Severe Coronavirus Disease 2019 Disease Research Articles

Blood transcriptome responses in patients correlate with severity of COVID-19 disease.

Coronavirus disease 2019 (COVID-19) is an infectious disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Infected individuals display a wide spectrum of disease severity, as defined by the World Health Organization (WHO). One of the main factors underlying this heterogeneity is the host immune response, with severe COVID-19 often associated with a hyperinflammatory state. Our current study aimed to pinpoint the specific genes and pathways underlying differences in the disease spectrum and outcomes observed, through in-depth analyses of whole blood transcriptomics in a large cohort of COVID-19 participants. All WHO severity levels were well represented and mild and severe disease displaying distinct gene expression profiles. WHO severity levels 1-4 were grouped as mild disease, and signatures from these participants were different from those with WHO severity levels 6-9 classified as severe disease. Severity level 5 (moderate cases) presented a unique transitional gene signature between severity levels 2-4 (mild/moderate) and 6-9 (severe) and hence might represent the turning point for better or worse disease outcome. Gene expression changes are very distinct when comparing mild/moderate or severe cases to healthy controls. In particular, we demonstrated the hallmark down-regulation of adaptive immune response pathways and activation of neutrophil pathways in severe compared to mild/moderate cases, as well as activation of blood coagulation pathways. Our data revealed discrete gene signatures associated with mild, moderate, and severe COVID-19 identifying valuable candidates for future biomarker discovery.

Evaluation of Health-Related Quality of Life and Mental Health in 729 Medical Students in Indonesia During the COVID-19 Pandemic.

BACKGROUND The coronavirus disease 2019 (COVID-19) pandemic has impacted the health-related quality of life (HRQoL) and mental health worldwide. However, its impact on medical students in Indonesia has not been well documented. This study aimed to evaluate HRQoL and mental health in 729 Indonesian medical students during the COVID-19 pandemic. MATERIAL AND METHODS We conducted a cross-sectional study from 31 August to 30 September 2021. The study instrument was an online questionnaire that was distributed via social media platforms. The 12-item short form version 2 (SF12v2) was used to measure HRQoL, and the 21-item Depression, Anxiety, and Stress Scale (DASS-21) was used to measure mental health. RESULTS From 729 Indonesian medical students included in the analyses, 37.3% had impaired physical component and 66.9% had impaired mental component of HRQoL. The determinants were medical students' island of residence, history of hospitalization, and family member's hospitalization and death due to COVID-19. Concerning mental health, the prevalence of reported symptoms of depression, anxiety, and stress were 45.4%, 65.2%, and 60.9%, respectively. Sex, study method, grade, previous COVID-19 disease severity, comorbidities, previous learning experience, and history of family isolation were identified as the determinants of mental health. CONCLUSIONS This study highlights the adverse effects of COVID-19 on HRQoL and mental health in Indonesian medical students. The results identified key associations, including SARS-CoV-2 infection and comorbidities experienced by the students, the health of their families, including grief following bereavement, and the effects of social isolation during the pandemic.

The value of chest X-ray and CT severity scoring systems in the diagnosis of COVID-19: A review.

Coronavirus disease 2019 (COVID-19) is caused by a coronavirus family member known as severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). The main laboratory test to confirm the quick diagnosis of COVID-19 infection is reverse transcription-polymerase chain reaction (RT-PCR) based on nasal or throat swab sampling. A small percentage of false-negative RT-PCR results have been reported. The RT-PCR test has a sensitivity of 50-72%, which could be attributed to a low viral load in test specimens or laboratory errors. In contrast, chest CT has shown 56-98% of sensitivity in diagnosing COVID-19 at initial presentation and has been suggested to be useful in correcting false negatives from RT-PCR. Chest X-rays and CT scans have been proposed to predict COVID-19 disease severity by displaying the score of lung involvement and thus providing information about the diagnosis and prognosis of COVID-19 infection. As a result, the current study provides a comprehensive overview of the utility of the severity score index using X-rays and CT scans in diagnosing patients with COVID-19 when compared to RT-PCR.

