Prognostic parameters of in-hospital mortality in COVID-19 patients-An Italian experience

Cholesterol and COVID-19-therapeutic opportunities at the host/virus interface during cell entry

The rapid development of vaccines to combat severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections has been critical to reduce the severity of COVID-19. However, the continuous emergence of new SARS-CoV-2 subtypes highlights the need to develop additional approaches that oppose viral infections. Targeting host factors that support virus entry, replication, and propagation provide opportunities to lower SARS-CoV-2 infection rates and improve COVID-19 outcome. This includes cellular cholesterol, which is critical for viral spike proteins to capture the host machinery for SARS-CoV-2 cell entry. Once endocytosed, exit of SARS-CoV-2 from the late endosomal/lysosomal compartment occurs in a cholesterol-sensitive manner. In addition, effective release of new viral particles also requires cholesterol. Hence, cholesterol-lowering statins, proprotein convertase subtilisin/kexin type 9 antibodies, and ezetimibe have revealed potential to protect against COVID-19. In addition, pharmacological inhibition of cholesterol exiting late endosomes/lysosomes identified drug candidates, including antifungals, to block SARS-CoV-2 infection. This review describes the multiple roles of cholesterol at the cell surface and endolysosomes for SARS-CoV-2 entry and the potential of drugs targeting cholesterol homeostasis to reduce SARS-CoV-2 infectivity and COVID-19 disease severity.

Serum levels of soluble suppression of tumorigenicity 2 (sST2) and heart-type fatty acid binding protein (H-FABP) independently predict in-hospital mortality in geriatric patients with COVID-19

Elevation of cardiac damage biomarkers is associated with adverse clinical outcomes and increased mortality in COVID-19 patients. This study assessed the association of admission serum levels of sST2 and H-FABP with in-hospital mortality in 191 geriatric patients (median age 86 yrs., IQR 82-91 yrs.) with COVID-19 and available measures of hs-cTnT and NT-proBNP at admission. Cox proportional hazards models were utilized to predict in-hospital mortality, considering clinical/biochemical confounders as covariates. A composite cardiac score was calculated to improve predictive accuracy. Patients deceased during their hospital stay (26%) exhibited higher levels of all biomarkers, which demonstrated good discrimination for in-hospital mortality. Addition of sST2 and H-FABP significantly improved the discriminatory power of hs-cTnT and NT-proBNP. The composite cardiac score (AUC=0.866) further enhanced the predictive accuracy. Crude and adjusted Cox regressions models revealed that both sST2 and H-FABP were independently associated with in-hospital mortality (HR for sST2 ≥129 ng/mL, 4.32 [1.48-12.59]; HR for H-FABP ≥18 ng/mL, 7.70 [2.12-28.01]). The composite cardiac score also independently correlated with in-hospital mortality (HR for 1-unit increase, 1.47 [1.14-1.90]). In older patients with COVID-19, sST2 and H-FABP demonstrated prognostic value, improving the predictive accuracy of the routinely assessed biomarkers hs-cTnT and NT-proBNP.

Hospital Admission Factors Independently Affecting the Risk of Mortality of COVID-19 Patients

INTRODUCTION

COVID-19 is a disease characterized by high in-hospital mortality, which seems to be dependent on many predisposing factors.

OBJECTIVES

The aim of this study was to analyze the clinical symptoms, abnormalities in the results of laboratory tests, and coexisting chronic diseases that independently affected the risk of in-hospital mortality in patients with COVID-19.

PATIENTS AND METHODS

We analyzed the records of patients with COVID-19 who were hospitalized from 6 March 2020 to 30 November 2021.

RESULTS

Out of the entire group of 2138 patients who were analyzed, 12.82% died during hospitalization. In-hospital mortality was independently associated with older age (OR 1.53, 95% CI 1.20-1.97); lower arterial blood oxygen saturation (OR 0.95, 95% CI 0.92-0.99); the presence of a neoplasm (OR 4.45, 95% CI 2.01-9.62), a stomach ulcer (OR 3.35, 95% CI 0.94-11.31), and dementia (OR 3.40, 95% CI 1.36-8.26); a higher score on the SOFA scale (OR 1.73, 95% CI 1.52-1.99); higher lactate dehydrogenase (LDH) (OR 1.08, 95% CI 1.05-1.12); higher N-terminal pro-brain natriuretic peptide (NT pro BNP) (OR 1.06, 95% CI 1.01-1.11); and lower total bilirubin in blood concentration (OR 0.94, 95% CI 0.90-0.99).

