Disease Severity In COVID-19 Patients Research Articles

Diagnostic and early prognostic value of serum CRP and LDH levels in patients with possible COVID-19 at the first admission.

COVID-19 is the infection caused by the new coronavirus. Specific treatment for COVID-19 has not been established, yet. It is important to determine the disease severity of the patients at the first admission. Therefore, the exploration of biomarkers is deemed necessary. We aimed to assess the diagnostic and early prognostic value of CRP and LDH levels in possible COVID-19 patients presenting with a severe clinical picture. We evaluated the correlations of relevant routine laboratory test results with disease severity in COVID-19 patients admitted to our infectious diseases clinic. Patients were divided into severe and non-severe disease groups based on clinical findings, oxygen saturation levels in the arterial blood, biochemical test results, and radiological findings. Differences in the findings between the two disease severity groups were examined to determine potential biomarkers. Median age and the CRP and LDH levels in the severe disease group were statistically significantly higher compared to the nonsevere group (p < 0.0001). No other parameters statistically significant differences have been observed between the two groups (P > 0.05). CRP and LDH levels were positively correlated with lung lesions in early-stage COVID-19, potentially reflecting disease severity. Because LDH and CRP levels can potentially reflect the pulmonary function, they can be potential predictors of COVID-19- related respiratory failure. For avoiding poor prognosis; LDH and CRP should be considered as potential predictors for identifying the need for thoracic CT scans, close monitoring of pulmonary function, and aggressive supportive therapy early in the course of COVID-19.

Innate Immune Response to SARS-CoV-2 Infection: From Cells to Soluble Mediators.

The vulnerability of humankind to SARS-CoV-2 in the absence of a pre-existing immunity, the unpredictability of the infection outcome, and the high transmissibility, broad tissue tropism, and ability to exploit and subvert the immune response pose a major challenge and are likely perpetuating the COVID-19 pandemic. Nevertheless, this peculiar infectious scenario provides researchers with a unique opportunity for studying, with the latest immunological techniques and understandings, the immune response in SARS-CoV-2 naïve versus recovered subjects as well as in SARS-CoV-2 vaccinees. Interestingly, the current understanding of COVID-19 indicates that the combined action of innate immune cells, cytokines, and chemokines fine-tunes the outcome of SARS-CoV-2 infection and the related immunopathogenesis. Indeed, the emerging picture clearly shows that the excessive inflammatory response against this virus is among the main causes of disease severity in COVID-19 patients. In this review, the innate immune response to SARS-CoV-2 infection is described not only in light of its capacity to influence the adaptive immune response towards a protective phenotype but also with the intent to point out the multiple strategies exploited by SARS-CoV-2 to antagonize host antiviral response and, finally, to outline inborn errors predisposing individuals to COVID-19 disease severity.

Viral load and disease severity in COVID-19.

The relationship between COVID-19 severity and viral load is unknown. Our objective was to assess the association between viral load and disease severity in COVID-19. In this single center observational study of adults with laboratory confirmed SARS-CoV-2, the first positive in-hospital nasopharyngeal swab was used to calculate the log10 copies/ml [log10 copy number (CN)] of SARS-CoV-2. Four categories based on level of care and modified sequential organ failure assessment score (mSOFA) at time of swab were determined. Median log10CN was compared between different levels of care and mSOFA quartiles. Median log10CN was compared in patients who did and did not receive influenza vaccine, and the correlation between log10CN and D-dimer was examined. We found that of 396 patients, 54.3% were male, and 25% had no major comorbidity. Hospital mortality was 15.7%. Median mSOFA was 2 (IQR 0–3). Median log10CN was 5.5 (IQR 3.3–8.0). Median log10CN was highest in non-intubated ICU patients [6.4 (IQR 4.4–8.1)] and lowest in intubated ICU patients [3.6 (IQR 2.6–6.9)] (p value < 0.01). In adjusted analyses, this difference remained significant [mean difference 1.16 (95% CI 0.18–2.14)]. There was no significant difference in log10CN between other groups in the remaining pairwise comparisons. There was no association between median log10CN and mSOFA in either unadjusted or adjusted analyses or between median log10CN in patients with and without influenza immunization. There was no correlation between log10CN and D-dimer. We conclude, in our cohort, we did not find a clear association between viral load and disease severity in COVID-19 patients. Though viral load was higher in non-intubated ICU patients than in intubated ICU patients there were no other significant differences in viral load by disease severity.Supplementary InformationThe online version contains supplementary material available at 10.1007/s11739-021-02786-w.