Association of persistent respiratory symptoms with severity of COVID-19

Background: Coronavirus disease 2019 (COVID-19) is a new and highly contagious respiratory disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Symptoms and disease severity of COVID-19 vary from asymptomatic to severe or fatal illness. A major complication of those who survived from COVID-19 is the development of lung disease leading to persistence of respiratory symptoms. The objective of the present study was to find out the association of persistence of respiratory symptoms with severity of COVID-19.
 Methods: This prospective observational study was carried out in the Department of Respiratory Medicine, Bangabandhu Sheikh Mujib Medical University, Dhaka during the period from July 2020 to December 2020. During follow-up around three months (90.62±2.21 days) after the onset of the first COVID-19 symptoms, 500 patients were taken as the study sample.
 Results: Total patients were 500 with 206 (41.2%) severe cases. Two-fifths of the study participants had persistent respiratory symptom at 3 months. Persistence of respiratory symptoms was associated with severity of COVID-19 (p = <0.001). Among the respiratory symptoms, shortness of breath (34.72%) and cough (29.63%) were the most prevalent symptoms that was persisted in severe COVID-19 during follow-up.
 Conclusion: This study has shown that persistent respiratory symptoms were common after COVID-19 that was about 40% and were associated with the severity of COVID-19.
 BIRDEM Med J 2023; 13(1): 16-21

The salivary and nasopharyngeal microbiomes are associated with SARS-CoV-2 infection and disease severity.

Emerging evidence suggests the oral and upper respiratory microbiota may play important roles in modulating host immune responses to viral infection. As the host microbiome may be involved in the pathophysiology of coronavirusdisease 2019 (COVID-19), we investigated associations between the oral and nasopharyngeal microbiome and COVID-19 severity.We collected saliva (n = 78) and nasopharyngeal swab (n = 66) samples from a COVID-19 cohort and characterized the microbiomes using 16S ribosomal RNA gene sequencing. We also examined associations between the salivary and nasopharyngeal microbiome and age, COVID-19 symptoms, and blood cytokines.Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection status, but not COVID-19 severity, was associated with community-level differences in the oral and nasopharyngeal microbiomes. Salivary and nasopharyngeal microbiome alpha diversity negatively correlated with age and were associated with fever and diarrhea. Oral Bifidobacterium, Lactobacillus, and Solobacterium were depleted in patients with severe COVID-19. Nasopharyngeal Paracoccus was depleted while nasopharyngeal Proteus, Cupravidus, and Lactobacillus were increased in patients with severe COVID-19. Further analysis revealed that the abundance of oral Bifidobacterium was negatively associated with plasma concentrations of known COVID-19 biomarkers interleukin 17Fand monocyte chemoattractant protein-1.Our results suggest COVID-19 disease severity is associated with the relative abundance of certain bacterial taxa.

The Relation between ACE Gene Polymorphism and the Severity of COVID-19 Infection.

The coronavirus disease 2019 (COVID-19) pandemic, which emerged in China at the end of 2019, rapidly spread worldwide. The angiotensin-converting enzyme (ACE) gene contains an insertion/deletion (I/D) polymorphism that leads to a higher serum ACE level which is associated with several diseases and also with a high mortality rate in SARS. Therefore, this study aimed at assessing the association between ACE gene polymorphism and the risk and severity of COVID-19 disease in patients. Methodology. Forty-five SARS-CoV-2 infected patients and another random control group of 45 healthy individuals were included. The detection of ACE I/D gene polymorphism in both groups was done by PCR. 53% of infected patients with SARS-CoV-2 had an ACE deletion/deletion genotype (D/D), 27% had an ACE deletion/insertion genotype (D/I), and 20% had an ACE insertion/insertion genotype (I/I). On the one hand, the D/D variant was significantly detected in the COVID-19 patients compared to the control subjects, whereas the I/I variant was significantly detected in the control subjects compared to the COVID-19 patients (p = 0.004). The D/D variant subgroup showed the lowest lymphocytic count compared to the D/I or I/I subgroups. In addition, the C-reactive protein was significantly higher and the oxygen saturation was significantly lower in patients with the D/D allele compared to the other subgroups. ACE gene polymorphism, particularly the DD genotype, was observed to affect the severity of COVID-19 infection.

