Predictor Of Severe COVID-19 Research Articles

Male gender and aging as predictors of severe COVID-19: Studying the genetic, laboratory, radiologic and clinical findings among Egyptianadults

COVID-19 poses a serious risk, especially to the elderly. Additionally, COVID-19 has demonstrated a blatant sex-specific bias, with men exhibiting a more severe reaction and greater fatality rate. The aim of this study is to assess the genotypic and allelic frequencies of the chemokine ligand CXCL12 rs2839693 and its receptor CXCR4 rs2228014 according to age and sex. Also, to evaluate the interaction between age and sex and other risk variables affects how severe COVID-19 is.The present study conducted on 131 female and 169 male COVID-19 Egyptian patients who admitted to Assiut University Quarantine Hospital during the period from July to November 2022, the mean age of patients was 64.31±11.002 years old, patients with age > 65 years were 156 and < 65 years old were 144. Real-time PCR was used to identify the polymorphisms of CXCL12 rs2839693 and CXCR4 rs2228014 using a TaqMan test probe.No significant differences in CXCL12 rs2839693 and CXCR4 rs2228014 genotypic and allelic frequencies according to age and sex.Severe/critical illness was more prevalent in males than females. Also, severe and critical illness was more prevalent in patients with age >65years than patients with age ≤65.Of the statistics that are usually obtained upon admission, age and sex were significant indicators of the severity of the condition. Severe instances were more likely to occur in males and elders. Particular care needs to be paid to older male individuals, as well as individuals with comorbid diseases.

Psychopharmacotherapy factor in the variants of COVID-19 course in psychiatric inpatients

The aim of this study is to examine the relationship between the severity and duration criteria of COVID-19 and the psychopharmacotherapy administered to patients in within a psychiatric hospital.Materials and Methods. We analyzed 169 case histories involving completed clinical cases of COVID-19 treatment in a specialized infectious psychiatric department in St. Petersburg, covering the period from May 2020 to January 2021. Correlation, dispersion, and regression analyses were employed to evaluate severe and mild COVID-19 progression indicators, as well as the duration of persistent SARS-CoV-2 viral shedding. We assessed the clinical and laboratory parameters in patients, along with the psychopharmacotherapy administered, including antidepressants, antipsychotics, and acid sphingomyelinase inhibitors (FIASMA-active drugs).Results. Cardiovascular diseases emerged as a predictor of severe COVID-19 when combined with an increasing platelet-to-lymphocyte ratio (PLR), increasing the risk of severe course by over two-fold. The use of any psychotropic agents was associated with a 0.9% increase in the risk of severe course of COVID-19 for each unit increase in the systemic inflammation index PLR, specifically in patients with intellectual disability (ICD-10 codes F70-79), when compared to patients with schizophrenia (ICD-10 codes F20-29). High PLR values and the use of FIASMA-active drugs were associated with prolonged COVID-19 duration, while antidepressant therapy and elevated C-reactive protein levels were associated with a reduced predicted duration of viral shedding in 13.8% of variance. Additional consideration of the nosology of psychiatric disorders in the regression model increased the proportion of explained variance to 22.8%.Conclusion. Consideration should be given to thymoanaleptic therapy for individuals with psychiatric disorders during periods of increased disease incidence leading up to potential SARS-CoV-2 infection, as it may serve as a protective factor against COVID-19. Furthermore, there is no evidence to suggest adverse effects of antipsychotics on the severity and duration of COVID-19. Further research is required to investigate the effects of FIASMA-active psychopharmacological agents within nosologically homogeneous groups.

Age-related differences in the cytokine profile in the lungs of Syrian hamsters (Mesocricetus auratus) infected with SARS-CoV-2 virus

Cytokine profile and age play a significant role in COVID-19. A hyperinflammatory response caused by proinflammatory cytokines can lead to cytokine storm and tissue damage. And the levels of interferons, which play an essential role in antiviral immunity, decrease with age. In this regard, there is a need to study the age-related characteristics of COVID-19. Syrian hamsters (Mesocricetus auratus) are the primary model objects for studying the SARS-CoV-2 infectious process. Classic laboratory animals such as mice and rats are not infected by this virus. Current research aimed to examine and compare the cytokine profile in the lungs of young (5-month-old) and aging (18-month-old) individuals of Syrian hamsters infected with the SARS-CoV-2 virus. The levels of cytokines were studied by ELISA: TNF-α, as the main proinflammatory cytokine; IL-6, as the predictor of severe COVID-19; INF-α and INF-γ, which are important components of antiviral immunity. The study showed that during COVID-19, the level of the proinflammatory marker TNF-α significantly increased in 5-month-old hamsters, while Il-6 increased in 18-month-old hamsters. Interferon levels were higher in young, healthy animals than in healthy, aging animals.