Autoantibodies against ACE2 and angiotensin type-1 receptors increase severity of COVID-19

The renin-angiotensin system (RAS) plays a major role in COVID-19. Severity of several inflammation-related diseases has been associated with autoantibodies against RAS, particularly agonistic autoantibodies for angiotensin type-1 receptors (AA-AT1) and autoantibodies against ACE2 (AA-ACE2). Disease severity of COVID-19 patients was defined as mild, moderate or severe following the WHO Clinical Progression Scale and determined at medical discharge. Serum AA-AT1 and AA-ACE2 were measured in COVID-19 patients (n = 119) and non-infected controls (n = 23) using specific solid-phase, sandwich enzyme-linked immunosorbent assays. Serum LIGHT (TNFSF14; tumor necrosis factor ligand superfamily member 14) levels were measured with the corresponding assay kit. At diagnosis, AA-AT1 and AA-ACE2 levels were significantly higher in the COVID-19 group relative to controls, and we observed significant association between disease outcome and serum AA-AT1 and AA-ACE2 levels. Mild disease patients had significantly lower levels of AA-AT1 (p < 0.01) and AA-ACE2 (p < 0.001) than moderate and severe patients. No significant differences were detected between males and females. The increase in autoantibodies was not related to comorbidities potentially affecting COVID-19 severity. There was significant positive correlation between serum levels of AA-AT1 and LIGHT (TNFSF14; rPearson = 0.70, p < 0.001). Both AA-AT1 (by agonistic stimulation of AT1 receptors) and AA-ACE2 (by reducing conversion of Angiotensin II into Angiotensin 1-7) may lead to increase in AT1 receptor activity, enhance proinflammatory responses and severity of COVID-19 outcome. Patients with high levels of autoantibodies require more cautious control after diagnosis. Additionally, the results encourage further studies on the possible protective treatment with AT1 receptor blockers in COVID-19.

A single transcript for the prognosis of disease severity in COVID-19 patients

With many countries strapped for medical resources due to the COVID-19 pandemic, it is highly desirable to allocate the precious resources to those who need them the most. Several markers have been found to be associated with the disease severity in COVID-19 patients. However, the established markers only display modest prognostic power individually and better markers are urgently needed. The aim of this study is to investigate the potential of S100A12, a prominent marker gene for bacterial infection, in the prognosis of disease severity in COVID-19 patients. To ensure the robustness of the association, a total of 1695 samples from 14 independent transcriptome datasets on sepsis, influenza infection and COVID-19 infection were examined. First, it was demonstrated that S100A12 was a marker for sepsis and severity of sepsis. Then, S100A12 was found to be a marker for severe influenza infection, and there was an upward trend of S100A12 expression as the severity level of influenza infection increased. As for COVID-19 infection, it was found that S100A12 expression was elevated in patients with severe and critical COVID-19 infection. More importantly, S100A12 expression at hospital admission was robustly correlated with future quantitative indexes of disease severity and outcome in COVID-19 patients, superior to established prognostic markers including CRP, PCT, d-dimer, ferritin, LDH and fibrinogen. Thus, S100A12 is a valuable novel prognostic marker for COVID-19 severity and deserves more attention.

