 active anti-SARS-CoV-2 compounds were predicted from the TCMSP database. Among these compounds, six compounds with highly potent activity were confirmed in the anti-SARS-CoV-2 experiments. The molecular fingerprint similarity analysis revealed that only 24 of the 1011 compounds have high similarity to the FDA-approved antiviral drugs, indicating that most of the compounds were structurally novel. Based on the predicted anti-SARS-CoV-2 compounds, we identified 74 anti-SARS-CoV-2 medicinal plants through enrichment analysis. The 74 plants are widely distributed in 68 genera and 43 families, 14 of which belong to antipyretic detoxicate plants. In summary, this study provided several medicinal plants with potential anti-SARS-CoV-2 activity, which offer an attractive starting point and a broader scope to mine for potentially novel anti-SARS-CoV-2 drugs.

Effectiveness of inactivated COVID-19 vaccines against mild disease, pneumonia, and severe disease among persons infected with SARS-CoV-2 Omicron variant: Real-world study in Jilin Province, China.

BACKGROUND: : It is critical to determine the real-world performance of vaccines against coronavirus disease 2019 (COVID-19) so that appropriate treatments and policies can be implemented. There was a rapid wave of infections by the Omicron variant in Jilin Province (China) during spring 2022. We examined the effectiveness of inactivated vaccines against Omicron using real-world data from this epidemic. METHODS: . This retrospective case-case study of vaccine effectiveness (VE) examined infected patients who were quarantined and treated from April 16 to June 8, 2022 and responded to an electronic questionnaire. Data were analyzed by univariable and multivariable analyses. RESULTS: . A total of 2968 cases with SARS-CoV-2 infections (asymptomatic: 1029, mild disease: 1858, pneumonia: 108, severe disease: 21) were enrolled in the study. Multivariable regression indicated that the risk for pneumonia or severe disease was greater in those who were older or had underlying diseases, but was less in those who received COVID-19 vaccines. Relative to no vaccination, VE against the composite of pneumonia and severe disease was significant for those who received 2 doses (60.1%, 95%CI: 40.0%, 73.5%) or 3 doses (68.1%, 95%CI: 44.6%, 81.7%), and VE was similar in the subgroups of males and females. However, VE against the composite of all three classes of symptomatic diseases was not significant overall, nor after stratification by sex. There was no statistical difference in the VE of vaccines from different manufacturers. CONCLUSION: . The inactivated COVID-19 vaccines protected patients against pneumonia and severe disease from Omicron infection, and booster vaccination enhanced this effect.

Antisense oligonucleotides to therapeutically target SARS-CoV-2 infection.

Although the COVID-19 pandemic began over three years ago, the virus responsible for the disease, SARS-CoV-2, continues to infect people across the globe. As such, there remains a critical need for development of novel therapeutics against SARS-CoV-2. One technology that has remained relatively unexplored in COVID-19 is the use of antisense oligonucleotides (ASOs)-short single-stranded nucleic acids that bind to target RNA transcripts to modulate their expression. In this study, ASOs targeted against the SARS-CoV-2 genome and host entry factors, ACE2 and TMPRSS2, were designed and tested for their ability to inhibit cellular infection by SARS-CoV-2. Using our previously developed SARS-CoV-2 bioassay platform, we screened 180 total ASOs targeting various regions of the SARS-CoV-2 genome and validated several ASOs that potently blocked SARS-CoV-2 infection in vitro. Notably, select ASOs retained activity against both the WA1 and B.1.1.7 (commonly known as alpha) variants. Screening of ACE2 and TMPRSS2 ASOs showed that targeting of ACE2 also potently prevented infection by the WA1 and B.1.1.7 SARS-CoV-2 viruses in the tested cell lines. Combined with the demonstrated success of ASOs in other disease indications, these results support further research into the development of ASOs targeting SARS-CoV-2 and host entry factors as potential COVID-19 therapeutics.