CONCLUSIONS

We found that low oxygen saturation, old age, and the coexistence of cancer, gastric ulcers, and dementia syndrome were variables that independently increased mortality during hospitalization due to COVID-19. Moreover, we found that decreased platelet count and bilirubin concentration and increased levels of LDH and NT-proBNP were laboratory test results that independently indicated a higher risk of mortality. We also confirmed the usefulness of the SOFA scale in predicting treatment results. The ability to identify mortality risk factors on admission to hospital will facilitate both adjusting the intensity of treatment and the monitoring of patients infected with SARS-CoV-2.

Plasma Proprotein Convertase Subtilisin/Kexin Type 9 (PCSK9) as a Possible Biomarker for Severe COVID-19

Proprotein convertase subtilisin/kexin type 9 (PCSK9) reduces low density lipoprotein (LDL) uptake, leading to increased plasma levels of LDL. In addition, PCSK9 has been implicated in inflammation independently of the effects on cholesterol metabolism. The current analysis showed that our 156 patients with systemic inflammatory response syndrome (SIRS) or sepsis had higher plasma PCSK9 levels in contrast with the 68 healthy controls. COVID-19 sepsis patients had increased plasma PCSK9 levels in comparison to sepsis patients not infected by SARS-CoV-2. For further analysis, patients were divided in two groups based on COVID-19. In both sub-cohorts, plasma PCSK9 levels did not correlate with C-reactive protein, leukocyte count, and procalcitonin. Plasma PCSK9 levels of both patient groups did not significantly differ among SIRS/sepsis patients with and without dialysis and patients with and without ventilation. Furthermore, vasopressor therapy was not significantly associated with altered plasma PCSK9 levels. In the non-COVID-19 SIRS/sepsis group, patients with Gram-negative and Gram-positive infections had similar plasma PCSK9 levels as patients without a detectable pathogen in their blood. In conclusion, the current study suggests PCSK9 as a possible biomarker for COVID-19, but this needs to be validated in larger cohorts.

The bidirectional interaction of COVID-19 infections and lipoproteins

COVID-19 infections decrease total cholesterol, LDL-C, HDL-C, and apolipoprotein A-I, A-II, and B levels while triglyceride levels may be increased or inappropriately normal for the poor nutritional status. The degree of reduction in total cholesterol, LDL-C, HDL-C, and apolipoprotein A-I are predictive of mortality. With recovery lipid/lipoprotein levels return towards pre-infection levels and studies have even suggested an increased risk of dyslipidemia post-COVID-19 infection. The potential mechanisms for these changes in lipid and lipoprotein levels are discussed. Decreased HDL-C and apolipoprotein A-I levels measured many years prior to COVID-19 infections are associated with an increased risk of severe COVID-19 infections while LDL-C, apolipoprotein B, Lp (a), and triglyceride levels were not consistently associated with an increased risk. Finally, data suggest that omega-3-fatty acids and PCSK9 inhibitors may reduce the severity of COVID-19 infections. Thus, COVID-19 infections alter lipid/lipoprotein levels and HDL-C levels may affect the risk of developing COVID-19 infections.

Lipoprotein(a) Does Not Predict Thrombotic Events and In-Hospital Outcomes in Patients with COVID-19

The prothrombotic and proinflammatory properties of lipoprotein(a) (Lp(a)) have been hypothesized to play a role in the pathogenesis of severe COVID-19; however, the prognostic impact of Lp(a) on the clinical course of COVID-19 remains controversial. This study aimed to investigate whether Lp(a) may be associated with biomarkers of thrombo-inflammation and the occurrence of thrombotic events or adverse clinical outcomes in patients hospitalized for COVID-19. We consecutively enrolled a cohort of patients hospitalized for COVID-19 and collected blood samples for Lp(a) assessment at hospital admission. A prothrombotic state was evaluated through D-dimer levels, whereas a proinflammatory state was evaluated through C-reactive protein (CRP), procalcitonin, and white blood cell (WBC) levels. Thrombotic events were marked by the diagnosis of deep or superficial vein thrombosis (DVT or SVT), pulmonary embolism (PE), stroke, transient ischemic attack (TIA), acute coronary syndrome (ACS), and critical limb ischemia (CLI). The composite clinical end point of intensive care unit (ICU) admission/in-hospital death was used to evaluate adverse clinical outcomes. Among 564 patients (290 (51%) men, mean age of 74 ± 17 years) the median Lp(a) value at hospital admission was 13 (10-27) mg/dL. During hospitalization, 64 (11%) patients were diagnosed with at least one thrombotic event and 83 (15%) patients met the composite clinical end point. Lp(a), as either a continuous or categorical variable, was not associated with D-dimer, CRP, procalcitonin, and WBC levels (p > 0.05 for all correlation analyses). In addition, Lp(a) was not associated with a risk of thrombotic events (p > 0.05 for multi-adjusted odds ratios) nor with a risk of adverse clinical outcomes (p > 0.05 for multi-adjusted hazard ratios). In conclusion, Lp(a) does not influence biomarkers of plasma thrombotic activity and systemic inflammation nor has any impact on thrombotic events and adverse clinical outcomes in patients hospitalized for COVID-19.