Immune characterization and profiles of SARS-CoV-2 infected patients reveals potential host therapeutic targets and SARS-CoV-2 oncogenesis mechanism

The spread of SARS-CoV-2 and the increasing mortality rates of COVID-19 create an urgent need for treatments, which are currently lacking. Although vaccines have been approved by the FDA for emergency use in the U.S., patients will continue to require pharmacologic intervention to reduce morbidity and mortality as vaccine availability remains limited. The rise of new variants makes the development of therapeutic strategies even more crucial to combat the current pandemic and future outbreaks. Evidence from several studies suggests the host immune response to SARS-CoV-2 infection plays a critical role in disease pathogenesis. Consequently, host immune factors are becoming more recognized as potential biomarkers and therapeutic targets for COVID-19. To develop therapeutic strategies to combat current and future coronavirus outbreaks, understanding how the coronavirus hijacks the host immune system during and after the infection is crucial. In this study, we investigated immunological patterns or characteristics of the host immune response to SARS-CoV-2 infection that may contribute to the disease severity of COVID-19 patients. We analyzed large bulk RNASeq and single cell RNAseq data from COVID-19 patient samples to immunoprofile differentially expressed gene sets and analyzed pathways to identify human host protein targets. We observed an immunological profile of severe COVID-19 patients characterized by upregulated cytokines, interferon-induced proteins, and pronounced T cell lymphopenia, supporting findings by previous studies. We identified a number of host immune targets including PERK, PKR, TNF, NF-kB, and other key genes that modulate the significant pathways and genes identified in COVID-19 patients. Finally, we identified genes modulated by COVID-19 infection that are implicated in oncogenesis, including E2F transcription factors and RB1, suggesting a mechanism by which SARS-CoV-2 infection may contribute to oncogenesis. Further clinical investigation of these targets may lead to bonafide therapeutic strategies to treat the current COVID-19 pandemic and protect against future outbreaks and viral escape variants.

A variant in TMPRSS2 is associated with decreased disease severity in COVID-19

BackgroundMortality due to COVID-19 caused by SARS-CoV-2 infection varies among populations. Functional relevance of genetic variations in Angiotensin-converting enzyme 2 (ACE2) and Transmembrane serine protease 2 (TMPRSS2), two crucial host factors for viral entry, might explain some of this variation. MethodsIn this comparative study in Indian subjects, we recruited 510 COVID-19 patients and retrieved DNA from 520 controls from a repository. Associations between variants in ACE2 and TMPRSS2 with disease severity were identified by whole exome sequencing (WES, n = 20) and targeted genotyping (n = 1010). Molecular dynamic simulations (MDS) were performed to explore functional relevance of the variants. Cleavage of spike glycoprotein by wild and variant TMPRSS2 was determined in HEK293T cells. Potential effects of confounders on the association between genotype and disease severity were tested (Mantel-Haenszel test). ResultsWES identified deleterious variant in TMPRSS2 (rs12329760, G > A, p. V160M). The minor allele frequency (MAF) was 0·27 in controls, 0·31 in asymptomatic, 0·21 in mild-to-moderately affected and 0·19 in severely affected COVID-19 patients. Risk of severity increased with decreasing MAF: Asymptomatic: Odds ratio-0·69 (95% CI–0·52–0·93; p = 0·01); mild-to-moderate: Odds ratio-1·89 (95% CI–1·22–2.92;p = 0·004) and severe: Odds ratio-1·79 (95% CI–1·11–2.88;p = 0·01). No confounding effect of diabetes and hypertension were observed on the risk of developing severe COVID-19 disease with respect to genotype. MDS revealed decreased stability of TMPRSS2 with 160 M variant. Spike glycoprotein cleavage by TMPRSS2 reduced ~2·4-fold in cells expressing 160 M variant. ConclusionWe demonstrate association of TMPRSS2 variant rs12329760 with decreased disease severity in COVID-19 patients from India.

Evaluation of hematological parameters as an indicator of disease severity in Covid-19 patients: Pakistan's experience.