Association of nirmatrelvir/ritonavir treatment on upper respiratory SARS-CoV-2 RT-PCR negative conversion rates among high-risk patients with COVID-19.

BACKGROUND: Acceleration of negative respiratory conversion of SARS-CoV-2 in patients with coronavirus disease 2019 (COVID-19) might reduce viral transmission. Nirmatrelvir/ritonavir is a new antiviral agent recently approved for treatment of COVID-19 that has the potential to facilitate negative conversion. METHODS: A cohort of hospitalized adult patients with mild-to-moderate COVID-19 who had a high-risk for progression to severe disease were studied. These patients presented with COVID-19 symptoms between March 5 and April 5, 2022. The time from positive to negative upper respiratory RT-PCR conversion was assessed by Kaplan-Meier plots and Cox proportional hazards regression with the adjustment for patients baseline demographic and clinical characteristics. RESULTS: There were 258 patients treated with nirmatrelvir/ritonavir and 224 non-treated patients who had mild-to-moderate COVID-19. The median (interquartile range) time for patients who converted from positive to negative RT-PCR was 10 days (7-12 days) in patients treated ≤5 days after symptom onset and 17 days (12-21 days) in non-treated patients, respectively. The proportions of patients with a negative conversion at day 15 were 89.7% and 42.0% in treated patients and non-treated patients, corresponding to a hazard ratio of 4.33 (95% CI, 3.31-5.65). Adjustment for baseline differences between the groups had little effect on the association. Subgroup analysis on treated patients suggests that time to negative conversion did not vary with the patients' baseline characteristics. CONCLUSION: This cohort study of high-risk patients with mild-to-moderate COVID-19 found an association between nirmatrelvir/ritonavir treatment and accelerated negative RT-PCR respiratory SARS-CoV-2 conversion that might reduce the risk of viral shedding and disease transmission.

Chinese parents' willingness to vaccinate their children against COVID-19: A systematic review and meta-analysis.

Introduction: To evaluate Chinese parents' willingness to vaccinate their children against COVID-19, identify its predictors, and provide a reference for raising the COVID-19 vaccination rate for children. Method: PubMed, Cochrane Library, Embase, and the databases in Chinese, including CNKI, WanFang, VIP, CBM, were searched from December 2019 to June 2022, and citation tracking was used to identify relevant studies. To calculate the rate with 95% confidence intervals (CI), a random-effects model was used. To explore sources of heterogeneity, sensitivity analysis and subgroup analysis were conducted. This analysis was registered on PROSPERO (CRD42022346866) and reported in compliance with the PRISMA guidelines. Result: Overall, 80 studies were screened, and 13 studies with 47994 parents were included after removing duplicates and excluding 19 studies that did not meet the selection criteria by title, abstract and full-text screening. The pooled willingness rate of Chinese parents to vaccinate their children against COVID-19 was 70.0% (95% CI: 62.0~78.0%). Level of education, perceived susceptibility of children infected with COVID-19, and parental attitudes toward vaccination (such as perceived efficacy and safety of the COVID-19 vaccines, parental willingness to vaccinate themselves, parental vaccination hesitancy, and the history of children's vaccination against influenza) were the main predictors of parents' intention to vaccinate their children. Discussion: Chinese parents' willingness to vaccinate their children against COVID-19 is moderate, and factors including parental education level, perceived susceptibility of children infected with COVID-19, and parental attitudes toward vaccination affect this decision. Fully identifying these factors and their mechanism will be essential to further raise the willingness rate. Systematic review registration: https://www.crd.york.ac.uk/PROSPERO/, identifier: CRD42022346866.