2705. Predictors of Severe COVID-19 among Solid Organ Transplant Recipients

Abstract Background While some studies have found worse COVID-19 outcomes among solid organ transplant (SOT) recipients, others found no difference when comorbidities and other risk factors for severe disease were accounted for. It remains unclear whether immunosuppressive medications increase the risk of progression to severe disease in SOT recipients. Methods We conducted a retrospective case-control study of SOT recipients diagnosed with COVID-19 at the University of Kansas Medical Center between January 1, 2020 and December 31, 2022. Severe COVID-19 was defined by hypoxia while the patient was on room air during a 21-day period after the COVID-19 diagnosis was established. We fit a logistic regression model with severe COVID-19 as the response variable and adjusted for prescription of mycophenolate, tacrolimus and prednisone and a set of covariates including age, sex, race, body mass index, hypertension, diabetes mellitus, prespecified time period of COVID-19 diagnosis during the pandemic, chronic heart disease, chronic lung disease, malignancy, end stage renal disease, cirrhosis, smoking, receipt of COVID-19 vaccine, and receipt of monoclonal antibodies. Results A total of 570 SOT recipients were diagnosed with COVID-19. Our cohort consisted of 458 kidney, 73 liver, 54 heart, 43 pancreas, and 8 lung recipients. The median patient age was 54 years, 59% were male, and 70% were white. Severe COVID-19 developed in 127/570 (22.3%) patients. A total of 58/570 (10.2%) patients died. A multivariable analysis showed that age (OR = 1.04; p < 0.01), race other than white (OR = 1.88; p = 0.02), chronic heart disease (OR = 1.91, p = 0.01), chronic lung disease (OR = 2.21; p = 0.02), lack of prior COVID-19 vaccination (OR = 2.09; p = 0.01), and not receiving treatment with monoclonal antibodies (OR = 3.82; p < 0.01) were associated with severe COVID-19. Being on treatment with mycophenolate, tacrolimus, or prednisone at the time of COVID-19 diagnosis was not associated with severe disease. Conclusion Patients receiving mycophenolate, tacrolimus, or prednisone at the time of COVID-19 diagnosis were not more likely to experience severe disease. Overall mortality in our SOT population was 10%. Disclosures All Authors: No reported disclosures

Exploring dysregulated immune response genes and endothelial dysfunction biomarkers as predictors of severe COVID-19

Identifying individuals and factors associated with severe cases of COVID-19 is crucial as the pandemic continues to spread globally. Effective biomarkers for predicting severe cases are essential for optimizing clinical management, therapy, and preventing unfavorable outcomes. This exploratory observational study aimed to investigate the expression of dysregulated immune response genes (ARG1, NOS2, ITGA4, and SELPLG) in total leukocytes, plasmatic levels of P-selectin and PSGL-1, and their clinical associations in patients with mild and severe COVID-19. Data from 117 confirmed COVID-19 patients (severe = 58, mild = 59) were collected upon admission. Gene expression was measured using RT-qPCR, and plasma protein levels assessed with ELISA assay. The severe COVID-19 patient group had a higher median age of 62.0 (p = 0.0001), a higher proportion of black individuals (86.2%, p < 0.0001), and more males (65.5%, p = 0.007). The neutrophil–lymphocyte ratio (NLR) and platelet-lymphocyte ratio (PLR) were significantly higher in the severe COVID-19 patient group (p < 0.0001), indicating ongoing systemic inflammation. Severe COVID-19 patients also exhibited increased expression of ARG1 (p < 0.05) and SELPLG (p < 0.0001) genes, as well as higher concentrations of soluble P-selectin (p < 0.005) and PSGL-1 (p < 0.05) proteins. Multivariate analysis revealed that NLR, PLR, the expression of SELPLG and sPSGL-1 were independent predictors of COVID-19 severity. In conclusion, this study suggests that biomarkers of endothelial dysfunction and dysregulated leukocyte responses are associated with COVID-19 severity, serving as promising predictive tools for optimizing clinical management and patient monitoring.