BackgroundThe severity of COVID‐19 could be evaluated by examining several blood parameters mainly white blood cell (WBC) count, granulocytes, platelet, and novel hemocytometric markers neutrophils to lymphocyte ratio (NLR), platelet‐to‐lymphocyte (PLR), and lymphocyte to monocyte ratio (LMR). The current study was conducted to investigate alteration in blood parameters and their association with the severity and mortality of COVID‐19 patients.MethodologyAn observational cross‐sectional study was conducted retrospectively, a total of 101 COVID‐19 positive patients were examined: 52 were mild, 24 were moderate, 09 were severe, and 16 were critically diseased patients. We also recorded 16 deaths associated with the critical group. The overall mean age observed in our study was 48.94 years, where the mean age for critical individuals was 62.12 ± 14.35 years.ResultsA significant association between the disease severity and elevation in blood parameters were observed. The WBC's and granulocyte count were significantly increased (p value <0.001) while the mean platelet count (165.0 × 109/L) and red blood cell volume distribution width (RDW) were decreased in the critical group (57.86%) compared to mild group's patients (177.3%) (p = 0.83). The lymphocytes count was decreased in critical patients (1.40 × 109/L) compared to mild patients (1.92 × 109/L) (p = 0.28). A significant association was observed in platelet‐lymphocyte ratio (p < 0.001), Neutrophil‐Lymphocyte ratio (p = <0.001), and Lymphocyte‐Monocyte ratio (0.011).ConclusionThese blood parameters could be used as a suitable biomarker for the prognosis and severity of COVID‐19. Evaluating novel hemograms NLR, PLR, and LMR can aid clinicians to identify potentially severe cases at early stages, initiate effective management in time, and conduct early triage which may reduce the overall mortality of COVID‐19 patients.

Automated quantitative thin slice volumetric low dose CT analysis predicts disease severity in COVID-19 patients

PurposeThis study aimed to identify predictive (bio-)markers for COVID-19 severity derived from automated quantitative thin slice low dose volumetric CT analysis, clinical chemistry and lung function testing. MethodsSeventy-four COVID-19 patients admitted between March 16th and June 3rd 2020 to the Asklepios Lung Clinic Munich-Gauting, Germany, were included in the study. Patients were categorized in a non-severe group including patients hospitalized on general wards only and in a severe group including patients requiring intensive care treatment. Fully automated quantification of CT scans was performed via IMBIO CT Lung Texture analysis™ software. Predictive biomarkers were assessed with receiver-operator-curve and likelihood analysis. ResultsFifty-five patients (44% female) presented with non-severe COVID-19 and 19 patients (32% female) with severe disease. Five fatalities were reported in the severe group. Accurate automated CT analysis was possible with 61 CTs (82%). Disease severity was linked to lower residual normal lung (72.5% vs 87%, p = 0.003), increased ground glass opacities (GGO) (8% vs 5%, p = 0.031) and increased reticular pattern (8% vs 2%, p = 0.025). Disease severity was associated with advanced age (76 vs 59 years, p = 0.001) and elevated serum C-reactive protein (CRP, 92.2 vs 36.3 mg/L, p < 0.001), lactate dehydrogenase (LDH, 485 vs 268 IU/L, p < 0.001) and oxygen supplementation (p < 0.001) upon admission. Predictive risk factors for the development of severe COVID-19 were oxygen supplementation, LDH >313 IU/L, CRP >71 mg/L, <70% normal lung texture, >12.5% GGO and >4.5% reticular pattern. ConclusionAutomated low dose CT analysis upon admission might be a useful tool to predict COVID-19 severity in patients.

Does higher body mass index increase COVID-19 severity? A systematic review and meta-analysis.

IntroductionObesity and higher BMI is one of the leading comorbidities to increase the risk of COVID-19 severity. This paper presents a systematic review and meta-analysis estimating the effects of overweight and obesity on COVID-19 disease severity.MethodTwo electronic databases (Medline and Cochrane library) and one grey literature database (Grey Literature Report) were searched. The risks of bias of the selected studies were assessed by using the Navigation Guide method for human data. Both random and fixed effect meta-analyses were determined using Review Manager (RevMan) software version 5.4.ResultsAfter initial screening, 12 studies were fulfilled the eligibility criteria, comprising a total of 405359 patients, and included in the systematic review. The pooled risk of COVID-19 severity was 1.31 times higher based on both fixed and random effect model among those overweight patients, I2 0% and 2.09 and 2.41 times higher based on fixed and random effect respectively among obese patients, I2 42% compared to healthy individuals.ConclusionOverweight and obesity are found to be risk factors for disease severity of COVID-19 patients. However, further assessment of metabolic parameters is required to estimate the risk factors of COVID-19 patients and understanding the mechanism between COVID-19 and body mass index.

