scholarly journals Diverse Functional Autoantibodies in Patients with COVID-19

2020 ◽  
Author(s):  
Eric Y. Wang ◽  
Tianyang Mao ◽  
Jon Klein ◽  
Yile Dai ◽  
John D. Huck ◽  
...  
Keyword(s):  
Disease Severity ◽  
Healthcare Workers ◽  
Immune Cell ◽  
Wide Spectrum ◽  
Severe Disease ◽  
Surface Proteins ◽  
Complement Components ◽  
Host Immune Responses ◽  
High Prevalence ◽  
The Impact

COVID-19 manifests with a wide spectrum of clinical phenotypes that are characterized by exaggerated and misdirected host immune responses1–8. While pathological innate immune activation is well documented in severe disease1, the impact of autoantibodies on disease progression is less defined. Here, we used a high-throughput autoantibody discovery technique called Rapid Extracellular Antigen Profiling (REAP) to screen a cohort of 194 SARS-CoV-2 infected COVID-19 patients and healthcare workers for autoantibodies against 2,770 extracellular and secreted proteins (the “exoproteome”). We found that COVID-19 patients exhibit dramatic increases in autoantibody reactivities compared to uninfected controls, with a high prevalence of autoantibodies against immunomodulatory proteins including cytokines, chemokines, complement components, and cell surface proteins. We established that these autoantibodies perturb immune function and impair virological control by inhibiting immunoreceptor signaling and by altering peripheral immune cell composition, and found that murine surrogates of these autoantibodies exacerbate disease severity in a mouse model of SARS-CoV-2 infection. Analysis of autoantibodies against tissue-associated antigens revealed associations with specific clinical characteristics and disease severity. In summary, these findings implicate a pathological role for exoproteome-directed autoantibodies in COVID-19 with diverse impacts on immune functionality and associations with clinical outcomes.

scholarly journals Neutrophil-to-Lymphocyte Ratio and Platelet-to-Lymphocyte Ratio and Their Role as Predictors of Disease Severity of Coronavirus Disease 2019 (COVID-19)

2021 ◽  
Author(s):  
Rohit Jain ◽  
Arun Gopal ◽  
Basant Kumar Pathak ◽  
Sourya Sourabh Mohakuda ◽  
TVSVGK Tilak ◽  
...  
Keyword(s):  
Disease Severity ◽  
Complete Blood Count ◽  
Wide Spectrum ◽  
Statistical Significance ◽  
Severe Disease ◽  
Neutrophil To Lymphocyte Ratio ◽  
Screening Tools ◽  
Platelet To Lymphocyte Ratio ◽  
Lymphocyte Ratio ◽  
Time Of Admission

Abstract Context Due to the wide spectrum of clinical illness in coronavirus disease 2019 (COVID-19) patients, it is important to stratify patients into severe and nonsevere categories. Neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR) have been evaluated rapidly by a few studies worldwide for its association with severe disease, but practically none have been conducted in the Indian population. This study was undertaken to examine the role of NLR and PLR in predicting severe disease in Indian patients. Objectives The objective was to study the association of NLR and PLR observed at the time of admission with maximum disease severity during hospitalization and to study their role in predicting disease severity. Material and Methods A total of 229 COVID-19 patients were admitted at the center during the study period. After applying inclusion and exclusion criteria, 191 patients were included in the study. The demographic, clinical, and laboratory (complete blood count, NLR, and PLR) data of all patients were obtained at the time of admission. Maximum disease severity of all patients was assessed during hospitalization. Statistical Analysis Chi-square and Mann–Whitney U tests were used to assess statistical significance. Receiver operating characteristic curve (ROC) was plotted for NLR and PLR to estimate the cutoff values and sensitivity and specificity using Youden’s index for predicting severe disease. Logistic regression analysis was used to estimate the odds ratios (OR) and 95% confidence intervals. Results Mean NLR and PLR were significantly higher in severe patients (NLR = 7.41; PLR = 204) compared with nonsevere patients (NLR = 3.30; PLR = 121). ROC analysis showed that NLR, in comparison to PLR, had a higher area under the curve (AUC) of 0.779, with a larger OR of 1.237 and cutoff of 4.1, and showed 69% sensitivity and 78% specificity in predicting severe disease. Cut off for PLR was 115.3, which showed 79% sensitivity and 62% specificity in predicting severe disease. Conclusion NLR and PLR, both showing acceptable AUCs, can be used as screening tools to predict disease severity. However, NLR was a better predictor of disease severity.