Клинико-лабораторная характеристика больных коронавирусной инфекцией

The purpose — to establish the clinical and laboratory features of COVID-19 in patients who were hospitalized at the Republic Clinical Hospital for Infectious Diseases in Kazan and to identify predictors of severe disease and death. Material and methods. A comprehensive examination of 172 patients with coronavirus infection (COVID-19) was carried out. Patients were analyzed by gender, age, presence of vaccination against COVID-19, comorbidities, laboratory data — levels of lymphocytes, C reactive protein (CRP), ferritin, lactate dehydrogenase (LDH), D-dimer, fibrinogen, interleukin-6 (IL-6), and disease outcomes. Results. There were no gender differences in patients with respect to the severity of COVID-19, clinical manifestations, comorbidities, or disease outcome (p &gt; 0.05). Severe and extremely severe forms of the disease among individuals vaccinated against COVID-19 were recorded significantly less frequently (p &lt; 0.05). The predominant symptoms of coronavirus infection were weakness, fever, headache, cough, shortness of breath. Concomitant pathology was more often recorded with severe COVID-19 than with mild (p &lt; 0.05). At admission, all patients had lymphopenia, elevated levels of CRP, ferritin, LDH, D-dimer, fibrinogen, and IL-6, the severity of which was significantly higher in severe COVID-19 and death (p &lt; 0.01). Conclusion. Lymphopenia, hypofibrinogenemia, elevated levels of CRP, ferritin, LDH, IL-6, and D-dimer should be regarded as predictors of severe COVID-19 and death. Monitoring the dynamics of these blood biomarkers provides the individual approach to the management of patients with coronavirus infection.

SARS-CoV-2 severity prediction in young adults using artificial intelligence

Aim: to build a predictive model for severe COVID-19 prediction in young adults using deep learning methods. Materials and methods: data from 906 medical records of patients aged 18 to 44 years with laboratory-confirmed SARS-CoV-2 infection during 2020–2021 period was analyzed. Evaluation of laboratory and instrumental data was carried out using the Mann-Whitney U-test. The level of statistical significance was p≤0,05. The neural network was trained using the Pytorch framework. Results: in patients with mild to moderate SARS-CoV-2 infection, peripheral oxygen saturation, erythrocytes, hemoglobin, total protein, albumin, hematocrit, serum iron, transferrin, and absolute peripheral blood eosinophil and lymphocyte counts were significantly higher than in patients with severe СOVID-19 (p&lt; 0,001). The values of the absolute number of neutrophils, ESR, glucose, ALT, AST, CPK, urea, LDH, ferritin, CRP, fibrinogen, D-dimer, respiration rate, heart rate, blood pressure in the group of patients with mild and moderate severity were statistically significantly lower than in the group of severe patients (p &lt; 0.001). Eleven indicators were identified as predictors of severe COVID-19 (peripheral oxygen level, peripheral blood erythrocyte count, hemoglobin level, absolute eosinophil count, absolute lymphocyte count, absolute neutrophil count, LDH, ferritin, C-reactive protein, D-dimer levels) and their threshold values. A model intended to predict COVID-19 severity in young adults was built. Conclusion. The values of laboratory and instrumental indicators obtained in patients with SARS-CoV-2 infection upon admission significantly differ. Among them eleven indicators were significantly associated with the development of a severe COVID-19. A predictive model based on artificial intelligence method with high accuracy predicts the likelihood of severe SARS-CoV-2 course development in young adults.

The informative value of CD3+CD4+ and CD3+CD8+ T-cell count and cHIS scale as predictors of severe COVID-19 when using interleukin-6 receptor blockers in the in-hospital setting

Clinical and laboratory signs of hyperinflammatory response in COVID-19 may serve as prognostic markers of the disease scenario. In real-world practice, there is an unmet need to determine the optimal timing of identifying predictors of SARS-CoV-2 adverse outcomes in the context of patient stratification to improve the effectiveness of anti-IL-6R therapy. Lymphopenia has a high informative value for the adverse prognosis of the COVID-19 course; however, the informative value of CD3+CD4+, CD3+CD8+ T-cell count remains questionable. In addition to lymphocyte phenotyping, a six-criterion additive scale (cHIS) was used in the study. To study the informative value of CD3+CD4+, CD3+CD8+ T-cell phenotyping and cHIS scale as predictors of severe COVID-19 when using IL-6R blockers. A single-center, bi-directional study included 179 patients with SARS-CoV-2-induced community-acquired pneumonia with severe acute inflammation and progressing respiratory failure. Data were obtained from electronic patient records. Anti-IL-6R was administered in addition to standard therapy in the cohorts. The following disease outcomes were used to determine the informative value of the studied parameters: mortality and hospital discharge. Inflammatory markers were measured before and after administering anti-IL-6R, followed by monitoring. Statistical analysis was performed using SPSS (version 25.0). The quantitative indices were described using the median and interquartile range. Quantitative indices were compared using nonparametric methods: Mann-Whitney U-test, Kruskal-Wallis test. The groups were compared by qualitative characteristics using Pearson's chi-square test. Correlation analysis of quantitative indicators was performed using Spearman rank correlation. For additional analysis of the cHIS scale, odds ratio and decision tree methods were used. Differences were considered statistically significant at р≤0,05. Immunophenotyping of lymphocytes as a predictor of the severe SARS-CoV-2 requires further research. The cHIS scale may be implemented in routine clinical practice due to its high predictive value. A cHIS score of ≥2 on the first day of admission is a critical threshold for intensification and revision of therapy. The prognosis with cHIS is logically relevant in the first three days of hospitalization. The main result of the study is the definition of target groups of patients with community-acquired SARS-CoV-2 pneumonia for the IL-6R-blockers, considering the timing of their effective use in real clinical practice.