Detection of Aircraft Emissions Using Long-Path Differential Optical Absorption Spectroscopy at Hefei Xinqiao International Airport

Airport emissions have received increased attention because of their impact on atmospheric chemical processes, the microphysical properties of aerosols, and human health. At present, the assessment methods for airport pollution emission mainly involve the use of the aircraft emission database established by the International Civil Aviation Organization, but the emission behavior of an engine installed on an aircraft may differ from that of an engine operated in a testbed. In this study, we describe the development of a long-path differential optical absorption spectroscopy (LP-DOAS) instrument for measuring aircraft emissions at an airport. From 15 October to 23 October 2019, a measurement campaign using the LP-DOAS instrument was conducted at Hefei Xinqiao International Airport to investigate the regional concentrations of various trace gases in the airport’s northern area and the variation characteristics of the gas concentrations during an aircraft’s taxiing and take-off phases. The measured light path of the LP-DOAS passed through the aircraft taxiway and the take-off runway concurrently. The aircraft’s take-off produced the maximum peak in NO2 average concentrations of approximately 25 ppbV and SO2 average concentrations of approximately 8 ppbV in measured area. Owing to the airport’s open space, the pollution concentrations decreased rapidly, the overall levels of NO2 and SO2 concentrations in the airport area were very low, and the maximum hourly average NO2 and SO2 concentrations during the observation period were better than the Class 1 ambient air quality standards in China. Additionally, we discovered that the NO2 and SO2 emissions from the Boeing 737–800 aircraft monitored in this experiment were weakly and positively related to the age of the aircraft. This measurement established the security, feasibility, fast and non-contact of the developed LP-DOAS instrument for monitoring airport regional concentrations as well as NO2 and SO2 aircraft emissions during routine airport operations without interfering with the normal operation of the airport.

Validated tool for early prediction of intensive care unit admission in COVID-19 patients.

BACKGROUND: The novel coronavirus disease 2019 (COVID-19) pandemic is a global threat caused by the severe acute respiratory syndrome coronavirus-2. AIM: To develop and validate a risk stratification tool for the early prediction of intensive care unit (ICU) admission among COVID-19 patients at hospital admission. METHODS: The training cohort included COVID-19 patients admitted to the Wuhan Third Hospital. We selected 13 of 65 baseline laboratory results to assess ICU admission risk, which were used to develop a risk prediction model with the random forest (RF) algorithm. A nomogram for the logistic regression model was built based on six selected variables. The predicted models were carefully calibrated, and the predictive performance was evaluated and compared with two previously published models. RESULTS: There were 681 and 296 patients in the training and validation cohorts, respectively. The patients in the training cohort were older than those in the validation cohort (median age: 63.0 vs 49.0 years, P < 0.001), and the percentages of male gender were similar (49.6% vs 49.3%, P = 0.958). The top predictors selected in the RF model were neutrophil-to-lymphocyte ratio, age, lactate dehydrogenase, C-reactive protein, creatinine, D-dimer, albumin, procalcitonin, glucose, platelet, total bilirubin, lactate and creatine kinase. The accuracy, sensitivity and specificity for the RF model were 91%, 88% and 93%, respectively, higher than those for the logistic regression model. The area under the receiver operating characteristic curve of our model was much better than those of two other published methods (0.90 vs 0.82 and 0.75). Model A underestimated risk of ICU admission in patients with a predicted risk less than 30%, whereas the RF risk score demonstrated excellent ability to categorize patients into different risk strata. Our predictive model provided a larger standardized net benefit across the major high-risk range compared with model A. CONCLUSION: Our model can identify ICU admission risk in COVID-19 patients at admission, who can then receive prompt care, thus improving medical resource allocation.

Nomogram for prediction of fatal outcome in patients with severe COVID-19: a multicenter study.