Prevalence of Anaemia and its Association with Severity of COVID-19 among Hospitalised Patients: A Cross-sectional Study

Introduction: Coronavirus Disease-2019 (COVID-19) emerged as a global pandemic and was associated with various haematologic abnormalities. There are very few studies from India regarding the association between anaemia and disease severity of COVID-19. Aim: To check the prevalence of anaemia and its association with severity of disease among hospitalised COVID-19 patients. Materials and Methods: This was a cross-sectional study involving 203 patients admitted in general ward and Intensive Care Unit (ICU) of a tertiary care hospital in eastern India. Complete blood count at admission along with other relevant clinical and laboratory parameters was noted. Haematological parameters of the patients were described and then correlated with disease severity and death. Spearman’s correlation and Chi-square test were used to determine the associations. Results: Out of 203 patients with COVID-19,145 (71.4%) had anaemia. The study included 107 males (52.7%) and 96 females (47.3%), of which 77 (80%) females had anaemia compared to 68 (63.5%) males. Co-morbidities were present in 73 patients. Haemoglobin levels were significantly negatively correlated with disease severity (p<0.001). This was even true for patients without any other co-morbidities (p<0.05). Haemoglobin was also negatively correlated with deaths in this study (p<0.05). Conclusion: The prevalence of anaemia in admitted patients of COVID-19 was very high and low haemoglobin levels were associated with more severe disease and death. So, low haemoglobin levels in COVID-19 may be considered as a risk factor for more severe disease and death.

The effect of hereditary thrombotic factors and comorbidities on the severity of COVID-19 disease.

Coronavirus disease 2019 (COVID-19) has rapidly spread worldwide and presents critical challenges for public health. Due to its chronic and systemic course, COVID-19 is currently accepted as a multi-systemic infectious disease. Here we explore the possible association between disease course and hereditary thrombotic factors and comorbidities. The patients admitted to the COVID-19 center in the Istanbul Faculty of Medicine were recruited for the study. The patients were classified according to the clinical course, severe vs. mild. Five polymorphic loci were analyzed by multiplex PCR: Factor V Leiden (FVL), FII G20210A, Beta-fibrinogen G-455A, and methylenetetrahydrofolate reductase (MTHFR) C677T and A1298C. FII G20210A and Beta-fibrinogen G-455A genotypes were significantly higher in the study group compared to the literature. Wildtype genotype (GG) in Factor V Leiden locus was significantly associated with low D-Dimer levels (p =0.013). The GA genotype increased the D-Dimer levels 2.55-times compared to the GG genotype (p =0.003). Moreover, the Beta-fibrinogen G-455G genotype was significantly higher in the LDH>250 group (p =0.046). The presence of solid tumors in patients with COVID-19 was related to the severity of the disease course. No evidence of a correlation between the severity of the disease and all five thrombotic mutations was found, whereas the FII G20210A and Beta-fibrinogen G-455A mutations were significantly high compared to previously reported Turkish population data and global carrier rates. This finding will need to be verified by further studies with larger samples since it may reflect a likelihood of having the COVID-19 disease. The high carrier frequency of FVL mutation was more likely present in the D-dimer high group generating an increase in the D-dimer levels 2.55-times compared to the wildtype.

Stress hyperglycemia is associated with disease severity in COVID-19.

Coronavirus disease 2019 (COVID-19) is a global pandemic that has affected millions of people worldwide. In this paper, we analyse the relationship between stress hyperglycaemia and disease severity in patients with COVID-19. A total of 252 patients with COVID-19 were included in this study. The patients were divided into the following groups: COVID-19 with stress hyperglycaemia (SHG), COVID-19 with diabetes (DM), and COVID-19 with normal blood glucose (NG). The stress hyperglycaemia rate (SHR) was calculated using the fasting blood glucose (FBG)/glycated haemoglobin (HbA1c) ratio. To further compare the disease characteristics of different SHRs, we divided the SHR into low SHR and high SHR according to the SHR median. Correlations between the severity of the disease and other factors were analysed after adjusting for sex and age. Multivariate analysis was performed using logistic regression to analyse the risk factors predicting the severity of COVID-19. Compared with the NG group, the SHG group had higher disease severity (p < 0.001); the SHG group had higher HbA1c, FBG, SHR, blood urea nitrogen (BUN), interleukin 6 (IL-6), and neutrophil levels, while lymphocyte, CD3+ T cell, CD8+ T cell, CD4+ T cell, CD16+CD56 cell, and CD19+ cell counts were lower (p < 0.05). Compared with the NG group, the DM group had higher HbA1c, blood glucose, BUN, lactate dehydrogenase (LDH), erythrocyte sedimentation rate (ESR), C-reactive protein (CRP), and neutrophils, while CD8+ T cell counts were lower (p < 0.05). Compared with the DM group, the SHG group had higher SHR and lower HbA1c, CD3+ T cell, CD4+ T cell, CD16+CD56 cell, and T cell ratio levels (p < 0.05). Compared to the low SHR group, the high SHR group had patients with more severe COVID-19 (p = 0.004). Also, the high SHR grouphad higher age, HbA1c, FBG, asparate aminotransferaze (AST), BUN, LDH, uric acid (UA), CRP, IL-6, and procalcitonin (PCT), while lymphocyte, CD3+ T cell, CD4+ T cell, CD8+ T cell, and CD19+ cell counts were lower (p < 0.05).Binary logistic regression analysis showed that SHR, gender, and lymphocyte count wererisk factorsfor the severity of COVID-19. Stress hyperglycaemia, as indicated by a higher SHR, is independently associated with the severity of COVID-19.