Extracellular vesicles in COVID-19 prognosis, treatment, and vaccination: an update

The lethality of the COVID 19 pandemic became the trigger for one of the most meteoric races on record in the search for strategies of disease control. Those include development of rapid and sensitive diagnostic methods, therapies to treat severe cases, and development of anti-SARS-CoV-2 vaccines, the latter responsible for the current relative control of the disease. However, the commercially available vaccines are still far from conferring protection against acquiring the infection, so the development of more efficient vaccines that can cut the transmission of the variants of concerns that currently predominate and those that will emerge is a prevailing need. On the other hand, considering that COVID 19 is here to stay, the development of new diagnosis and treatment strategies is also desirable. In this sense, there has recently been a great interest in taking advantage of the benefits offered by extracellular vesicles (EVs), membrane structures of nanoscale size that carry information between cells participating in this manner in many physiological homeostatic and pathological processes. The interest has been focused on the fact that EVs are relatively easy to obtain and manipulate, allowing the design of natural nanocarriers that deliver molecules of interest, as well as the information about the pathogens, which can be exploited for the aforementioned purposes. Studies have shown that infection with SARS-CoV-2 induces the release of EVs from different sources, including platelets, and that their increase in blood, as well as some of their markers, could be used as a prognosis of disease severity. Likewise, EVs from different sources are being used as the ideal carriers for delivering active molecules and drugs to treat the disease, as well as vaccine antigens. In this review, we describe the progress that has been made in these three years of pandemic regarding the use of EVs for diagnosis, treatment, and vaccination against SARS-CoV-2 infection. KEY POINTS: • Covid-19 still requires more effective and specific treatments and vaccines. • The use of extracellular vesicles is emerging as an option with multiple advantages. • Association of EVs with COVID 19 and engineered EVs for its control are presented.

Prognostic models in COVID-19 infection that predict severity: a systematic review

Current evidence on COVID-19 prognostic models is inconsistent and clinical applicability remains controversial. We performed a systematic review to summarize and critically appraise the available studies that have developed, assessed and/or validated prognostic models of COVID-19 predicting health outcomes. We searched six bibliographic databases to identify published articles that investigated univariable and multivariable prognostic models predicting adverse outcomes in adult COVID-19 patients, including intensive care unit (ICU) admission, intubation, high-flow nasal therapy (HFNT), extracorporeal membrane oxygenation (ECMO) and mortality. We identified and assessed 314 eligible articles from more than 40 countries, with 152 of these studies presenting mortality, 66 progression to severe or critical illness, 35 mortality and ICU admission combined, 17 ICU admission only, while the remaining 44 studies reported prediction models for mechanical ventilation (MV) or a combination of multiple outcomes. The sample size of included studies varied from 11 to 7,704,171 participants, with a mean age ranging from 18 to 93 years. There were 353 prognostic models investigated, with area under the curve (AUC) ranging from 0.44 to 0.99. A great proportion of studies (61.5%, 193 out of 314) performed internal or external validation or replication. In 312 (99.4%) studies, prognostic models were reported to be at high risk of bias due to uncertainties and challenges surrounding methodological rigor, sampling, handling of missing data, failure to deal with overfitting and heterogeneous definitions of COVID-19 and severity outcomes. While several clinical prognostic models for COVID-19 have been described in the literature, they are limited in generalizability and/or applicability due to deficiencies in addressing fundamental statistical and methodological concerns. Future large, multi-centric and well-designed prognostic prospective studies are needed to clarify remaining uncertainties.

Vaccination saves lives: a real-time study of patients with chronic diseases and severe COVID-19 infection

OBJECTIVES

This study aims to describe the demographic and clinical profile and ascertain the determinants of outcome among hospitalized coronavirus disease 2019 (COVID-19) adult patients enrolled in the National Clinical Registry for COVID-19 (NCRC).

METHODS

NCRC is an on-going data collection platform operational in 42 hospitals across India. Data of hospitalized COVID-19 patients enrolled in NCRC between 1st September 2020 to 26th October 2021 were examined.