scholarly journals The interplay between environmental exposures and COVID-19 risks in the health of children

2021 ◽  
Vol 20 (1) ◽  
Author(s):  
Peter D. Sly ◽  
Brittany A. Trottier ◽  
Catherine M. Bulka ◽  
Stephania A. Cormier ◽  
Julius Fobil ◽  
...  
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Disease Severity ◽  
Research Effort ◽  
Severe Disease ◽  
Environmental Exposures ◽  
Research Strategy ◽  
Lessons Learned ◽  
Research Questions ◽  
The Impact

Abstract Background An unusual feature of SARS-Cov-2 infection and the COVID-19 pandemic is that children are less severely affected than adults. This is especially paradoxical given the epidemiological links between poor air quality and increased COVID-19 severity in adults and that children are generally more vulnerable than adults to the adverse consequences of air pollution. Objectives To identify gaps in knowledge about the factors that protect children from severe SARS-Cov-2 infection even in the face of air pollution, and to develop a transdisciplinary research strategy to address these gaps. Methods An international group of researchers interested in children’s environmental health was invited to identify knowledge gaps and to develop research questions to close these gaps. Discussion Key research questions identified include: what are the effects of SAR-Cov-2 infection during pregnancy on the developing fetus and child; what is the impact of age at infection and genetic susceptibility on disease severity; why do some children with COVID-19 infection develop toxic shock and Kawasaki-like symptoms; what are the impacts of toxic environmental exposures including poor air quality, chemical and metal exposures on innate immunity, especially in the respiratory epithelium; what is the possible role of a “dirty” environment in conveying protection – an example of the “hygiene hypothesis”; and what are the long term health effects of SARS-Cov-2 infection in early life. Conclusion A concerted research effort by a multidisciplinary team of scientists is needed to understand the links between environmental exposures, especially air pollution and COVID-19. We call for specific research funding to encourage basic and clinical research to understand if/why exposure to environmental factors is associated with more severe disease, why children appear to be protected, and how innate immune responses may be involved. Lessons learned about SARS-Cov-2 infection in our children will help us to understand and reduce disease severity in adults, the opposite of the usual scenario.

scholarly journals Pathophysiology of acute respiratory syndrome coronavirus 2 infection: a systematic literature review to inform EULAR points to consider

RMD Open ◽  
2021 ◽  
Vol 7 (1) ◽  
pp. e001549 ◽  
Author(s):  
Aurélie Najm ◽  
Alessia Alunno ◽  
Xavier Mariette ◽  
Benjamin Terrier ◽  
Gabriele De Marco ◽  
...  
Keyword(s):  
Literature Review ◽  
Systematic Literature Review ◽  
Immune Cell ◽  
Severe Disease ◽  
Cell Phenotype ◽  
Loss Of Function ◽  
Humoral And Cellular Immunity ◽  
Host Immune Responses ◽  
Disease Spectrum ◽  
And Function

BackgroundThe SARS-CoV-2 pandemic is a global health problem. Beside the specific pathogenic effect of SARS-CoV-2, incompletely understood deleterious and aberrant host immune responses play critical roles in severe disease. Our objective was to summarise the available information on the pathophysiology of COVID-19.MethodsTwo reviewers independently identified eligible studies according to the following PICO framework: P (population): patients with SARS-CoV-2 infection; I (intervention): any intervention/no intervention; C (comparator): any comparator; O (outcome) any clinical or serological outcome including but not limited to immune cell phenotype and function and serum cytokine concentration.ResultsOf the 55 496 records yielded, 84 articles were eligible for inclusion according to question-specific research criteria. Proinflammatory cytokine expression, including interleukin-6 (IL-6), was increased, especially in severe COVID-19, although not as high as other states with severe systemic inflammation. The myeloid and lymphoid compartments were differentially affected by SARS-CoV-2 infection depending on disease phenotype. Failure to maintain high interferon (IFN) levels was characteristic of severe forms of COVID-19 and could be related to loss-of-function mutations in the IFN pathway and/or the presence of anti-IFN antibodies. Antibody response to SARS-CoV-2 infection showed a high variability across individuals and disease spectrum. Multiparametric algorithms showed variable diagnostic performances in predicting survival, hospitalisation, disease progression or severity, and mortality.ConclusionsSARS-CoV-2 infection affects both humoral and cellular immunity depending on both disease severity and individual parameters. This systematic literature review informed the EULAR ‘points to consider’ on COVID-19 pathophysiology and immunomodulatory therapies.