CT Severity Score in COVID-19 Patients and its Association with Diabetes Mellitus and Hypertension: A Retrospective Study

Introduction: The Coronavirus Disease 2019 (COVID-19), caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), was first identified in Wuhan, China, in December 2019. It is thought that, people who have Diabetes Mellitus (DM) and Hypertension (HTN) are more likely to get a severe COVID19 infection. High-resolution Chest Computed Tomography (HRCT) has been shown to provide immediate results with high sensitivity and specificity for determining the severity of COVID19 infection and lung involvement. Aim: To determine the association between chest CT Severity Scores (CTSS) and DM and HTN in COVID-19 patients. Materials and Methods: This retrospective observational study was conducted in the Department of Radiodiagnosis at, Gajra Raja Medical College, Gwalior, Madhya Pradesh, India. The duration of the study was 1 month, from July 2020 to August 2020. Based on the degree of lung involvement seen on HRCT chest scans, A total of 100 patients (68 males and 32 females) with COVID-19 infection were given a quantitative CTSS. The patients were divided into groups with mild, moderate, and severe lung involvement based on the CTSS. The Chi-square test was used to assess the relationship between DM, HTN, and CTSS. The data was analysed using Statistical Package for Social Sciences (SPSS) version 17.0. Results: The mean age of study participants was 45.7±15.95 years. A total of 72 (72%) of the participants were of normal weight, 8 (8%) were overweight or obese, and 20 (20%) were underweight. COVID19 patients with a co-diagnosis of DM (61.9%) or HTN (69.2%) had more severe lung involvement than COVID-19 patients without DM (19%) or HTN (21%). DM and HTN were found to be significantly associated with severe lung involvement (p-value&lt;0.01). Conclusion: Diabetic and hypertensive patients are more likely than non diabetic and non hypertensive patients to develop the severe form of COVID-19 and have a higher CT lung involvement score. DM and HTN should be considered as risk factors for the severity of COVID-19 disease.

Beta blockers may be protective in COVID-19; findings of a study to develop an interpretable machine learning model to assess COVID-19 disease severity in light of clinical findings, medication history, and patient comorbidities

The coronavirus disease 2019 (COVID-19) has overwhelmed healthcare systems and continues to pose a significant threat worldwide. Predicting disease severity would enhance treatment provision and resource allocation. Although multiple studies were conducted to assess COVID-19's severity using machine learning (ML) models, few studies focus on patient medication history and comorbidities. In this study, ML algorithms were trained using a comprehensive dataset comprising medication history, comorbidities, and clinical findings. Patient data was gathered from King Fahad University Hospital (KFUH) in Saudi Arabia (IRB#: 2021-05-480). The dataset comprised 622 positive COVID-19 with 49 features. Three experiments were conducted to train four ML algorithms, including random forest (RF), gradient boosting machine (GMB), extreme gradient boost (XGBoost), and extra trees (ET). Findings revealed that GBM outperformed other models with 96.30% accuracy, 95.80% precision, 97.64% recall, and 96.69% F-score, with 23 features. Moreover, the permutation feature importance technique suggested that the five most influential features for forecasting disease severity were “CRP level”, “CO2 level”, “SrCr”, “Tocilizumab”, and “Age”. In addition, the shapley additive explanation (SHAP) recommended that the “D-Dimer level”, “CrCl”, and “Hypertension” were also influential. The development of an effective GBM model has the potential to aid medical specialists in the assessment of disease severity. While several models take into account patient presentation and laboratory findings, this study is unique in its scope, considering a far more comprehensive patient profile. The developed model was able to accurately predict features that have been clinically shown to correlate with disease severity. Of interest the model was able to identify a pattern of association between the use of certain medications such and disease severity. We report that the use of beta blockers may be associated with reduced severity, whereas the use of immune modulating drugs namely tocilizumab appeared to be associated with poor disease outcomes in this patient population.