RESULTS

Analysis of 29 509 hospitalized, adult COVID-19 patients [mean (SD) age: 51.1 (16.2) year; male: 18 752 (63.6%)] showed that 15 678 (53.1%) had at least one comorbidity. Among 25 715 (87.1%) symptomatic patients, fever was the commonest symptom (72.3%) followed by shortness of breath (48.9%) and dry cough (45.5%). In-hospital mortality was 14.5% (n = 3957). Adjusted odds of dying were significantly higher in age group ≥60 years, males, with diabetes, chronic kidney diseases, chronic liver disease, malignancy and tuberculosis, presenting with dyspnoea and neurological symptoms. WHO ordinal scale 4 or above at admission carried the highest odds of dying [5.6 (95% CI: 4.6-7.0)]. Patients receiving one [OR: 0.5 (95% CI: 0.4-0.7)] or two doses of anti-SARS CoV-2 vaccine [OR: 0.4 (95% CI: 0.3-0.7)] were protected from in-hospital mortality.

CONCLUSIONS

WHO ordinal scale at admission is the most important independent predictor for in-hospital death in COVID-19 patients. Anti-SARS-CoV2 vaccination provides significant protection against mortality.

Deep Survival Analysis With Clinical Variables for COVID-19

OBJECTIVE

Millions of people have been affected by coronavirus disease 2019 (COVID-19), which has caused millions of deaths around the world. Artificial intelligence (AI) plays an increasing role in all areas of patient care, including prognostics. This paper proposes a novel predictive model based on one dimensional convolutional neural networks (1D CNN) to use clinical variables in predicting the survival outcome of COVID-19 patients.

METHODS AND PROCEDURES

We have considered two scenarios for survival analysis, 1) uni-variate analysis using the Log-rank test and Kaplan-Meier estimator and 2) combining all clinical variables ([Formula: see text]=44) for predicting the short-term from long-term survival. We considered the random forest (RF) model as a baseline model, comparing to our proposed 1D CNN in predicting survival groups.

RESULTS

Our experiments using the univariate analysis show that nine clinical variables are significantly associated with the survival outcome with corrected p < 0.05. Our approach of 1D CNN shows a significant improvement in performance metrics compared to the RF and the state-of-the-art techniques (i.e., 1D CNN) in predicting the survival group of patients with COVID-19.

CONCLUSION

Our model has been tested using clinical variables, where the performance is found promising. The 1D CNN model could be a useful tool for detecting the risk of mortality and developing treatment plans in a timely manner.

CLINICAL IMPACT

The findings indicate that using both Heparin and Exnox for treatment is typically the most useful factor in predicting a patient's chances of survival from COVID-19. Moreover, our predictive model shows that the combination of AI and clinical data can be applied to point-of-care services through fast-learning healthcare systems.

Clinical Characteristics and Predictors of In-Hospital Mortality of Patients Hospitalized with COVID-19 Infection

Background: The identification of parameters that would serve as predictors of prognosis in COVID-19 patients is very important. In this study, we assessed independent factors of in-hospital mortality of COVID-19 patients during the second wave of the pandemic. Material and methods: The study group consisted of patients admitted to two hospitals and diagnosed with COVID-19 between October 2020 and May 2021. Clinical and demographic features, the presence of comorbidities, laboratory parameters, and radiological findings at admission were recorded. The relationship of these parameters with in-hospital mortality was evaluated. Results: A total of 1040 COVID-19 patients (553 men and 487 women) qualified for the study. The in-hospital mortality rate was 26% across all patients. In multiple logistic regression analysis, age ≥ 70 years with OR = 7.8 (95% CI 3.17−19.32), p < 0.001, saturation at admission without oxygen ≤ 87% with OR = 3.6 (95% CI 1.49−8.64), p = 0.004, the presence of typical COVID-19-related lung abnormalities visualized in chest computed tomography ≥40% with OR = 2.5 (95% CI 1.05−6.23), p = 0.037, and a concomitant diagnosis of coronary artery disease with OR = 3.5 (95% CI 1.38−9.10), p = 0.009 were evaluated as independent risk factors for in-hospital mortality. Conclusion: The relationship between clinical and laboratory markers, as well as the advancement of lung involvement by typical COVID-19-related abnormalities in computed tomography of the chest, and mortality is very important for the prognosis of these patients and the determination of treatment strategies during the COVID-19 pandemic.

Serum calprotectin can indicate current and future severity of COVID-19

BACKGROUND

Predictive and prognostic biomarkers to guide 2019 novel coronavirus disease (COVID-19) are critically evolving. Dysregulated immune responses are the pivotal cause of severity mainly mediated by neutrophil activation. Thus, we evaluated the association of calprotectin, neutrophil secretory protein, and other mediators of inflammation with the severity and outcomes of COVID-19.