BACKGROUND: To develop an effective model of predicting fatal outcomes in the severe coronavirus disease 2019 (COVID-19) patients. METHODS: Between February 20, 2020 and April 4, 2020, consecutive confirmed 2541 COVID-19 patients from three designated hospitals were enrolled in this study. All patients received chest computed tomography (CT) and serological examinations at admission. Laboratory tests included routine blood tests, liver function, renal function, coagulation profile, C-reactive protein (CRP), procalcitonin (PCT), interleukin-6 (IL-6), and arterial blood gas. The SaO2 was measured using pulse oxygen saturation in room air at resting status. Independent high-risk factors associated with death were analyzed using Cox proportional hazard model. A prognostic nomogram was constructed to predict the survival of severe COVID-19 patients. RESULTS: There were 124 severe patients in the training cohort, and there were 71 and 76 severe patients in the two independent validation cohorts, respectively. Multivariate Cox analysis indicated that age ≥ 70 years (HR = 1.184, 95% CI 1.061-1.321), panting (breathing rate ≥ 30/min) (HR = 3.300, 95% CI 2.509-6.286), lymphocyte count < 1.0 × 109/L (HR = 2.283, 95% CI 1.779-3.267), and interleukin-6 (IL-6) >  10 pg/ml (HR = 3.029, 95% CI 1.567-7.116) were independent high-risk factors associated with fatal outcome. We developed the nomogram for identifying survival of severe COVID-19 patients in the training cohort (AUC = 0.900, 95% CI 0.841-0.960, sensitivity 95.5%, specificity 77.5%); in validation cohort 1 (AUC = 0.811, 95% CI 0.763-0.961, sensitivity 77.3%, specificity 73.5%); in validation cohort 2 (AUC = 0.862, 95% CI 0.698-0.924, sensitivity 92.9%, specificity 64.5%). The calibration curve for probability of death indicated a good consistence between prediction by the nomogram and the actual observation. The prognosis of severe COVID-19 patients with high levels of IL-6 receiving tocilizumab were better than that of those patients without tocilizumab both in the training and validation cohorts, but without difference (P = 0.105 for training cohort, P = 0.133 for validation cohort 1, and P = 0.210 for validation cohort 2). CONCLUSIONS: This nomogram could help clinicians to identify severe patients who have high risk of death, and to develop more appropriate treatment strategies to reduce the mortality of severe patients. Tocilizumab may improve the prognosis of severe COVID-19 patients with high levels of IL-6.

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.

Sustainability of SARS-CoV-2 Induced Humoral Immune Responses in COVID-19 Patients from Hospitalization to Convalescence Over Six Months.

Understanding the persistence of antibody in convalescent COVID-19 patients may help to answer the current major concerns such as the risk of reinfection, the protection period of vaccination and the possibility of building an active herd immunity. This retrospective cohort study included 172 COVID-19 patients who were hospitalized in Wuhan. A total of 404 serum samples were obtained over six months from hospitalization to convalescence. Antibodies in the specimens were quantitatively analyzed by the capture chemiluminescence immunoassays (CLIA). All patients were positive for the anti-SARS-CoV-2 IgM/IgG at the onset of COVID-19 symptoms, and the IgG antibody persisted in all the patients during the convalescence. However, only approximately 25% of patients can detect the IgM antibodies, IgM against N protein (N-IgM) and receptor binding domain of S protein (RBD-IgM) at the 27th week. The titers of IgM, N-IgM and RBD-IgM reduced to 16.7%, 17.6% and 15.2% of their peak values respectively. In contrast, the titers of IgG, N-IgG and RBD-IgG peaked at 4-5th week and reduced to 85.9%, 62.6% and 87.2% of their peak values respectively at the end of observation. Dynamic behavior of antibodies and their correlation in age, gender and severity groups were investigated. In general, the COVID-19 antibody was sustained at high levels for over six months in most of the convalescent patients. Only a few patients with antibody reducing to an undetectable level which needs further attention. The humoral immune response against SARS-CoV-2 infection in COVID-19 patients exhibits a typical dynamic of acquired immunity.

Virus load and virus shedding of SARS-CoV-2 and their impact on patient outcomes.