Predictors of severe COVID-19 among healthcare workers in Sabah, Malaysia

BackgroundHealthcare workers (HCWs) is the high-risk group for COVID-19 infection due to increased workplace exposure. However, evidence of the disease burden and factors associated with severe COVID-19 infection among HCWs is limited. Therefore, this article aims to describe the prevalence of severe COVID-19 disease among HCWs in Sabah, Malaysia, and to determine the factors associated with severe COVID-19 infection.MethodA retrospective cross-sectional study was carried out by assessing the data of COVID-19-infected HCWs in Sabah, Malaysia, from 1st March 2021 until 30th September 2021. Logistic regression analysis was used in this study.ResultsThree thousand and forty HCWs were diagnosed with COVID-19 from 1st March 2021 until 30th September 2021. Of the 3040 HCWs, 2948 (97.0%) HCWs were mild, whereas 92 (3.0%) were severe. The multivariate logistic regression model showed that severe COVID-19 among HCWs in Sabah was associated with those do not receive any COVID-19 vaccination (aOR 6.061, 95% CI 3.408 – 10.780), underlying co-morbidity (aOR 3.335, 95% CI 2.183 – 5.096), and female (aOR 1.833, 95% CI 1.090 – 3.081).ConclusionHCWs should strictly adhere to preventive measures, including vaccination, personal protective equipment, and early referral to a physician upon identifying severe COVID-19 infection. Early screening and aggressive co-morbidity treatment among HCWs are essential for public health practitioners to prevent severe COVID-19 disease. Regardless of co-morbidity status, HCWs should stay up to date with COVID-19 vaccination, including booster doses.

CLINICAL AND LABORATORY PREDICTORS OF SEVERE COVID-19 IN MEN AND WOMEN OF DIFFERENT AGE GROUPS

The large amount of papers on studying severe COVID-19 predictors have been published so far, but unfortunately the identified criteria are not universal for different regions of Russia and for the whole world. Therefore, a decision was made to apply routine research methods and compare the criteria previously proposed by other researchers with the criteria identified by us in patients living in Astrakhan Region. The study aimed at searching for and analyzing clinical and laboratory predictors to improve prediction of severe COVID-19 in men and women of different age groups. Materials and methods. Medical records of 361 patients were used as clinical material to conduct a retrospective study. Four groups with sex and age differencies were formed to verify the factors aggravating the course of COVID-19. Examination was performed according to Version 9 of the Temporary Guidelines for Prevention, Diagnosis and Treatment of the Novel Coronavirus Infection (COVID-19). Results. Clinical evidence on admission included unspecific complaints typical of other acute respiratory diseases – generalized weakness, temperature rise over 37.5° C, dyspnea, dry cough, and compressing pain. The spectrum of comorbid diseases includes hypertension, congestive heart failure, coronary heart disease, diabetes mellitus, and obesity. Conclusions. Delayed hospitalization of patients from the day of disease onset due to nonspecific COVID-19 symptoms is one of the unfavorable clinical predictors. Comorbidities that aggravate the course of COVID-19 are consistent with the comorbid conditions identified by other researchers [1,2]. High levels of procalcitonin, D-dimer, brain natriuretic peptide, lactate dehydrogenase and blood creatinine were identified as the most significant predictors of severe COVID-19 on admission, which is also consistent with the findings of other authors. Laboratory parameters like alanine transaminase &gt; 45 u/l and aspartate transaminase &gt; 55 u/l can be used for male patients aged 55 and older, while an increased leukocyte count &gt; 7.4 ×109/l and C-reactive protein &gt; 82 g/l – for female patients aged 55 and older.