METHODS

This two-center prospective study focused on PCR-proven COVID-19 patients (n = 76) with different clinical presentations and SARS-CoV-2 negative control subjects (n = 24). Serum calprotectin (SC) was compared with IL-6 and other laboratory parameters.

RESULTS

Median levels of SC were significantly higher in COVID-19 patients in comparison to the control group (3760 vs. 2100 ng/ml, p < 0.0001). Elevated SC was significantly respective of disease severity (3760 ng/ml in mild up to 5700 ng/ml in severe cases, p < 0.0001). Moreover, the significant positive and negative correlations of SC with disease severity and oxygenation status indicated disease progression and respiratory worsening, respectively. It was found that SC was high in severe patients during hospitalization and significantly declined to normal after recovery. The logistic analysis identified the independent predictive power of SC for respiratory status or clinical severity. Indeed, SC behaved as a better discriminator for both outcomes, as it exhibited the largest area under the curve (receiver operating curve analysis), with the highest specificity and sensitivity when the predictive value of inflammatory biomarkers was compared.

CONCLUSION

Calprotectin can be used as a reliable prognostic tool to predict the poor clinical outcomes of COVID-19 patients.

Vascular dysfunction in COVID-19 patients: update on SARS-CoV-2 infection of endothelial cells and the role of long non-coding RNAs

Although COVID-19 is primarily a respiratory disease, it may affect also the cardiovascular system. COVID-19 patients with cardiovascular disorder (CVD) develop a more severe disease course with a significantly higher mortality rate than non-CVD patients. A common denominator of CVD is the dysfunction of endothelial cells (ECs), increased vascular permeability, endothelial-to-mesenchymal transition, coagulation, and inflammation. It has been assumed that clinical complications in COVID-19 patients suffering from CVD are caused by SARS-CoV-2 infection of ECs through the angiotensin-converting enzyme 2 (ACE2) receptor and the cellular transmembrane protease serine 2 (TMPRSS2) and the consequent dysfunction of the infected vascular cells. Meanwhile, other factors associated with SARS-CoV-2 entry into the host cells have been described, including disintegrin and metalloproteinase domain-containing protein 17 (ADAM17), the C-type lectin CD209L or heparan sulfate proteoglycans (HSPG). Here, we discuss the current data about the putative entry of SARS-CoV-2 into endothelial and smooth muscle cells. Furthermore, we highlight the potential role of long non-coding RNAs (lncRNAs) affecting vascular permeability in CVD, a process that might exacerbate disease in COVID-19 patients.

Reduced circulating FABP2 in patients with moderate to severe COVID-19 may indicate enterocyte functional change rather than cell death

The gut is of importance in the pathology of COVID-19 both as a route of infection, and gut dysfunction influencing the severity of disease. Systemic changes caused by SARS-CoV-2 gut infection include alterations in circulating levels of metabolites, nutrients and microbial products which alter immune and inflammatory responses. Circulating plasma markers for gut inflammation and damage such as zonulin, lipopolysaccharide and β-glycan increase in plasma along with severity of disease. However, Intestinal Fatty Acid Binding Protein / Fatty Acid Binding Protein 2 (I-FABP/FABP2), a widely used biomarker for gut cell death, has paradoxically been shown to be reduced in moderate to severe COVID-19. We also found this pattern in a pilot cohort of mild (n = 18) and moderately severe (n = 19) COVID-19 patients in Milan from March to June 2020. These patients were part of the first phase of COVID-19 in Europe and were therefore all unvaccinated. After exclusion of outliers, patients with more severe vs milder disease showed reduced FABP2 levels (median [IQR]) (124 [368] vs. 274 [558] pg/mL, P < 0.01). A reduction in NMR measured plasma relative lipid-CH3 levels approached significance (median [IQR]) (0.081 [0.011] vs. 0.073 [0.024], P = 0.06). Changes in circulating lipid levels are another feature commonly observed in severe COVID-19 and a weak positive correlation was observed in the more severe group between reduced FABP2 and reduced relative lipid-CH3 and lipid-CH2 levels. FABP2 is a key regulator of enterocyte lipid import, a process which is inhibited by gut SARS-CoV-2 infection. We propose that the reduced circulating FABP2 in moderate to severe COVID-19 is a marker of infected enterocyte functional change rather than gut damage, which could also contribute to the development of hypolipidemia in patients with more severe disease.