BACKGROUND: Understanding a virus shedding patterns in body fluids/secretions is important to determine the samples to be used for diagnosis and to formulate infection control measures. AIM: To investigate the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) shedding patterns and its risk factors. METHODS: All laboratory-confirmed coronavirus disease 2019 patients with complete medical records admitted to the Shenzhen Third People's Hospital from January 28, 2020 to March 8, 2020 were included. Among 145 patients (54.5% males; median age, 46.1 years), three (2.1%) died. The bronco-alveolar lavage fluid (BALF) had the highest virus load compared with the other samples. The viral load peaked at admission (3.3 × 108 copies) and sharply decreased 10 d after admission. RESULTS: The viral load was associated with prolonged intensive care unit (ICU) duration. Patients in the ICU had significantly longer shedding time compared to those in the wards (P < 0.0001). Age > 60 years [hazard ratio (HR) = 0.6; 95% confidence interval (CI): 0.4-0.9] was an independent risk factor for SARS-CoV-2 shedding, while chloroquine (HR = 22.8; 95%CI: 2.3-224.6) was a protective factor. CONCLUSION: BALF had the highest SARS-CoV-2 load. Elderly patients had higher virus loads, which was associated with a prolonged ICU stay. Chloroquine was associated with shorter shedding duration and increased the chance of viral negativity.

Treatment of COVID-19 patients with hydroxychloroquine or chloroquine: A retrospective analysis (preprint)

Background There is an urgent need for an effective treatment to cure patients with COVID-19 and reduce the duration of viral shedding. Methods We conducted a retrospective study using data from the electronic medical records of patients with confirmed SARS-CoV-2 infection who were hospitalized in the E1-4 intensive care center of Guanggu Hospital, Wuhan City, Hubei Province, China, from February 11, 2020, to March 23, 2020. According to the diagnostic results, the hospitalized patients were divided into the experimental group treated with hydroxychloroquine (HCQ) or chloroquine (CQ) and the control group only treated with conventional therapy without HCQ or CQ. The main outcome was the clearance rate of SARS-CoV-2. Results A total of 37 patients were evaluated. Eighteen patients were assigned to the HCQ or CQ group, and 19 were assigned to the routine treatment group. Treatment with HCQ or CQ was not associated with a difference from routine treatment in the viral shedding duration (median, 14 days vs. 10 days; hazard ratio for viral shedding, 0.393; 95% confidence interval [CI], 0.151 to 1.022; P=0.056). No significant difference in the viral shedding rate was observed between the groups at any time point (7 days, 14 days, 21 days, 28 days and the end point). Conclusion Although this is a retrospective analysis, the results suggest that treatment with HCQ or CQ had no impact on the duration of viral shedding. 

Triboelectrification induced self-powered microbial disinfection using nanowire-enhanced localized electric field (preprint)

Air-transmitted pathogens may lead to severe epidemics (e.g., COVID-19) showing huge threats to public health. Inactivation of the pathogenic microbes in the air is an essential process, whereas the feasibility of existing air disinfection technologies has encountered obstacles including only achieving physical separation but no inactivation, obvious pressure drops, and energy intensiveness. Here we report a rapid disinfection method for inactivating air-transmitted bacteria and viruses using the nanowire-enhanced localized electric field to damage the outer structures of microbes. This air disinfection system is driven by a triboelectric nanogenerator that converts mechanical vibration to electricity effectively and achieves self-powered. Assisted by a rational design for the accelerated charging and trapping of microbes, this self-powered air disinfection system promotes the microbial transport and achieves high performance: >99.99% microbial inactivation within 0.025s in a fast airflow (2 m/s) while only causing low pressure drops (<24 Pa). This rapid, self-powered air disinfection method may fill the urgent need for the air-transmitted microbial inactivation to protect public health.

Cardiac injury prediction and lymphocyte immunity and inflammation analysis in hospitalized patients with coronavirus disease 2019 (COVID-19).