Multifaceted COVID-19 Associated Coagulopathy

The pathophysiology behind Coronavirus Disease-2019 (COVID-19) has remained blur even after more than two years of onset of the pandemic. Apart from pulmonary parenchymal involvement, widespread vascular thrombosis affecting both pulmonary and extra-pulmonary systems has also been seen to contribute to COVID-19 associated morbidity. This vascular manifestation often remains undiagnosed due to non specific and varied symptoms that range from asymptomatic detection to life threatening presentations. A series of six COVID-19 positive (three male and three female) cases who presented with thrombosis of pulmonary, coronary and cerebral vessels despite being on thromboprophylaxis are reported herein. The age of patients ranged from 32 to 80 years. Out of six patients, three had comorbidities. The most common complication was Pulmonary Thromboembolism (PTE, n=4) followed by Myocardial Infarction (MI, n=1) and cerebellar infarct (n=1). Out of three patients with PTE, one patient had concurrent Deep Vein Thrombosis (DVT). All patients were managed as per guidelines issued by the Ministry of Health and Family Welfare for severe COVID-19 disease. Out of six patients, three patients died and three were discharged. The series highlights the need for high index of suspicion on the part of the treating physician that could aid in early detection and successful management of this potentially fatal condition.

Vaccine-based clinical protection against SARS-CoV-2 infection and the humoral immune response: A 1-year follow-up study of patients with multiple sclerosis receiving ocrelizumab.

Given the varying severity of coronavirus disease 2019 (COVID-19) and the rapid spread of Severe-Acute-Respiratory-Syndrome-Corona-Virus-2 (SARS-CoV-2), vaccine-mediated protection of particularly vulnerable individuals has gained increasing attention during the course of the pandemic. We performed a 1-year follow-up study of 51 ocrelizumab-treated patients with multiple sclerosis (OCR-pwMS) who received COVID-19 vaccination in 2021. We retrospectively identified 37 additional OCR-pwMS, 42 pwMS receiving natalizumab, 27 pwMS receiving sphingosine 1-phosphate receptor modulators, 59 pwMS without a disease-modifying therapy, and 61 controls without MS (HC). In OCR-pwMS, anti-SARS-CoV-2(S)-antibody titers were measured prior to the first and after the second, third, and fourth vaccine doses (pv2/3/4). The SARS-CoV-2-specific T cell response was analyzed pv2. SARS-CoV-2 infection status, COVID-19 disease severity, and vaccination-related adverse events were assessed in all pwMS and HC. We found a pronounced and increasing anti-SARS-CoV-2(S)-antibody response after COVID-19 booster vaccinations in OCR-pwMS (pv2: 30.4%, pv3: 56.5%, and pv4 90.0% were antibody positive). More than one third of OCR-pwMS without detectable antibodies pv2 developed positive antibodies pv3. 23.5% of OCR-pwMS had a confirmed SARS-CoV-2 infection, of which 84.2% were symptomatic. Infection rates were comparable between OCR-pwMS and control groups. None of the pwMS had severe COVID-19. An attenuated humoral immune response was not associated with a higher risk of SARS-CoV-2 infection. Additional COVID-19 vaccinations can boost the humoral immune response in OCR-pwMS and improve clinical protection against COVID-19. Vaccines effectively protect even OCR-pwMS without a detectable COVID-19 specific humoral immune response, indicating compensatory, e.g., T cell-mediated immunological mechanisms.

Delirium in hospitalized COVID-19 patients: Predictors and implications for patient outcome.