The impact of multiple sclerosis severity on health state utility values: Evidence from Australia

2016 ◽  
Vol 23 (8) ◽  
pp. 1157-1166 ◽  
Author(s):  
Hasnat Ahmad ◽  
Bruce V Taylor ◽  
Ingrid van der Mei ◽  
Sam Colman ◽  
Beth A O’Leary ◽  
...  
Keyword(s):  
Multiple Sclerosis ◽  
Disease Severity ◽  
Severe Disease ◽  
Health Utility ◽  
Health State Utility ◽  
Health State ◽  
Utility Values ◽  
Health State Utility Values ◽  
Economic Analyses ◽  
The Impact

Background: The measurement of health state utility values (HSUVs) for a representative sample of Australian people with multiple sclerosis (MS) has not previously been performed. Objectives: Our main aim was to quantify the HSUVs for different levels of disease severities in Australian people with MS. Method: HSUVs were calculated by employing a ‘judgement-based’ method that essentially creates EQ-5D-3L profiles based on WHOQOL-100 responses and then applying utility weights to each level in each dimension. A stepwise linear regression was used to evaluate the relationship between HSUVs and disease severity, classified as mild (Expanded Disability Status Scale (EDSS) levels: 0–3.5), moderate (EDSS levels: 4–6) and severe (EDSS levels: 6.5–9.5). Results: Mean HSUV for all people with MS was 0.53 (95% confidence interval (CI): 0.52–0.54). Utility decreased with increasing disease severity: 0.61 (95% CI: 0.60–0.62), 0.51 (95% CI: 0.50–0.52) and 0.40 (95% CI: 0.38–0.43) for mild, moderate and severe disease, respectively. Adjusted differences in mean HSUV between the three severity groups were statistically significant. Conclusion: For the first time in Australia, we have quantified the impact of increasing severity of MS on health utility of people with MS. The HSUVs we have generated will be useful in further health economic analyses of interventions that slow progression of MS.

scholarly journals Risk surveillance and mitigation: autoantibodies as triggers and inhibitors of severe reactions to SARS-CoV-2 infection

2021 ◽  
Vol 27 (1) ◽  
Author(s):  
Catherine Chen ◽  
Aisah Amelia ◽  
George W. Ashdown ◽  
Ivo Mueller ◽  
Anna K. Coussens ◽  
...  
Keyword(s):  
Severe Disease ◽  
Surface Proteins ◽  
Prognostic Indicators ◽  
Individual Risk ◽  
Long Term Effects ◽  
Complement Components ◽  
Screening Strategies ◽  
Life Threatening ◽  
Asymptomatic Infections

AbstractCOVID-19 clinical presentation differs considerably between individuals, ranging from asymptomatic, mild/moderate and severe disease which in some cases are fatal or result in long-term effects. Identifying immune mechanisms behind severe disease development informs screening strategies to predict who are at greater risk of developing life-threatening complications. However, to date clear prognostic indicators of individual risk of severe or long COVID remain elusive. Autoantibodies recognize a range of self-antigens and upon antigen recognition and binding, important processes involved in inflammation, pathogen defence and coagulation are modified. Recent studies report a significantly higher prevalence of autoantibodies that target immunomodulatory proteins including cytokines, chemokines, complement components, and cell surface proteins in COVID-19 patients experiencing severe disease compared to those who experience mild or asymptomatic infections. Here we discuss the diverse impacts of autoantibodies on immune processes and associations with severe COVID-19 disease.

scholarly journals The COVID-19 Hospitalization Metric in the Pre- and Post-vaccination Eras as a Measure of Pandemic Severity: A Retrospective, Nationwide Cohort Study

2021 ◽  
Author(s):  
Nathanael Fillmore ◽  
Jennifer La ◽  
Chunlei Zheng ◽  
Shira Doron ◽  
Nhan Do ◽  
...  
Keyword(s):  
Disease Severity ◽  
Severe Disease ◽  
Supplemental Oxygen ◽  
Case Definition ◽  
Vaccination Status ◽  
P Value ◽  
Case Definitions ◽  
Pandemic Severity ◽  
Vaccine Availability ◽  
The Impact