BACKGROUND: Coronavirus disease 2019 (COVID-19) is an ongoing global pandemic. The ability to predict cardiac injury and analyze lymphocyte immunity and inflammation of cardiac damage in patients with COVID-19 is limited. We aimed to determine the risk factors and predictive markers of cardiac injury in these patients. METHODS: Data from 124 consecutive hospitalized patients with confirmed COVID-19 were collected. We compared the proportion of cardiovascular disease history in moderate, severe, and critical cases. We obtained high-sensitivity cardiac troponin I (hs-cTn I) results from 68 patients. Patients were divided into two groups based on positive hs-cTn I result: those with cardiac injury (n = 19) and those without cardiac injury (n = 49). RESULTS: Compared with the group with moderate disease, hypertension, coronary heart disease, and smoking were more common in severe and critical cases. Diabetes mellitus was most common in the critical group. Age older than 65 years, presence of chronic kidney disease, and lower blood lymphocyte percentage were independent risk factors of cardiac injury. The total T- and B-lymphocyte counts and CD4+ and CD8+ T-cell counts were significantly lower in those with cardiac injury. A minimal lymphocyte percentage < 7.8% may predict cardiac injury. The interleukin (IL) 6 level in plasma was elevated in the group with cardiac injury. CONCLUSIONS: The lymphocyte percentage in blood may become a predictive marker of cardiac injury in COVID-19 patients. The total T and B cells and CD4+ and CD8+ cell counts decreased and the IL-6 level increased in COVID-19 patients with cardiac injury.

Cardiac Injury and Clinical Course of Patients With Coronavirus Disease 2019.

Background: Cardiac injury is recognized as one of the most common critical complications during exacerbation of coronavirus disease 2019 (COVID-19). This study aimed to investigate the effect of cardiac injury on the clinical course of COVID-19 and to examine its potential mechanism and treatments. Methods and Results: A total of 222 hospitalized patients with COVID-19 from Wuhan were selected for the study during February 10 to March 28, 2020. Demographic, laboratory, and clinical data on admission and during hospitalization were compared between patients with COVID-19 with or without cardiac injury. On admission, cardiac injury (n = 29) was associated with advanced age, more underlying coronary artery disease, and a lower Pao2. Troponin levels were correlated with inflammatory markers (C-reactive protein: r = 0.348, P < 0.001; interleukin 6: r = 0.558, P < 0.001) and d-dimer levels (r = 0.598, P < 0.001). During hospitalization, another six patients suffered from cardiac injury and cardiac injury (n = 35), resulting in higher rates of ventilation (invasive: 51.4 vs. 1.6%, P < 0.001; non-invasive: 31.4 vs. 1.1%, P < 0.001) and mortality (54.3 vs. 1.1%, P < 0.001). Cardiac injury on admission was a predictive factor for mortality (adjusted hazard ratio = 4.73, 95% confidence interval = 1.35-16.63, P = 0.015). Receiver operating characteristic curve analysis showed that, on admission, a troponin level of 36.35 pg/mL was predictive for mortality with a sensitivity of 73.7% and a specificity of 92.1%. Conclusions: Cardiac injury complicates the disease course and increases the mortality rate of COVID-19. Troponin levels should be checked at admission and during hospitalization for triage, better monitoring, and managing those with COVID-19, especially in the most severe patients. Condensed Abstract: Cardiac injury is not uncommon in COVID-19. In a cohort of 222 patients with COVID-19, cardiac injury was found in 29 patients on admission and in another 6 patients during hospitalization. The admission level of troponin was well-correlated with inflammatory factors and d-dimer levels and strongly predicted mortality. Cardiac injury is a manifestation secondary to hypoxia and systemic infection, but which nevertheless further complicates the disease course and increases the mortality rate. Troponin levels should be checked at admission and during hospitalization for triage, better monitoring, and managing those with COVID-19, especially in the most severe patients.