Predictors of hospitalisation and death due to SARS-CoV-2 infection in Finland: A population-based register study with implications to vaccinations

IntroductionThe aim of this study was to investigate how age and underlying medical conditions affect the risk of severe outcomes following SARS-CoV-2 infection and how they should be weighed while prioritising vaccinations against COVID-19. MethodsThis population-based register study includes all SARS-CoV-2 PCR-test-positive cases until 24 Feb 2021, based on the Finnish National Infectious Diseases Register. The cases were linked to other registers to identify presence of predisposing factors and severe outcomes (hospitalisation, intensive care treatment, death). The odds of severe outcomes were compared in those with and without the pre-specified predisposing factors using logistic regression. Furthermore, population-based rates were compared between those with a given predisposing factor and those without any of the specified predisposing factors using negative binomial regression. ResultsAge and various comorbidities were found to be predictors of severe COVID-19. Compared to 60–69-year-olds, the odds ratio (OR) of death was 7.1 for 70–79-year-olds, 26.7 for 80–89-year-olds, and 55.8 for ≥ 90-year-olds. Among the 20–69-year-olds, chronic renal disease (OR 9.4), malignant neoplasms (5.8), hematologic malignancy (5.6), chronic pulmonary disease (5.4), and cerebral palsy or other paralytic syndromes (4.6) were strongly associated with COVID-19 mortality; severe disorders of the immune system (8.0), organ or stem cell transplant (7.2), chronic renal disease (6.7), and diseases of myoneural junction and muscle (5.5) were strongly associated with COVID-19 hospitalisation. Type 2 diabetes and asthma, two very common comorbidities, were associated with all three outcomes, with ORs from 2.1 to 4.3. The population-based rate of SARS-CoV-2 infection decreased with age. Taking the 60–69-year-olds as reference, the rate ratio was highest (3.0) for 20–29-year-olds and < 1 for 70–79-year-olds and 80–89-year-olds. ConclusionComorbidities predispose for severe COVID-19 among younger ages. In vaccine prioritisation both the risk of infection and the risk of severe outcomes, if infected, should be considered.

Early Th2 inflammation in the upper respiratory mucosa as a predictor of severe COVID-19 and modulation by early treatment with inhaled corticosteroids: a mechanistic analysis

BackgroundCommunity-based clinical trials of the inhaled corticosteroid budesonide in early COVID-19 have shown improved patient outcomes. We aimed to understand the inflammatory mechanism of budesonide in the treatment of early COVID-19.MethodsThe STOIC trial was a randomised, open label, parallel group, phase 2 clinical intervention trial where patients were randomly assigned (1:1) to receive usual care (as needed antipyretics were only available treatment) or inhaled budesonide at a dose of 800 μg twice a day plus usual care. For this experimental analysis, we investigated the nasal mucosal inflammatory response in patients recruited to the STOIC trial and in a cohort of SARS-CoV-2-negative healthy controls, recruited from a long-term observational data collection study at the University of Oxford. In patients with SARS-CoV-2 who entered the STOIC study, nasal epithelial lining fluid was sampled at day of randomisation (day 0) and at day 14 following randomisation, blood samples were also collected at day 28 after randomisation. Nasal epithelial lining fluid and blood samples were collected from the SARS-CoV-2 negative control cohort. Inflammatory mediators in the nasal epithelial lining fluid and blood were assessed for a range of viral response proteins, and innate and adaptive response markers using Meso Scale Discovery enzyme linked immunoassay panels. These samples were used to investigate the evolution of inflammation in the early COVID-19 disease course and assess the effect of budesonide on inflammation.Findings146 participants were recruited in the STOIC trial (n=73 in the usual care group; n=73 in the budesonide group). 140 nasal mucosal samples were available at day 0 (randomisation) and 122 samples at day 14. At day 28, whole blood was collected from 123 participants (62 in the budesonide group and 61 in the usual care group). 20 blood or nasal samples were collected from healthy controls. In early COVID-19 disease, there was an enhanced inflammatory airway response with the induction of an anti-viral and T-helper 1 and 2 (Th1/2) inflammatory response compared with healthy individuals. Individuals with COVID-19 who clinically deteriorated (ie, who met the primary outcome) showed an early blunted respiratory interferon response and pronounced and persistent Th2 inflammation, mediated by CC chemokine ligand (CCL)-24, compared with those with COVID-19 who did not clinically deteriorate. Over time, the natural course of COVID-19 showed persistently high respiratory interferon concentrations and elevated concentrations of the eosinophil chemokine, CCL-11, despite clinical symptom improvement. There was persistent systemic inflammation after 28 days following COVID-19, including elevated concentrations of interleukin (IL)-6, tumour necrosis factor-α, and CCL-11. Budesonide treatment modulated inflammation in the nose and blood and was shown to decrease IL-33 and increase CCL17. The STOIC trial was registered with ClinicalTrials.gov, NCT04416399.InterpretationAn initial blunted interferon response and heightened T-helper 2 inflammatory response in the respiratory tract following SARS-CoV-2 infection could be a biomarker for predicting the development of severe COVID-19 disease. The clinical benefit of inhaled budesonide in early COVID-19 is likely to be as a consequence of its inflammatory modulatory effect, suggesting efficacy by reducing epithelial damage and an improved T-cell response.FundingOxford National Institute of Health Research Biomedical Research Centre and AstraZeneca.