Immune Profile in Patients With COVID-19: Lymphocytes Exhaustion Markers in Relationship to Clinical Outcome.

The velocity of the COVID-19 pandemic spread and the variable severity of the disease course has forced scientists to search for potential predictors of the disease outcome. We examined various immune parameters including the markers of immune cells exhaustion and activation in 21 patients with COVID-19 disease hospitalised in our hospital during the first wave of the COVID-19 pandemic in Slovakia. The results showed significant progressive lymphopenia and depletion of lymphocyte subsets (CD3+, CD4+, CD8+ and CD19+) in correlation to the disease severity. Clinical recovery was associated with significant increase in CD3+ and CD3+CD4+ T-cells. Most of our patients had eosinopenia on admission, although no significant differences were seen among groups with different disease severity. Non-survivors, when compared to survivors, had significantly increased expression of PD-1 on CD4+ and CD8+ cells, but no significant difference in Tim-3 expression was observed, what suggests possible reversibility of immune paralysis in the most severe group of patients. During recovery, the expression of Tim-3 on both CD3+CD4+ and CD3+CD8+ cells significantly decreased. Moreover, patients with fatal outcome had significantly higher proportion of CD38+CD8+ cells and lower proportion of CD38+HLA-DR+CD8+ cells on admission. Clinical recovery was associated with significant decrease of proportion of CD38+CD8+ cells. The highest AUC values within univariate and multivariate logistic regression were achieved for expression of CD38 on CD8+ cells and expression of PD1 on CD4+ cells alone or combined, what suggests, that these parameters could be used as potential biomarkers of poor outcome. The assessment of immune markers could help in predicting outcome and disease severity in COVID-19 patients. Our observations suggest, that apart from the degree of depletion of total lymphocytes and lymphocytes subsets, increased expression of CD38 on CD3+CD8+ cells alone or combined with increased expression of PD-1 on CD3+CD4+ cells, should be regarded as a risk factor of an unfavourable outcome in COVID-19 patients. Increased expression of PD-1 in the absence of an increased expression of Tim-3 on CD3+CD4+ and CD3+CD8+ cells suggests potential reversibility of ongoing immune paralysis in patients with the most severe course of COVID-19.

A randomized clinical trial evaluating the immunomodulatory effect of convalescent plasma on COVID-19-related cytokine storm.

Evaluating the effect of convalescent plasma (CP) on some cytokine storm indices in severe COVID-19 patients. Totally, 62 patients were randomly assigned into two groups for this clinical trial. Patients in the intervention group received one unit (500 mL) plasma on the admission day plus standard drugs while the controls merely received standard treatments. Eventually, primary and secondary outcomes were evaluated. In the CP group, compared with controls, the mean levels of lymphocytes and IL-10 significantly increased while the levels of IL-6, TNF-α, and IFN-γ decreased (p < 0.05). The length of in-hospital stay, and mortality rate did not significantly reduce in the CP group compared with controls (p > 0.05) while WHO severity scores remarkably improved (p = 0.01), despite the higher frequency of underlying diseases among the CP group (66.7%) vs. controls (33.3%). Although CP has a remarkable immunomodulatory and antiviral potential to improve the cytokine storm and disease severity in COVID-19 patients, it did not considerably affect the mortality rate.Supplementary InformationThe online version contains supplementary material available at 10.1007/s11739-021-02734-8.