Admission Predictors of Mortality in Hospitalized COVID-19 Patients-A Serbian Cohort Study

Background: Early prediction of COVID-19 patients’ mortality risk may be beneficial in adequate triage and risk assessment. Therefore, we aimed to single out the independent morality predictors of hospitalized COVID-19 patients among parameters available on hospital admission. Methods: An observational, retrospective−prospective cohort study was conducted on 703 consecutive COVID-19 patients hospitalized in the University Clinical Center Kragujevac between September and December 2021. Patients were followed during the hospitalization, and in-hospital mortality was observed as a primary end-point. Within 24 h of admission, patients were sampled for blood gas and laboratory analysis, including complete blood cell count, inflammation biomarkers and other biochemistry, coagulation parameters, and cardiac biomarkers. Socio-demographic and medical history data were obtained using patients’ medical records. Results: The overall prevalence of mortality was 28.4% (n = 199). After performing multiple regression analysis on 20 parameters, according to the initial univariate analysis, only four independent variables gave statistically significant contributions to the model: SaO2 < 88.5 % (aOR 3.075), IL-6 > 74.6 pg/mL (aOR 2.389), LDH > 804.5 U/L (aOR 2.069) and age > 69.5 years (aOR 1.786). The C-index of the predicted probability calculated using this multivariate logistic model was 0.740 (p < 0.001). Conclusions: Parameters available on hospital admission can be beneficial in predicting COVID-19 mortality.

The Role of Bioelectrical Impedance Analysis in Predicting COVID-19 Outcome

Background

Published data regarding the impact of obesity on COVID-19 outcomes are inconsistent. However, in most studies, body composition was assessed using body mass index (BMI) alone, thus neglecting the presence and distribution of adipose tissue. Therefore, we aimed to investigate the impact of body and visceral fat on COVID-19 outcomes.

Methods

Observational, prospective cohort study included 216 consecutive COVID-19 patients hospitalized at University Clinical Center Kragujevac (Serbia) from October to December 2021. Body composition was assessed using the BMI, body fat percentage (%BF), and visceral fat (VF) via bioelectrical impedance analysis (BIA). In addition to anthropometric measurements, variables in the research were socio-demographic and medical history data, as well as admission inflammatory biomarkers. Primary end-points were fatal outcomes and intensive care unit (ICU) admission.

Results

The overall prevalence of obesity was 39.3% according to BMI and 50.9% according to % BF, while 38.4% of patients had very high VF levels. After adjusting odds ratio values for cofounding variables and obesity-related conditions, all three anthropometric parameters were significant predictors of primary end-points. However, we note that % BF and VF, compared to BMI, were stronger predictors of both mortality (aOR 3.353, aOR 3.05, and aOR 2.387, respectively) and ICU admission [adjusted odds ratio (aOR) 7.141, aOR 3.424, and aOR 3.133, respectively].

Conclusion

Obesity is linked with COVID-19 mortality and ICU admission, with BIA measurements being stronger predictors of outcome compared to BMI use alone.

Elevated Lp(a) and course of COVID-19: Is there a relationship?

Background

Lipoprotein (a)–Lp(a) has proinflammatory, prothrombotic and proatherogenic properties and may theoretically influence the course of COVID-19.

Objectives

The aim of the study was to explore whether patients hospitalized due to COVID-19 with Lp(a) ≥30mg/dl may develop a worse course of the disease, increased incidence of thromboembolic complications, intubation and ICU hospitalization or death.

Patients and methods

A retrospective analysis was performed of 124 patients hospitalized due to COVID-19 in the Department of Internal Diseases and Clinical Pharmacology between 29 November 2020 and 15 April 2021. The only exclusion criterion was age≥80 years. Patients were divided into two groups: 1. COVID-19 patients with Lp(a) <30mg/dl regarded as not elevated n = 80; 2. COVID-19 patients with Lp(a) ≥30 regarded as elevated n = 44.

Results

A total of 124 COVID-19 patients were included in the study (66 men and 58 women) with a mean age of 62.8±11 years. COVID-19 patients with elevated Lp(a) level had significantly longer hospitalization time (11 vs. 9.5 days; p = 0.0362), more extensive radiological changes in CT scan (35 vs. 30%; p = 0.0301) and higher oxygen demand on admission (8 vs. 5L/min; p = 0.0428). Elevated Lp(a) was also associated with significantly higher OR for High Flow Nasal Oxygen Therapy (HFNOT) OR = 3.5 95%CI(1.2;8.9), p = 0.0140, Intubation and ICU OR = 4.1 95%CI(1.1;15.2) p = 0.0423, Death OR = 2.8 95%CI(0.9;8.5), p = 0.0409.

Conclusions

Elevated Lp(a) might be one of the factors which contribute to a more severe course of COVID-19; however, further studies including larger groups of patients are needed.