322. Risk Factors for COVID-19 Disease Severity Using Electronic-Health Records in a Real-World Cohort in the United States

BackgroundOver 32 million cases of COVID-19 have been reported in the US. Outcomes range from mild upper respiratory infection to hospitalization, acute respiratory failure, and death. We assessed risk factors associated with severe disease, defined as hospitalization within 21 days of diagnosis or death, using US electronic health records (EHR).MethodsPatients in the Optum de-identified COVID-19 EHR database who were diagnosed with COVID-19 in 2020 were included in the analysis. Regularized multivariable logistic regression was used to identify risk factors for severe disease. Covariates included demographics, comorbidities, history of influenza vaccination, and calendar time.ResultsOf the 193,454 eligible patients, 36,043 (18.6%) were hospitalized within 21 days of COVID-19 diagnosis, and 6,397 (3.3%) died. Calendar time followed an inverse J-shaped relationship where severe disease rates rapidly declined in the first 25 weeks of the pandemic. BMI followed an asymmetric V-shaped relationship with highest rates of disease severity observed at the extremes. In the multivariable model, older age had the strongest association with disease severity (odds ratios and 95% confidence intervals of significant associations in Figure). Other risk factors were male sex, uninsured status, underweight and obese BMI, higher Charlson Comorbidity Index, and individual comorbidities including hypertension. Asthma and overweight BMI were not associated with disease severity. Blacks, Hispanics, and Asians experienced higher odds of disease severity compared to Whites.Figure. Significant associations (odds ratio and 95% confidence intervals) with COVID-19 severity (hospitalization or death), adjusted for geographical division. Reference and abbreviation categories: Charlson comorbidity index (CCI) = 0; Age = 18-30; Sex = Female; Race/Ethnicity = White; Insurance = Commercial; Body mass index (BMI) = 18.5-25; Calendar time = 0-25 weeks; Chronic obstructive pulmonary disease (COPD).ConclusionOdds of hospitalization or death have decreased since the start of the pandemic, with the steepest decline observed up to mid-August, possibly reflecting changes in both testing and treatment. Older age is the most important predictor of severe COVID-19. Obese and underweight, but not overweight, BMI were associated with increased odds of disease severity when compared to normal weight. Hypertension, despite not being included in many guidelines for vaccine prioritization, is a significant risk factor. Pronounced health disparities remain across race and ethnicity after accounting for comorbidities, with minorities experiencing higher disease severity.Disclosures Shemra Rizzo, PhD, F. Hoffmann-La Roche Ltd. (Shareholder)Genentech, Inc. (Employee) Ryan Gan, PhD, F. Hoffmann-La Roche Ltd (Shareholder)Genentech, Inc. (Employee) Devika Chawla, PhD MSPH, F. Hoffmann-La Roche Ltd. (Shareholder)Genentech, Inc. (Employee) Kelly Zalocusky, PhD, F. Hoffmann-La Roche Ltd. (Shareholder)Genentech, Inc. (Employee) Xin Chen, PhD, F. Hoffmann-La Roche Ltd. (Shareholder)Genentech, Inc. (Employee) Yifeng Chia, PhD, F. Hoffmann-La Roche Ltd (Shareholder)Genentech, Inc. (Employee)

Relationship between chest computed tomography findings and clinical conditions of coronavirus disease (COVID-19): A multicentre experience.