Association between comorbidities and disease severity in COVID-19 patients of an infectious diseases hospital in Russia

The aim of the study was to investigate the association between the severity of COVID-19 and various comorbidities in hospitalized patients. For this reason, patient histories of 500 patients who were hospitalized in the infectious disease hospital (Moscow, Russia) during the coronavirus pandemic were analyzed. The results showed that cardiovascular and blood diseases, diabetes mellitus, diseases of the central nervous system + psychiatric disorders, and diseases of the urogenital system were all found to be associated with a more severe disease course (X2 = 44.404; p &lt;0.001; X2 = 55.395; p &lt;0.001; X2 = 19.974; p &lt;0.001; X2 = 11.723; p =0.003, respectively), while diseases of the digestive system and liver (including viral hepatitis), HIV infection, and diseases of the respiratory system + ENT organs where not found to be associated with severity of COVID-19 (X2 = 6.949; p =0.031; X2 =1.582; p =0.453; X2 = 0.528; p =0.768, respectively). There was also found no association between pregnancy and severity of COVID-19 (X2 = 0.705; p =0.703). The authors concluded that persons who are known to have comorbidities should take extra precautions to avoid getting infected with SARS-COV-2 since they may be at a higher risk of having a severe disease course if they get sick.

Comparing the Value of Cystatin C and Serum Creatinine for Evaluating the Renal Function and Predicting the Prognosis of COVID-19 Patients.

Background: Coronavirus disease- (COVID-19-) related renal function abnormality is associated with poor prognosis. However, the clinical significance of dynamic changes in renal function indicators has not been studied, and no studies have evaluated the renal function in COVID-19 patients by cystatin C. Objective: This study aimed to evaluate the effect of abnormal renal function on admission on prognosis of COVID-19 patients and the prognostic value of various renal function indicators. Methods: A total of 1,764 COVID-19 patients without a history of chronic kidney disease were categorized into two groups, an elevated cystatin C group and a normal cystatin C group, based on the results of renal function tests on admission. The clinical characteristics were compared between the two groups, and logistic or Cox regression analyses were performed to explore the associations between elevated cystatin C/serum creatinine levels and disease severity and survival. We also performed receiver operating characteristic (ROC) curve, Kaplan–Meier survival, and curve fitting analyses. Results: When adjusted for several significant clinical variables, elevated cystatin C levels on admission were independent predictors of disease severity (p < 0.001), and elevated creatinine levels were independent predictors of death (p = 0.020). Additionally, the ROC curve analysis shows that elevated cystatin C levels [area under the curve (AUC): 0.656] have a better predictive value for disease severity than elevated creatinine levels (AUC: 0.540). The survival curves of patients with elevated cystatin C/creatinine levels show a sharper decline than those of patients with normal cystatin C/creatinine levels (p < 0.001). The curve fitting analysis revealed that, compared to the flat curves of cystatin C and creatinine levels for patients who survived, the curves for patients who died kept rising, and cystatin C levels rose above the normal range earlier than creatinine. Conclusions: Elevated cystatin C, which occurs earlier than serum creatinine, is useful for the early detection of renal function abnormality and might have better predictive value for disease severity in COVID-19 patients, while elevated serum creatinine may have a better predictive value for risks of death.

Role of vitamin D in treating COVID-19-associated coagulopathy: problems and perspectives.

Aggressive inflammatory response leading to hypercoagulability has been found to be associated with disease severity in COVID-19 patients and portends bad treatment outcome. A state of acute disseminated intravascular coagulation (DIC), along with pulmonary embolism and/or deep vein thrombosis, has been observed in critically ill ICU patients. Autopsy reports of COVID-19 patients demonstrated microthrombi in lungs and in other organs, as well as marked inflammatory changes, characteristic clinicopathological features that exacerbate disease severity. Vitamin D supplementation was recommended by many clinicians across the globe to improve clinical symptoms of COVID-19 patients, mainly because of its immunomodulatory roles on immune cells. Furthermore, vitamin D and its associated molecules are also known to directly or indirectly regulate various thrombotic pathways. We propose that vitamin D supplementation not only attenuates the risk of Acute Respiratory Disease Syndrome (ARDS) but it also may have a role in reducing coagulation abnormalities in critically ill COVID-19 patients. The overarching goal of this review is to discuss the effects of vitamin D on coagulation pathways and other intertwined processes leading to thrombosis. Many clinical trials are currently investigating the efficacy of vitamin D supplementation in reducing the risk of COVID-19 infection. However, randomized placebo control clinical trials are also necessary to ascertain the effect of vitamin D supplementation on reducing the risk of coagulopathy in COVID-19 patients.