Abstract Importance: Since the early days of the pandemic, COVID-19 hospitalizations have been used as a measure of pandemic severity. However, case definitions do not include assessments of disease severity, which may be impacted by prior vaccination.Objective: To measure how the severity of respiratory disease changed among inpatients with documented SARS-CoV-2 infection and to measure the impact of vaccination status on these trends, in order to evaluate the accuracy of the metric of “hospitalization plus a positive SARS-CoV-2 test” for tracking pandemic severity.Design: Retrospective cohort of inpatients with laboratory-confirmed SARS-CoV-2. All data were obtained from electronic health records.Setting: Multi-center, nationwide study conducted in the healthcare system of the US Department of Veterans Affairs (VA) from March 1, 2020, through June 30, 2021.Participants: All VA patients admitted to a VA hospital with a laboratory-confirmed SARS-CoV-2 infection within the 14-days prior to admission or during the hospital admission.Main Outcome: Moderate-to-severe COVID-19 disease, defined by use of any supplemental oxygen or documented SpO2 <94%, during an inpatient hospitalization between one day before and two weeks after a positive SARS-CoV-2 test.Exposure: SARS-CoV-2 vaccination status at the time of hospitalization. Patients were regarded as fully vaccinated starting 14 days after receiving the second of a 2-dose regimen or 14 days after receipt of a single-dose vaccine.Results: Among 47,742 admissions in 38,508 unique patients with laboratory-confirmed SARS-CoV-2, N=28,731 met the criteria for moderate-to-severe COVID-19. The proportion with moderate-to-severe disease prior to widespread vaccine availability was 64.0% (95% CI, 63.1-64.9%) versus 52.0% in the later period (95% CI, 50.9-53.2%), p-value for non-constant effect, <0.001. Disease severity in the vaccine era among hospitalized patients was lower among both unvaccinated (55.0%, 95% CI, 53.7-56.4%) and vaccinated patients (42.6%, 95% CI, 40.6-44.8%).Conclusions and Relevance: The proportion of hospitalizations that are due to severe COVID-19 has changed with vaccine availability, thus, increasing proportions of mild and asymptomatic cases are included in hospitalization reporting metrics. The addition of simple measures of disease severity to the case definition of a SARS-CoV-2 hospitalization is a straightforward and objective change that should improve the value of the metric for tracking SARS-CoV-2 disease burden.

scholarly journals 81. Children and COVID-19 in Colorado: The Children’s Hospital Colorado Experience

2020 ◽  
Vol 7 (Supplement_1) ◽  
pp. S172-S173
Author(s):  
Kelly E Graff ◽  
Lori Silveira ◽  
Jane Jarjour ◽  
Shane Curran-Hays ◽  
Lauren Carpenter ◽  
...  
Keyword(s):  
Hospital Admission ◽  
Wide Spectrum ◽  
Severe Disease ◽  
Tertiary Care ◽  
Pediatric Intensive Care ◽  
Respiratory Support ◽  
Logistic Regression Models ◽  
Children's Hospital ◽  
Children’S Hospital ◽  
The Impact

Abstract Background Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a novel coronavirus that causes coronavirus disease of 2019 (COVID-19) and has been reported in &gt; 98,000 children in the U.S (5% of reported cases) as of early June 2020. Most published literature focuses on adults with COVID-19, but little is understood on the impact of SARS-CoV-2 in children. We created a database for children with COVID-19 at Children’s Hospital Colorado (CHCO), a large tertiary care pediatric hospital, to better understand the epidemiology and clinical outcomes of this disease in children. Methods We retrospectively reviewed the medical records of all pediatric and youth patients with positive SARS-CoV-2 PCR test results from March-May 2020. Univariate logistic regression models were used to identify predictors of hospital admission, need for critical care, and need for respiratory support among symptomatic patients, with p-values &lt; 0.05 considered statistically significant. Results We identified 246 patients with SARS-CoV-2 (age range: 17 days-25 years). We noted a Hispanic predominance with 68% of all patients with SARS-CoV-2 identifying as Hispanic or Latino, compared to 29% among all CHCO visits in 2019 (Figure 1). The most common symptoms at presentation were fever, cough, or shortness of breath in 94% of symptomatic patients. Sixty-eight patients (28%) were admitted, of which 7 (10%) required admission to the pediatric intensive care unit (PICU) for symptomatic COVID-19 disease (Figure 2). Age 0–3 months, certain symptoms at presentation, and several types of underlying medical conditions were predictors for both hospital admission and need for respiratory support (Figure 3). Initial and peak C-reactive protein (CRP) values were predictors for PICU admission with median peaks of 24.8mg/dL vs. 2.0mg/dL among PICU vs. non-PICU patients (OR 1.27, p=0.004). Figure 3: Predictors for Admission and Respiratory Support Requirement in CHCO Patients with SARS-CoV-2 Conclusion There is a wide spectrum of illness in children with SARS-CoV-2, ranging from asymptomatic to critical illness. Hispanic ethnicity was disproportionately represented in our cohort, which requires further evaluation. We found that young age, comorbid conditions, and CRP appear to be risk factors for severe disease in children. Disclosures Kelly E. Graff, MD, BioFire Diagnostics, LLC (Grant/Research Support)