This study aimed to investigate the clinical and chest computed tomography (CT) features associated with clinical parameters for coronavirus disease (COVID-19) in the capital of Turkey, Ankara. Epidemiological, clinical features, laboratory findings and radiological characteristics of 1563 hospitalised patients with COVID-19 in Ankara were collected, reviewed and analysed in this study. The risk factors associated with disease severity were investigated. Non-severe (1214; 77.7%) and severe cases (349; 22.3%) were enrolled in the study. Compared with the non-severe group, the severe group were significantly older and had more comorbidities (ie, hypertension, diabetes mellitus, cardiovascular disease and chronic kidney disease). Smoking was more common in the severe group. Severe patients had higher respiratory rates and higher incidences of cough and dyspnoea compared with non-severe patients. Compared with the non-severe patients, the severe patients had increased C-reactive protein (CRP), procalcitonin, neutrophil to lymphocyte ratio (NLR) and CRP/albumin ratio and decreased albumin. The occurrence rates of consolidation, subpleural sparing, crazy-paving pattern, cavity, halo sign, reversed halo sign, air bronchogram, pleural thickening, micronodule, subpleural curvilinear line and multilobar and bilateral involvement in the CT finding of the severe patients were significantly higher than those of the non-severe patients. Many factors are related to the severity of COVID-19, which can help clinicians judge the severity of the patient and evaluate the prognosis. This cohort study revealed that male sex, age (≥55years), patients with any comorbidities, especially those with cardiovascular disease, dyspnoea, increased CRP, D-dimer and NLR, and decreased lymphocyte count and CT findings of consolidation and multilobar involvement were predictors of severe COVID-19.

Predictors of severe COVID-19 in kidney transplant recipients in the different epidemic waves: Analysis of the Spanish Registry.

SARS‐CoV‐2 infection has produced high mortality in kidney transplant (KT) recipients, especially in the elderly. Until December 2020, 1011 KT with COVID‐19 have been prospectively included in the Spanish Registry and followed until recovery or death. In multivariable analysis, age, pneumonia, and KT performed ≤6 months before COVID‐19 were predictors of death, whereas gastrointestinal symptoms were protective. Survival analysis showed significant increasing mortality risk in four subgroups according to recipient age and time after KT (age <65 years and posttransplant time >6 months, age <65 and time ≤6, age ≥65 and time >6 and age ≥65 and time ≤6): mortality rates were, respectively, 11.3%, 24.5%, 35.4%, and 54.5% (p < .001). Patients were significantly younger, presented less pneumonia, and received less frequently specific anti‐COVID‐19 treatment in the second wave (July–December) than in the first one (March–June). Overall mortality was lower in the second wave (15.1 vs. 27.4%, p < .001) but similar in critical patients (66.7% vs. 58.1%, p = .29). The interaction between age and time post‐KT should be considered when selecting recipients for transplantation in the COVID‐19 pandemic. Advanced age and a recent KT should foster strict protective measures, including vaccination.

The value of C-reactive protein/albumin, fibrinogen/albumin, and neutrophil/lymphocyte ratios in predicting the severity of CoVID-19.

This retrospective study aimed to determine the predictive values of the C-reactive protein (CRP)/albumin ratio (CAR), fibrinogen/albumin ratio (FAR), and neutrophil/lymphocyte ratio (NLR) parameters, which reflect the systemic inflammatory status, for the severity of COVID-19. A total of 188 patients diagnosed with COVID-19 were enrolled in this study. Among them, 118 were in the severe group, and 70 were in the non-severe group. Levels of albumin, CRP, D-dimer, procalcitonin, fibrinogen, and hemoglobin; leukocyte, neutrophil, lymphocyte, and monocyte counts; and the FAR, CAR, and NLR were compared between the two groups. The CAR, FAR, and NLR values were significantly higher in the severe group compared to the non-severe group. CAR, FAR, and NLR were positively correlated with leukocyte and neutrophil counts and CRP, procalcitonin, and fibrinogen levels. On the other hand, they were inversely correlated with monocyte (except for NLR) and lymphocyte counts. Receiver operator characteristic analysis showed that the area under the curve (AUC) for CAR, FAR, and NLR was 0.841, 0.737, and 0.802, respectively. Our investigation revealed that the CAR, FAR, and NLR indices can be used to predict the severity of COVID-19, among which CAR was the best predictor of severe COVID-19.

Clinical characteristics of 41 patients with pneumonia due to 2019 novel coronavirus disease (COVID-19) in Jilin, China