The Association between TNF-α, IL-6, and Vitamin D Levels and COVID-19 Severity and Mortality: A Systematic Review and Meta-Analysis

BACKGROUND

An increasing number of scientific journals have proposed a connection between tumor necrosis factor-α (TNF-α) and interleukin-6 (IL-6) and the severity of COVID-19. Vitamin D has been discussed as a potential therapy for COVID-19 due to its immunomodulatory effects. This meta-analysis aims to determine the relationship, if any, between TNF-α, IL-6, vitamin D, and COVID-19 severity and mortality.

METHODS

The design of the study is a systematic review and meta-analysis. A literature search is performed using PubMed, Cochrane, ProQuest, and Google Scholar.

RESULTS

TNF-α insignificantly increases the risk of COVID-19 severity (adjusted odds ratio (aOR) = 1.0304; 95% CI 0.8178-1.2983; p = 0.80) but significantly increases the risk of COVID-19 mortality (crude hazard ratio (HR) = 1.0640; 95% CI 1.0259-1.1036; p = 0.0009). IL-6 significantly increases the risk of COVID-19 severity (aOR = 1.0284; 95% CI 1.0130-1.0441; p = 0.0003) and mortality (aOR = 1.0076; 95% CI 1.0004-1.0148; p = 0.04; adjusted hazard ratio (aHR) = 1.0036; 95% CI 1.0010-1.0061; p = 0.006). There is a statistically insignificant difference of the mean vitamin D levels between patients with severe COVID-19 and non-severe COVID-19 (mean difference (MD) = -5.0232; 95% CI 11.6832-1.6368; p = 0.14). A vitamin D deficiency insignificantly increases the risk of mortality of COVID-19 patients (aOR = 1.3827; 95% CI 0.7103-2.6916; p = 0.34).

CONCLUSION

IL-6 is an independent prognostic factor towards COVID-19 severity and mortality.

HDL in COVID-19 Patients: Evidence from an Italian Cross-Sectional Study

A number of studies have highlighted important alterations of the lipid profile in COVID-19 patients. Besides the well-known atheroprotective function, HDL displays anti-inflammatory, anti-oxidative, and anti-infectious properties. The aim of this retrospective study was to assess the HDL anti-inflammatory and antioxidant features, by evaluation of HDL-associated Serum amyloid A (SAA) enrichment and HDL-paraoxonase 1 (PON-1) activity, in a cohort of COVID-19 patients hospitalized at the Cardiorespiratory COVID-19 Unit of Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico of Milan. COVID-19 patients reached very low levels of HDL-c (mean ± SD: 27.1 ± 9.7 mg/dL) with a marked rise in TG (mean ± SD: 165.9 ± 62.5 mg/dL). Compared to matched-controls, SAA levels were significantly raised in COVID-19 patients at admission. There were no significant differences in the SAA amount between 83 alive and 22 dead patients for all-cause in-hospital mortality. Similar findings were reached in the case of PON-1 activity, with no differences between alive and dead patients for all-cause in-hospital mortality. In conclusion, although not related to the prediction of in-hospital mortality, reduction in HDL-c and the enrichment of SAA in HDL are a mirror of SARS-CoV-2 positivity even at the very early stages of the infection.

Echocardiographic assessment of the right ventricle in COVID-19: a systematic review

Cardiac involvement has been frequently reported in COVID-19 as responsible of increased morbidity and mortality. Given the importance of right heart function in acute and chronic respiratory diseases, its assessment in SARS-CoV-2 infected patients may add prognostic accuracy. Transthoracic echocardiography has been proposed to early predict myocardial injury and risk of death in hospitalized patients. This systematic review presents the up-to-date sum of literature regarding right ventricle ultrasound assessment. We evaluated commonly used echocardiographic parameters to assess RV function and discussed their relationship with pathophysiological mechanisms involved in COVID-19. We searched Medline and Embase for studies that used transthoracic echocardiography for right ventricle assessment in patients with COVID-19.

Prognostic Impact of Acute Cardiovascular Events in COVID-19 Hospitalized Patients-Results from the CORONA Germany Study

BACKGROUND

Acute myocardial injury (AMJ), assessed by elevated levels of cardiac troponin, is associated with fatal outcome in coronavirus disease 2019 (COVID-19). However, the role of acute cardiovascular (CV) events defined by clinical manifestation rather than sole elevations of biomarkers is unclear in hospitalized COVID-19 patients.

OBJECTIVE

The aim of this study was to investigate acute clinically manifest CV events in hospitalized COVID-19 patients.