scholarly journals Factors Associated with Hospitalization and Disease Severity in a Racially and Ethnically Diverse Population of COVID-19 Patients

2020 ◽  
Author(s):  
Angelico Mendy ◽  
Senu Apewokin ◽  
Anjanette A. Wells ◽  
Ardythe L. Morrow
Keyword(s):  
Vitamin D ◽  
Vitamin D Deficiency ◽  
Disease Severity ◽  
Severe Disease ◽  
Ethnically Diverse ◽  
Chronic Obstructive ◽  
Factors Associated ◽  
Race Ethnicity ◽  
The Impact ◽  
Hispanic White

ABSTRACTBackgroundThe coronavirus disease (COVID-19) first identified in Wuhan in December 2019 became a pandemic within a few months of its discovery. The impact of COVID-19 is due to both its rapid spread and its severity, but the determinants of severity have not been fully delineated.ObjectiveIdentify factors associated with hospitalization and disease severity in a racially and ethnically diverse cohort of COVID-19 patients.MethodsWe analyzed data from COVID-19 patients diagnosed at the University of Cincinnati health system from March 13, 2020 to May 31, 2020. Severe COVID-19 was defined as admission to intensive care unit or death. Logistic regression modeling adjusted for covariates was used to identify the factors associated with hospitalization and severe COVID-19.ResultsAmong the 689 COVID-19 patients included in our study, 29.2% were non-Hispanic White, 25.5% were non-Hispanic Black, 32.5% were Hispanic, and 12.8% were of ‘Other’ race/ethnicity. About 31.3% of patients were hospitalized and 13.2% had severe disease. In adjusted analyses, the sociodemographic factors associated with hospitalization and/or disease severity included older age, non-Hispanic Black or Hispanic race/ethnicity (compared non-Hispanic White), and smoking. The following comorbidities: diabetes, hypercholesterolemia, asthma, chronic obstructive pulmonary disease (COPD), chronic kidney disease, cardiovascular diseases, osteoarthritis, and vitamin D deficiency, were associated with hospitalization and/or disease severity. Hematological disorders such as anemia, coagulation disorders, and thrombocytopenia were associated with higher odds of both hospitalization and disease severity.ConclusionThis study confirms race and ethnicity as predictors of severe COVID-19 and identifies clinical risk factors not previously reported such a vitamin D deficiency, hypercholesterolemia, osteoarthritis, and anemia.

scholarly journals The impact of Coronavirus disease 2019 (COVID-19) on health systems and household resources in Africa and South Asia

2020 ◽  
Author(s):  
Nicholas Davies ◽  
Sedona Sweeney ◽  
Sergio Torres-Rueda ◽  
Fiammetta Bozzani ◽  
Nichola Kitson ◽  
...  
Keyword(s):  
United States ◽  
Health Systems ◽  
Resource Use ◽  
Healthcare Workers ◽  
Addis Ababa ◽  
Severe Disease ◽  
The United States ◽  
Economic Implications ◽  
Hospital Beds ◽  
The Impact