The prognostic value of the SOFA score in patients with COVID-19: a retrospective, observational study (preprint)

Background Patients with Coronavirus disease 2019 (COVID-19) have a high mortality rate, and thus, it is particularly important to predict the severity and prognosis of COVID-19. The Sequential Organ Failure Assessment (SOFA) score has been used to predict the clinical outcomes of patients with multiple organ failure requiring intensive care. Therefore, we retrospectively analyzed the clinical characteristics, risk factors, and relationship between the SOFA score and the prognosis of COVID-19 patients.Methods Clinical variables were compared between patients with mild and severe COVID-19. Univariate and multivariate logistic regression analyses were performed to identify the risk factors for severe COVID-19. The Cox proportional hazards model was used to analyze risk factors for hospital-related death. Survival analysis was performed by the Kaplan-Meier method, and survival differences were assessed by the log-rank test. Receiver operating characteristic (ROC) curves of the SOFA score in different situations were drawn, and the area under the ROC curve was calculated.Results The median SOFA score of all patients was 2 (IQR, 1–3). Patients with severe COVID-19 exhibited a significantly higher SOFA score than patients with mild COVID-19 [3 (IQR, 2–4) vs 1 (IQR, 0–1); P < 0.001]. The SOFA score increased the risk of severe COVID-19, with an odds ratio of 5.851 (95% CI: 3.044–11.245; P < 0.001). The area under the ROC curve (AUC) was used to evaluate the diagnostic accuracy of the SOFA score in predicting severe COVID-19 [cutoff value = 2; AUC = 0.908 (95% CI: 0.857–0.960); sensitivity: 85.20%; specificity: 80.40%] and the risk of death in COVID-19 patients [cutoff value = 5; AUC = 0.995 (95% CI: 0.985-1.000); sensitivity: 100.00%; specificity: 95.40%]. Regarding the 60-day mortality rates of patients in the two groups classified by the optimal cutoff value of the SOFA score (5), patients in the high SOFA score group (SOFA score ≥ 5) had a significantly greater risk of death than those in the low SOFA score group (SOFA score < 5).Conclusion The SOFA score could be used to evaluate the severity and 60-day mortality of COVID-19. The SOFA score may be an independent risk factor for in-hospital death.

The Prognostic Value of the SOFA Score in Patients with COVID-19: A Retrospective, Observational Study (preprint)

Background: Patients with Coronavirus disease 2019 (COVID-19) have a high mortality rate, and thus, it is particularly important to predict the severity and prognosis of COVID-19. The Sequential Organ Failure Assessment (SOFA) score has been used to predict the clinical outcomes of patients with multiple organ failure requiring intensive care. Therefore, we retrospectively analyzed the clinical characteristics, risk factors, and relationship between the SOFA score and the prognosis of COVID-19 patients.Methods: Clinical variables were compared between patients with mild and severe COVID-19. Univariate and multivariate logistic regression analyses were performed to identify the risk factors for severe COVID-19. The Cox proportional hazards model was used to analyze risk factors for hospital-related death. Survival analysis was performed by the Kaplan-Meier method, and survival differences were assessed by the log-rank test. Receiver operating characteristic (ROC) curves of the SOFA score in different situations were drawn, and the area under the ROC curve was calculated.Results: The median SOFA score of all patients was 2 (IQR, 1-3). Patients with severe COVID-19 exhibited a significantly higher SOFA score than patients with mild COVID-19 [3 (IQR, 2-4) vs 1 (IQR, 0-1); P<0.001]. The SOFA score increased the risk of severe COVID-19, with an odds ratio of 5.851 (95% CI: 3.044-11.245; P<0.001). The area under the ROC curve (AUC) was used to evaluate the diagnostic accuracy of the SOFA score in predicting severe COVID-19 [cutoff value = 2; AUC = 0.908 (95% CI: 0.857-0.960); sensitivity: 85.20%; specificity: 80.40%] and the risk of death in COVID-19 patients [cutoff value = 5; AUC = 0.995 (95% CI: 0.985-1.000); sensitivity: 100.00%; specificity: 95.40%]. Regarding the 60-day mortality rates of patients in the two groups classified by the optimal cutoff value of the SOFA score (5), patients in the high SOFA score group (SOFA score ≥5) had a significantly greater risk of death than those in the low SOFA score group (SOFA score <5).Conclusion: The SOFA score could be used to evaluate the severity and 60-day mortality of COVID-19. The SOFA score may be an independent risk factor for in-hospital death.