METHODS

From 1 March 2020 to 5 January 2021, we conducted a multicenter, prospective, epidemiological cohort study at six hospitals from Hamburg, Germany (a portion of the state-wide 45-center CORONA Germany cohort study) enrolling all hospitalized COVID-19 patients. Primary endpoint was occurrence of a clinically manifest CV-event.

RESULTS

In total, 132 CV-events occurred in 92 of 414 (22.2%) patients in the Hamburg-cohort: cardiogenic shock in 10 (2.4%), cardiopulmonary resuscitation in 12 (2.9%), acute coronary syndrome in 11 (2.7%), de-novo arrhythmia in 31 (7.5%), acute heart-failure in 43 (10.3%), myocarditis in 2 (0.5%), pulmonary-embolism in 11 (2.7%), thrombosis in 9 (2.2%) and stroke in 3 (0.7%). In the Hamburg-cohort, mortality was 46% (42/92) for patients with a CV-event and 33% (27/83) for patients with only AMJ without CV-event (OR 1.7, CI: (0.94-3.2), p = 0.077). Mortality was higher in patients with CV-events (Odds ratio(OR): 4.8, 95%-confidence-interval(CI): [2.9-8]). Age (OR 1.1, CI: (0.66-1.86)), atrial fibrillation (AF) on baseline-ECG (OR 3.4, CI: (1.74-6.8)), systolic blood-pressure (OR 0.7, CI: (0.53-0.96)), potassium (OR 1.3, CI: (0.99-1.73)) and C-reactive-protein (1.4, CI (1.04-1.76)) were associated with CV-events.

CONCLUSION

Hospitalized COVID-19 patients with clinical manifestation of acute cardiovascular events show an almost five-fold increased mortality. In this regard, the emergence of arrhythmias is a major determinant.

Prognostic parameters of in-hospital mortality in COVID-19 patients-An Italian experience

Background During COVID-19 outbreak, Italy was the first country in Europe to be heavily affected with an intensive care unit mortality of 26%. In order to reduce this percentage, physicians should establish clear and objective criteria to stratify COVID-19 patients at high risk of in-hospital death. Thus, the aim has been to test a large spectrum of variables ranging from clinical evaluation to laboratory biomarkers to identify which parameter would best predict all-cause in-hospital mortality in COVID-19 patients. Design observational study. Results Multivariate Cox regression analysis showed that each 5 years of increase in age corresponded to a hazard ratio (HR) of 1.28 (95% CI 1.00-1.65, P = .050); each increment of 803 ng/L of N-terminal pro-B-type natriuretic peptide (NT-proBNP) corresponded to a HR of 1.24 (95% CI 1.11-1.39, P < .001); each increment of 58 ng/L of interleukin (IL)-6 corresponded to a HR of 1.23 (95% CI 1.09-1.40, P < .001), and each increment of 250 U/L of lactate dehydrogenase (LDH) corresponded to a HR of 1.23 (95% CI 1.10-1.37, P < .001). According to the calculated cut-points for age (≥70 years), NT-proBNP (≥803 ng/L), IL-6 (≥58 ng/L) and LDH (≥371 U/L) when 2 out of these 4 were overcome, the HR was 2.96 (95% CI 1.97-4.45, P < .001). Conclusion In COVID-19 patients, besides age, the evaluation of three biochemical parameters, available in few hours after hospital admission can predict in-hospital mortality regardless of other comorbidities.

Cardiovascular Disease Complicating COVID-19 in the Elderly

SARS-CoV-2, a single-stranded RNA coronavirus, causes an illness known as coronavirus disease 2019 (COVID-19). The highly transmissible virus gains entry into human cells primarily by the binding of its spike protein to the angiotensin-converting enzyme 2 receptor, which is expressed not only in lung tissue but also in cardiac myocytes and the vascular endothelium. Cardiovascular complications are frequent in patients with COVID-19 and may be a result of viral-associated systemic and cardiac inflammation or may arise from a virus-induced hypercoagulable state. This prothrombotic state is marked by endothelial dysfunction and platelet activation in both macrovasculature and microvasculature. In patients with subclinical atherosclerosis, COVID-19 may incite atherosclerotic plaque disruption and coronary thrombosis. Hypertension and obesity are common comorbidities in COVID-19 patients that may significantly raise the risk of mortality. Sedentary behaviors, poor diet, and increased use of tobacco and alcohol, associated with prolonged stay-at-home restrictions, may promote thrombosis, while depressed mood due to social isolation can exacerbate poor self-care. Telehealth interventions via smartphone applications and other technologies that document nutrition and offer exercise programs and social connections can be used to mitigate some of the potential damage to heart health.