Delirium is recognized as a severe complication of coronavirus-disease-2019 (COVID-19). COVID-19-associated delirium has been linked to worse patient outcomes and is considered to be of multifactorial origin. Here we sought to evaluate the incidence and risk factors of delirium in hospitalized COVID-19 patients, along with its impact on clinical outcome. Consecutive adult COVID-19 patients admitted to a tertiary academic referral hospital between March 1st and December 31st, 2020 were included. Potential risk factors for delirium were evaluated, including: age, gender, disease severity (as per the highest WHO grading reached during admission), laboratory parameters for infection and renal function (as per their most extreme values), and presence of comorbidities. To assess the relative strength of risk factors for predicting the occurrence of delirium, we performed a random-forest survival analysis. 347 patients with positive COVID-19 PCR test and median age 68.2 [IQR 55.5, 80.5] years were included. Of those, 79 patients (22.8%) developed delirium, 81 (23.3%) were transferred to ICU, 58 (16.7%) died. 163 (73.8%) patients were discharged home, 13 (5.9%) to another hospital, 32 (14.5%) to nursing homes, 13 (5.9%) to rehabilitation with an overall median admission-to-discharge time of 53 [IQR 14, 195] days. The strongest predictors for the occurrence of delirium were blood urea nitrogen (minimal depth value (MD): 3.33), age (MD: 3.75), disease severity (as captured by WHO grading; MD: 3.93), leukocyte count (MD: 4.22), the presence of a neurodegenerative history (MD: 4.43), ferritin (MD: 4.46) and creatinine (MD: 4.59) levels. The risk of delirium in COVID-19 can be stratified based on COVID-19 disease severity and-similar to delirium associated with other respiratory infections-the factors advanced age, neurodegenerative disease history, and presence of elevated infection and renal-retention parameters. Screening for these risk factors may facilitate early identification of patients at high-risk for COVID-19-associated delirium.

306. Development a Predictive Score for Severe Coronavirus Disease 2019 (COVID-19) from High Risk Factor of Patient Described by Thai Government Policy

Abstract Background Thai government had a policy defined population groups that are at risk of severe COVID-19 infection. It is called “608 group” consisting of age more than 60 years old, obesity, diabetes mellitus, cancer, cerebrovascular disease, respiratory disease, chronic kidney disease, HIV infection, and pregnancy. But no study has evaluated performance of this policy. We aimed to develop parameter risk-based scoring system from Thai policy for diagnosis of severe COVID-19 infection. Methods A study was carried out in 11,677 patients with confirmed COVID-19 infection were admitted to Hatyai hospital, Songkhla, Thailand from 1 April 2021 to 31 December 2021. Patients were categorized to severe COVID-19 infection if their oxygen saturation less than 94% or need oxygen supplement. Multivariable logistic regression was used to explore for predictors. The logistic coefficients were transformed to risk-based scoring system. Results A total of 11,677 patients were included in analysis and predictive model development, 1036 (8.88%) patients were severe COVID-19 infection, and 10,631 (91.12%) patients were non-severe COVID-19 infection. Age more than 60 years old, obesity, diabetes, cancer, cerebrovascular disease, respiratory disease, chronic kidney disease, HIV infection, and pregnancy were used for derivation of the scoring system. The score-based model showed area under ROC of 0.81 (95%CI 0.79 – 0.82). The scoring system ranged from 0 to 40 was classified into 3 subcategories for clinical practicability. The sensitivity and specificity for predictive of severe COVID-19 were 81.18% and 69.83% for low risk patient, 70.56% and 80.79% in moderate risk patient, and 54.92% and 89.81% in high risk patient. Conclusion This simplified risk-based scoring system for prediction severe COVID-19 disease could aid general physicians or internist in evaluation and triage of patients who present with COVID-19 infection and help physicians in management and prioritization of patients in outbreak situation. Disclosures All Authors: No reported disclosures.

The role of serum ferritin level and disease severity in COVID-19 with type 2 diabetes mellitus patients