AbstractBackgroundCoronavirus disease 2019 (COVID-19) epidemics strain health systems and households. Health systems in Africa and South Asia may be particularly at risk due to potential high prevalence of risk factors for severe disease, large household sizes and limited healthcare capacity.MethodsWe investigated the impact of an unmitigated COVID-19 epidemic on health system resources and costs, and household costs, in Karachi, Delhi, Nairobi, Addis Ababa and Johannesburg. We adapted a dynamic model of SARS-CoV-2 transmission and disease to capture country-specific demography and contact patterns. The epidemiological model was then integrated into an economic framework that captured city-specific health systems and household resource use.FindingsThe cities severely lack intensive care beds, healthcare workers and financial resources to meet demand during an unmitigated COVID-19 epidemic. A highly mitigated COVID-19 epidemic, under optimistic assumptions, may avoid overwhelming hospital bed capacity in some cities, but not critical care capacity.InterpretationViable mitigation strategies encompassing a mix of responses need to be established to expand healthcare capacity, reduce peak demand for healthcare resources, minimise progression to critical care and shield those at greatest risk of severe disease.FundingBill & Melinda Gates Foundation, European Commission, National Institute for Health Research, Department for International Development, Wellcome Trust, Royal Society, Research Councils UK.Research in contextEvidence before this studyWe conducted a PubMed search on May 5, 2020, with no language restrictions, for studies published since inception, combining the terms (“cost” OR “economic”) AND “covid”. Our search yielded 331 articles, only two of which reported estimates of health system costs of COVID-19. The first study estimated resource use and medical costs for COVID-19 in the United States using a static model of COVID 19. The second study estimated the costs of polymerase chain reaction tests in the United States. We found no studies examining the economic implications of COVID-19 in low- or middle-income settings.Added value of this studyThis is the first study to use locally collected data in five cities (Karachi, Delhi, Nairobi, Addis Ababa and Johannesburg) to project the healthcare resource and health economic implications of an unmitigated COVID-19 epidemic. Besides the use of local data, our study moves beyond existing work to (i) consider the capacity of health systems in key cities to cope with this demand, (ii) consider healthcare staff resources needed, since these fall short of demand by greater margins than hospital beds, and (iii) consider economic costs to health services and households.Implications of all the evidenceDemand for ICU beds and healthcare workers will exceed current capacity by orders of magnitude, but the capacity gap for general hospital beds is narrower. With optimistic assumptions about disease severity, the gap between demand and capacity for general hospital beds can be closed in some, but not all the cities. Efforts to bridge the economic burden of disease to households are needed.

scholarly journals Combined Indexes of Serum NLR, CRP, LDH, IL-6 and D-Dimer Levels are a Biomarker of Disease Severity and Prognostic Predictor in Patients with Coronavirus Disease 2019

2021 ◽  
Author(s):  
Jing Li ◽  
Mingyang Tang ◽  
Didi Liu ◽  
Fengchao Wang ◽  
Yanqing Yang
Keyword(s):  
Disease Progression ◽  
Disease Severity ◽  
Severe Disease ◽  
Composite Endpoint ◽  
Serum Markers ◽  
Inflammatory Factors ◽  
Rna Detection ◽  
Host Immune Responses ◽  
Positive Rate ◽  
D Dimer

Abstract Background: Coronavirus disease-2019 (COVID-19) has become a worldwide emergency and has had a severe impact on human health. Inflammatory factors have the potential to either enhance the efficiency of host immune responses or damage the host organs with immune overreaction in COVID-19. Therefore, there is an urgent need to investigate the functions of inflammatory factors and serum markers that participate in disease progression. Methods: In total, 54 COVID-19 patients were enrolled in this study. Disease severity was evaluated by clinical evaluation, laboratory tests, and computed tomography (CT) scans. Data were collected at: admission, 3–5 days after admission, when severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA detection became negative, and composite endpoint. Results: We found that the positive rate in sputum was three times higher than that in throat swabs. Higher levels of C-reactive protein (CRP), lactate dehydrogenase (LDH), D-dimer (D-D), interleukin-6 (IL-6) and neutrophil-to-lymphocyte (NLR) or lower lymphocyte counts suggested more severe disease, and the levels of cytokines and serum markers were intrinsically correlated with disease progression. When SARS-CoV-2 RNA detection became negative, the receiver operating characteristic (ROC) curve demonstrated that LDH had the highest sensitivity independently, and four indicators (NLR, CRP, LDH, and D-D) when combined had the highest sensitivity in distinguishing critically ill patients from mild ones. Conclusions: Monitoring dynamic changes in NLR, CRP, LDH, IL-6, and D-D levels, combined with CT imaging and viral RNA detection in sputum, could aid in severity evaluation and prognosis prediction and facilitate COVID-19 treatment.

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