BackgroundThe clinical characteristics of patients with confirmed 2019 novel coronavirus disease (COVID-19) in Jilin Province, China were investigated.MethodsClinical, laboratory, radiology, and treatment data of 41 hospitalized patients with confirmed COVID-19 were retrospectively collected. The population was stratified by disease severity as mild, moderate, or severe, based on guidelines of the National Health and Medical Commission of China.ResultsThe 41 hospitalized patients with COVID-19 were studied, and the median age was 45 years (interquartile range [IQR], 31–53; range, 10–87 years) and 18 patients (43.9%) were female. All of the patients had recently visited Wuhan or other places (ie, Beijing, Thailand) or had Wuhan-related exposure. Common symptoms included fever (32[78%]) and cough (29[70.7%]). All patients were without hepatitis B/C virus hepatitis. CRP (C-reactive protein, 11.3 mg/L [interquartile range {IQR}, 2.45–35.2]) was elevated in 22 patients (53.7%), and cardiac troponin I (1.5 ng/mL [IQR, 0.8–5.0]) was elevated in 41 patients (100%). Chest computed tomographic scans showed bilateral ground glass opacity (GGO) or GGO with consolidation in the lungs of 27(65.9%) patients. 31(75.6%) patients had an abnormal electrocardiograph (ECG). Comparing the three groups, the levels of CRP and cardiac troponin I, GGO distribution in bilateral lungs, and electrocardiogram changes were statistically significant (p < 0.05). Cardiac troponin I had a strong positive correlation with CRP (r = 0.704, p = 0.042) and LDH (r = 0.738, p = 0.037).ConclusionSignificant differences among the groups suggest that several clinical parameters may serve as biomarkers of COVID-19 severity at hospital admission. Elevated cTnI could be considered as a predictor of severe COVID-19, reflecting the prognosis of patients with severe COVID-19. The results warrant further inspection and confirmation.

NAFLD and COVID-19: a Pooled Analysis.

The earliest evidence from China suggested that COVID-19 patients are even more vulnerable to succumbing from complications in the presence of a multimorbid status, including metabolic syndrome. Due to ongoing metabolic abnormalities, non-alcoholic fatty liver disease (NAFLD) appears to be a potential risk factor for contracting SARS-CoV-2 infection and developing related complications. This is because of the interplay of chronically active inflammatory pathways in NAFLD- and COVID-19-associated acute cytokine storm. The risk of severe disease could also be attributed to compromised liver function as a result of NAFLD. We systematically reviewed current literature to ascertain the relationship between NAFLD and severe COVID-19, independent of obesity, which is considered the major factor risk factor for both NAFLD and COVID-19. We found that NAFLD is a predictor of severe COVID-19, even after adjusting for the presence of obesity (OR 2.358; 95% CI: 1.902–2.923, p < 0.001).

The peripheral lymphocyte count as a predictor of severe COVID-19 and the effect of treatment with ciclesonide

We investigated whether reduced lymphocyte count, could predict the development of severe COVID-19. We also examined whether ciclesonide could prevent the development of severe COVID-19 among patients with the predictors. This was a retrospective cohort study. Of the 30 included patients, 12, 14, and 4 were allocated to severe pneumonia, non-severe pneumonia, and non-pneumonia groups, respectively. The group of the low level of lymphocyte counts of the sixth day after onset was significantly intubated approximately three days later. The incidence of the severe pneumoniae requiring intubation are significantly lower in the patients treated with ciclesonide than without it (11.18 % vs 83.33 %, p = 0.0033). The lymphocyte count after ciclesonide treatment in the non-severe pneumonia group was significantly higher (p = 0. 0156) than before. The lymphocyte count could be used to identify patients that may develop severe COVID-19. Treatment with ciclesonide may prevent the development of severe COVID-19.

Is lung density associated with severity of COVID-19?

PurposeEmphysema and chronic obstructive lung disease were previously identified as major risk factors for severe disease progression in COVID-19. Computed tomography (CT)-based lung-density analysis offers a fast, reliable, and quantitative assessment of lung density. Therefore, we aimed to assess the benefit of CT-based lung density measurements to predict possible severe disease progression in COVID-19.Material and methodsThirty COVID-19-positive patients were included in this retrospective study. Lung density was quantified based on routinely acquired chest CTs. Presence of COVID-19 was confirmed by reverse transcription polymerase chain reaction (RT-PCR). Wilcoxon test was used to compare two groups of patients. A multivariate regression analysis, adjusted for age and sex, was employed to model the relative increase of risk for severe disease, depending on the measured densities.ResultsIntensive care unit (ICU) patients or patients requiring mechanical ventilation showed a lower proportion of medium- and low-density lung volume compared to patients on the normal ward, but a significantly larger volume of high-density lung volume (12.26 dl IQR 4.65 dl vs. 7.51 dl vs. IQR 5.39 dl, p = 0.039). In multivariate regression analysis, high-density lung volume was identified as a significant predictor of severe disease.ConclusionsThe amount of high-density lung tissue showed a significant association with severe COVID-19, with odds ratios of 1.42 (95% CI: 1.09-2.00) and 1.37 (95% CI: 1.03-2.11) for requiring intensive care and mechanical ventilation, respectively. Acknowledging our small sample size as an important limitation; our study might thus suggest that high-density lung tissue could serve as a possible predictor of severe COVID-19.