Impact of cardiovascular diseases on severity of COVID-19 patients: A systematic review

Coronavirus disease 2019 (COVID-19) cases are increasing rapidly worldwide. Similar to Middle East respiratory syndrome where cardiovascular diseases were present in nearly 30% of cases, the increased presence of cardiovascular comorbidities remains true for COVID-19 as well. The mechanism of this association remains unclear at this time. Therefore, we reviewed the available literature and tried to find the probable association between cardiovascular disease with disease severity and mortality in COVID-19 patients. We searched Medline (via PubMed) and Cochrane Central Register of Controlled Trials for articles published until Sept 5, 2020. Nineteen articles were included involving 6,872 COVID-19 patients. The random-effect meta-analysis showed that cardiovascular disease was significantly associated with severity and mortality for COVID-19: odds ratio (OR) 2.89, 95% confidence interval (CI) 1.98-4.21 for severity and OR 3.00, 95% CI 1.67-5.39 for mortality, respectively. Risk of COVID-19 severity was higher in patients having diabetes, hypertension, chronic obstructive pulmonary disease, malignancy, cerebrovascular disease and chronic kidney disease. Similarly, patients with diabetes, hypertension, chronic liver disease, cerebrovascular disease and chronic kidney disease were at higher risk of mortality. Our findings showed that cardiovascular disease has a negative effect on health status of COVID-19 patients. However, large prevalence studies demonstrating the consequences of comorbid cardiovascular disease are urgently needed to understand the extent of these concerning comorbidities.

IL-6 and IL-10 as predictors of disease severity in COVID-19 patients: results from meta-analysis and regression

AimsSARS-CoV-2, an infectious agent behind the ongoing COVID-19 pandemic, induces high levels of cytokines such as IL-1, IL-2, IL-4, IL-6, IL-10, TNF-α, IFN-γ etc in infected individuals that play a role in the underlying patho-physiology. Nonetheless, exact association and contribution of every cytokine towards COVID-19 pathology remains poorly understood. Delineation of the roles of cytokines during COVID-19 holds the key to efficient patient management in clinics. This study performed a comprehensive meta-analysis to establish association between induced cytokines and COVID-19 disease severity to help in prognosis and clinical care. Main methodsScientific literature was searched to identify 13 cytokines (IL-1β, IL-2, IL-2R, IL-4, IL-5, IL-6, IL-7, IL-8, IL-10, IL-12, IL-17, TNF-α and IFN-γ) from 18 clinical studies. Standardized mean difference (SMD) for selected 6 cytokines IL-2, IL-4, IL-6, IL-10, TNF-α and IFN-γ between severe and non-severe COVID-19 patient groups were summarized using random effects model. A classifier was built using logistic regression model with cytokines having significant SMD as covariates. Key findingsOut of the 13 cytokines, IL-6 and IL-10 showed statistically significant SMD across studies synthesized. Classifier with mean values of both IL-6 and IL-10 as covariates performed well with accuracy of ~92% that was significantly higher than accuracy reported in literature with IL-6 and IL-10 as individual covariates. SignificanceSimple panel proposed by us with only two cytokine markers can be used as predictors for fast diagnosis of patients with higher risk of COVID-19 disease deterioration and thus can be managed well for a favourable prognosis.

Gut microbiota in antiviral strategy from bats to humans: a missing link in COVID-19.