Introduction: The disease progression of coronavirus disease 2019 (COVID-19) in individuals with comorbidities, such as type 2 diabetes mellitus (T2DM) in particular, has been associated with the occurrence of the cytokine storm. Ferritin, an acute-phase protein indicating inflammation, has been linked to T2DM and the severity of COVID-19. Our study aimed to investigate the association between the level of ferritin and the severity of COVID-19 in T2DM patients. Methods: A cross-sectional study was conducted among COVID-19 patients admitted at Dr. Soetomo General Hospital, Surabaya, from April to September 2020. The patients who met the inclusion criteria were enrolled in the study. The data used in this study was secondary data obtained from the medical records at Dr. Soetomo General Hospital, which consisted of serum ferritin levels, the severity of COVID-19, the results of blood analysis, and other demographic and clinical characteristics (age, gender, hypertension, the number of complaints, and vital signs). Data analysis was performed using SPSS software and presented in percentage (%), mean ± standard deviation (SD), or median (min-max). A chi-square test was carried out to identify the association between serum ferritin level and the severity of COVID-19 in T2DM patients at α=0.05. Results: Of the total 159 patients were included and 80.8% of them had moderate severity of COVID-19, whereas the rest (19.5%) had severe COVID-19. Out of total patients, 78.6% had ferritin levels of ≥400 mg/dL, suggesting hyperferritinemia syndrome (mean ± SD: 1177.21 ± 1275.90 mg/dL). The Chi-squared analysis revealed a significant association between serum ferritin levels with the severity of COVID-19 in T2DM patients (p=0.024). Conclusion: There was a significant relationship between serum ferritin levels and the severity of COVID-19 in T2DM patients and further study with a bigger sample size is needed to confirm this finding.

On the Centennial of Vitamin D—Vitamin D, Inflammation, and Autoimmune Thyroiditis: A Web of Links and Implications

The 100th anniversary of the discovery of vitamin D3 (VitD3) coincides with significant recent advances in understanding its mechanism of action along with accumulating knowledge concerning its genomic and nongenomic activities. A close relationship between VitD3 and the immune system, including both types of immunity, innate and adaptive, has been newly identified, while low levels of VitD3 have been implicated in the development of autoimmune thyroiditis (AIT). Active 1,25(OH)2 D3 is generated in immune cells via 1-α-hydroxylase, subsequently interacting with the VitD3 receptor to promote transcriptional and epigenomic responses in the same or adjacent cells. Despite considerable progress in deciphering the role of VitD3 in autoimmunity, its exact pathogenetic involvement remains to be elucidated. Finally, in the era of coronavirus disease 2019 (COVID-19), brief mention is made of the possible links between VitD3 deficiency and risks for severe COVID-19 disease. This review aims to commemorate the centennial of the discovery of VitD3 by updating our understanding of this important nutrient and by drawing up a framework of guidance for VitD3 supplementation, while emphasizing the necessity for personalized treatment in patients with autoimmune thyroid disease. A tailored approach based on the specific mechanisms underlying VitD3 deficiency in different diseases is recommended.

Evaluation of the Relationship Between Disease Severity and Viral Cycle Threshold Value in COVID-19 Patients

Objective: There is a positive and significant relationship between severity and viral load in some viral diseases. Studies on the relationship between SARS-CoV-2 viral load at diagnosis and severity of coronavirus disease-2019 (COVID-19) have yielded conflicting results. Therefore, we aimed to evaluate the relationship between viral load and the clinical status of patients with COVID-19. Methods: Data of the patients diagnosed with COVID-19 and admitted to our center between May 01 and June 31, 2020, were retrospectively reviewed. The patients were divided into two groups according to their clinical characteristics as mild-moderate and severe. The demographic, laboratory, clinical, and radiological data were retrieved from electronic folders. Results: The entire cohort included 285 patients; 254 had a mild-moderate clinical course, and 31 had a severe course. Statistical analyses revealed that SARS-CoV-2 viral load was not associated with symptom duration and clinical status (p&gt;0.05). According to multivariate logistic regression analysis, only ferritin, C-reactive protein, and lactate dehydrogenase elevations were positively correlated with severe clinical course. (p&lt;0.05). Conclusion: We do not recommend using viral load to predict disease severity in COVID-19. We also found that only ferritin, C-reactive protein, and lactate dehydrogenase accompanied severe clinical course.

GENETIC VARIANTS AND SERUM PROFILES OF CYTOKINES IN COVID-19 SEVERITY.

Background: Patients with severe coronavirus disease 2019 (COVID-19) are at an increased risk of acute respiratory distress syndrome and mortality. This is due to the increased levels of pro-inflammatory cytokines that amplify downstream pathways that are controlled by immune regulators. Objective: This study aimed to investigate the association between cytokine genetic variants, cytokine serum levels/profiles, and disease severity in critically and noncritically ill COVID-19 patients. Methods: This cross-sectional study recruited 646 participants who tested positive for severe acute respiratory syndrome coronavirus 2 from six collection sites across the United Arab Emirates. Medical files were accessed to retrieve clinical data. Blood samples were collected from all participants. Patients were divided into two clinical groups, noncritical (n = 453) and critical (n = 193), according to World Health Organization classification guidelines for COVID-19 patients. Cytokine analyses were conducted on serum of a subset of the cohort, specifically on 426 participants (noncritical, 264; critical, 162). Candidate gene analyses of 33 cytokine-related genes (2,836 variants) were extracted from a genome-wide association study to identify genetic variants with pleiotropic effects on a specific cytokine and the severity of COVID-19 disease. Results: Age, body mass index (BMI), and pre-existing medical conditions were found to be significant risk factors that contribute to COVID-19 disease severity. After correcting for age, sex, and BMI, IP-10 ( P < 0.001), IFN ( P = 0.001), IL-6 ( P < 0.001), and CXCL-16 ( P < 0.001) serum levels were significantly higher among critical COVID-19 cases, when compared with noncritically ill patients. To investigate if the genetic variants involved in the serum cytokine levels are associated with COVID-19 severity, we studied several genes. Single nucleotide polymorphisms in IL6 (rs1554606; odd ratio (OR) G = 0.67 [0.66, 0.68]; P = 0.017), IFNG (rs2069718; OR G = 0.63 [0.62, 0.64]; P = 0.001), MIP (rs799187; OR A = 1.69 [1.66, 1.72]; P = 0.034), and CXCL16 (rs8071286; OR A = 1.42 [1.41, 1.44]; P = 0.018) were found to be associated with critically ill patients. Polymorphisms in the CXCL10 , CCL2 , IL1 , CCL7 , and TNF genes were not associated with the COVID-19 critical phenotype. The genotypes of IL-6 (gene, IL6 [7p15.3]) and CXCL-16 (gene, CXCL16 [17p13.2]) were significantly associated with the serum levels of the respective cytokine in critical cases of COVID-19. Conclusion: Data obtained from measuring cytokine levels and genetic variant analyses suggest that IL-6 and CXCL-16 could potentially be used as potential biomarkers for monitoring disease progression of COVID-19 patients. The findings in this study suggest that specific cytokine gene variants correlate with serum levels of the specific cytokine. These genetic variants could be of assistance in the early identification of high-risk patients on admission to the clinic to improve the management of COVID-19 patients and other infectious diseases.

Severe COVID-19 in pregnancy has a distinct serum profile, including greater complement activation and dysregulation of serum lipids.

Pregnancies complicated by Coronavirus Disease 2019 (COVID-19) are at an increased risk of severe morbidity due to physiologic changes in immunologic, cardiovascular, and respiratory function. There is little is known about how severity of COVID-19 changes protein and metabolite expression in pregnancy. This study aims to investigate the pathophysiology behind various clinical trajectories in pregnant patients diagnosed with COVID-19 using multi-omics profiling. This is a prospective cohort study of 30 pregnant patients at a single tertiary care center. Participants were categorized by severity of COVID-19 disease (control, asymptomatic, mild/moderate, or severe). Maternal serum samples underwent LC-MS-based multiomics analysis for profiling of proteins, lipids, electrolytes, and metabolites. Linear regression models were used to assess how disease severity related to analyte levels. Reactome pathway enrichment analysis was conducted on differential analytes. Of 30 participants, 25 had confirmed diagnosis of COVID-19 (6 asymptomatic (one post-infection), 13 mild/moderate (all post-infection), 6 severe), and 5 participants were controls. Severe COVID-19 was associated with distinct profiles demonstrating significant proteomic and lipidomic signatures which were enriched for annotations related to complement and antibody activity. (FDR < 0.05). Downregulated analytes were not significantly enriched but consisted of annotation terms related to lipoprotein activity (FDR > 0.2). Post-infection mild/moderate COVID-19 did not have significantly altered serum protein, metabolite, or lipid metabolite levels compared to controls. Pregnancies with severe COVID-19 demonstrate greater inflammation and complement activation and dysregulation of serum lipids. This altered multiomic expression provides insight into the pathophysiology of severe COVID-19 in pregnancy and may serve as potential indicators for adverse pregnancy outcomes.