Bats are a potential natural reservoir for SARS-CoV-2 virus and other viruses detrimental to humans. Accumulated evidence has shown that, in their adaptation to a flight-based lifestyle, remodeling of the gut microbiota in bats may have contributed to immune tolerance to viruses. This evidence from bats provides profound insights into the potential influence of gut microbiota in COVID-19 disease in humans. Here, we highlight recent advances in our understanding of the mechanisms by which the gut microbiota helps bats tolerate deadly viruses, and summarize the current clinical evidence on the influence of gut microbiota on the susceptibility to SARS-CoV-2 infection and risk of COVID-19 leading to a fatal outcome. In addition, we discuss the implications of gut microbiota-targeted approaches for preventing infection and reducing disease severity in COVID-19 patients.

Determination of disease severity in COVID-19 patients using deep learning in chest X-ray images.

Chest X-ray plays a key role in diagnosis and management of COVID-19 patients and imaging features associated with clinical elements may assist with the development or validation of automated image analysis tools. We aimed to identify associations between clinical and radiographic features as well as to assess the feasibility of deep learning applied to chest X-rays in the setting of an acute COVID-19 outbreak. A retrospective study of X-rays, clinical, and laboratory data was performed from 48 SARS-CoV-2 RT-PCR positive patients (age 60±17 years, 15 women) between February 22 and March 6, 2020 from a tertiary care hospital in Milan, Italy. Sixty-five chest X-rays were reviewed by two radiologists for alveolar and interstitial opacities and classified by severity on a scale from 0 to 3. Clinical factors (age, symptoms, comorbidities) were investigated for association with opacity severity and also with placement of central line or endotracheal tube. Deep learning models were then trained for two tasks: lung segmentation and opacity detection. Imaging characteristics were compared to clinical datapoints using the unpaired student's t-test or Mann-Whitney U test. Cohen's kappa analysis was used to evaluate the concordance of deep learning to conventional radiologist interpretation. Fifty-six percent of patients presented with alveolar opacities, 73% had interstitial opacities, and 23% had normal X-rays. The presence of alveolar or interstitial opacities was statistically correlated with age (P = 0.008) and comorbidities (P = 0.005). The extent of alveolar or interstitial opacities on baseline X-ray was significantly associated with the presence of endotracheal tube (P = 0.0008 and P = 0.049) or central line (P = 0.003 and P = 0.007). In comparison to human interpretation, the deep learning model achieved a kappa concordance of 0.51 for alveolar opacities and 0.71 for interstitial opacities. Chest X-ray analysis in an acute COVID-19 outbreak showed that the severity of opacities was associated with advanced age, comorbidities, as well as acuity of care. Artificial intelligence tools based upon deep learning of COVID-19 chest X-rays are feasible in the acute outbreak setting.

EVALUATION OF THE RELATIONSHIP OF MPV, RDW AND PVI PARAMETERS WITH DISEASE SEVERITY IN COVID-19 PATIENTS.

SUMMARYCoronavirus was first detected in three severe pneumonia cases in Wuhan, China, in December 2019. Studies on red cell distribution width (RDW-CV) and mean platelet volume (MPV) laboratory parameters, which can be examined in complete blood count in COVID-19 patients, are still very limited. However, to the best of our knowledge, there are no studies examining the relationship between platelet volume index (PVI) and disease severity in COVID-19 patients, which was evaluated in this study. The aim of this study was to evaluate the relationship of disease severity in COVID-19 patients with their MPV, RDW, and PVI parameters. The study included 92 COVID-19 patients as a study group and 84 healthy individuals as control group. All laboratory data and radiological images were scanned retrospectively from patient files and hospital information system. Evaluation of the RDW-CV and MPV blood parameters, and PVI measured in COVID-19 patients yielded statistically significant differences according to the disease severity. We suggest that RDW-CV and PVI, evaluated within the scope of the study, may be the parameters that should be considered in the early diagnosis of the disease, from the initial stages of COVID-19. In addition, we think that the RDW-CV and MPV laboratory parameters, as well as PVI, which all are simple, inexpensive and widely used hematologic tests, can be used as important biomarkers in determining COVID-19 severity and mortality.