Prognostic value of elevated lactate dehydrogenase in patients with COVID-19: a systematic review and meta-analysis

Hematological and biochemical markers and cytokine levels in hospitalized psychiatric patients with COVID-19

Background

Multiple lines of evidence indicate a connection between the pathogenesis of coronavirus disease 2019 (COVID-19) and psychiatric diseases (PDs). To improve the treatment and management of individuals with psychosis and COVID-19, we evaluated biomarkers of PD patients, including those with schizophrenia (SCZ), bipolar disorder (BD), and major depression (MDD), along with the biomarkers of COVID-19.

Methods

In this study, 104 inpatients with concurrent PD and COVID-19 (PD+), the same 104 PD patients after they had recovered from COVID-19 (PD-), and 97 healthy controls (HCs) were evaluated. We analyzed the peripheral blood hematological parameters, serum biochemical parameters, and cytokine levels of the participants and compared the results among the three groups.

Results

The monocyte count; neutrophil-to-lymphocyte ratio (NLR); monocyte-to-lymphocyte ratio (MLR); systemic immune-inflammation index (SII); and C-reactive protein (CRP), serum CK isoenzyme MB (CK-MB), glucose (GLU), and interleukin (IL)-6 levels were significantly greater (P < 0.05), whereas the magnesium (Mg) level was lower (P < 0.05) in both the PD+ and PD- groups than in the HC group. Moreover, the above indicators were significantly different between the PD+ and PD- groups (P < 0.05).

Conclusion

Neutrophil count, monocyte count, NLR, MLR, SII, CRP, CK-MB, GLU and IL-6 levels were positively correlated with COVID-19 and PD. The Mg level was negatively correlated with COVID-19 and PD. Our findings suggest that Mg supplementation might be considered a potential treatment approach for PD patients with COVID-19. Despite these insights, the underlying pathophysiological mechanisms remain unclear, highlighting the vital need for further research to validate and build upon these findings.

Identification of Early Biomarkers of Mortality in COVID-19 Hospitalized Patients: A LASSO-Based Cox and Logistic Approach

This study aimed to identify possible early biomarkers of mortality among clinical and biochemical parameters, iron metabolism parameters, and cytokines detected within 24 h from admission in hospitalized COVID-19 patients. We enrolled 80 hospitalized patients (40 survivors and 40 non-survivors) with COVID-19 pneumonia and acute respiratory failure. The median time from the onset of COVID-19 symptoms to hospital admission was lower in non-survivors than survivors (p < 0.05). Respiratory failure, expressed as the ratio of arterial oxygen partial pressure to the fraction of inspired oxygen (P/F), was more severe in non-survivors than survivors (p < 0.0001). Comorbidities were similar in both groups. Among biochemical parameters and cytokines, eGFR and interleukin (IL)-1β were found to be significantly lower (p < 0.05), while LDH, IL-10, and IL-8 were significantly higher in non-survivors than in survivors (p < 0.0005, p < 0.05 and p < 0.005, respectively). Among other parameters, LDH values distribution showed the most significant difference between study groups (p < 0.0001). LASSO feature selection combined with Cox proportional hazards and logistic regression models was applied to identify features distinguishing between survivors and non-survivors. Both approaches highlighted LDH as the strongest predictor, with IL-22 and creatinine emerging in the Cox model, while IL-10, eGFR, and creatinine were influential in the logistic model (AUC = 0.744 for Cox, 0.723 for logistic regression). In a similar manner, we applied linear regression for predicting LDH levels, identifying the P/F ratio as the top predictor, followed by IL-10 and eGFR (NRMSE = 0.128). Collectively, these findings underscore LDH's critical role in mortality prediction, with P/F and IL-10 as key determinants of LDH increases in this Italian COVID-19 cohort.

Inflammatory biomarkers and adverse outcome in COVID-19: Prelude for future viral pandemics

Background

Dysregulated inflammatory response plays a key role in the pathogenesis of COVID-19. The role of inflammatory markers to predict adverse clinical outcome is still controversial. The aim of this study was to analyze the association of inflammatory markers with disease outcomes independent of the effect of age and co-morbidities.

Materials and Methods

This is a retrospective analysis of COVID-19 patients admitted at a dedicated COVID center from July 2020 to Mar 2022. Clinical characteristics and inflammatory markers namely serum Ferritin levels, CRP, D-Dimer levels, serum LDH and IL-6 Levels were studied. The following outcome parameters were collected: disease severity at onset and outcome (discharge/death).

Results

48.4% of the of 244 COVID-19 cases included had severe disease while 51.6% had moderate disease. Mean age was 61.3 ± 14.17 years and 71.7% were males. Primary Hypertension (48.4%) and Diabetes Mellitus (39.3%) were the most common co-morbidities. Increasing age, smoking, and alcohol consumption were associated with severe disease. CRP, D-dimer, and IL-6 were independent risk factors for disease severity while CRP, D dimer, LDH, Ferritin, and NLR (Neutrophil Lymphocyte ratio) were independent predictors of disease mortality. D-dimer was the most sensitive (95.8%) and specific (92.2%) marker to predict disease severity and serum LDH was the most sensitive (74.7%) to predict disease mortality at baseline.

Conclusion

Measurement of inflammatory markers might assist clinicians in predicting disease severity and prognosis of COVID-19. This may serve as a benchmark to understand the role of inflammatory markers in other diseases associated with dysregulated inflammatory response.

Predictive factors associated with short-term mortality in cats with feline infectious peritonitis treated with remdesivir or GS-441524 or both

BACKGROUND

Although most cats with feline infectious peritonitis (FIP) respond to treatment with remdesivir or GS-441524 or both with uneventful clinical courses, some die despite treatment.

OBJECTIVE

Identify predictive factors associated with short-term mortality in cats with FIP treated with IV remdesivir or PO GS-441524 or both.

ANIMALS

A total of 108 client-owned cats with FIP.

METHODS

Retrospective multicenter study using data collected from medical records. Factors associated with short-term mortality, defined as death within 84 days, were identified. Univariate analysis a t-test, Mann-Whitney U test, or Fisher's exact test and multivariate logistic regression were performed to assess patient characteristics and clinicopathological variables between survivors and nonsurvivors.

RESULTS

The short-term mortality rate was 12.0% (95% confidence interval [CI], 6.6%-19.7%). Univariate analysis identified plasma lactate dehydrogenase activity (LDH; P < .001) and bilirubin concentration (P = .001) as being significantly increased in nonsurvivors, whereas concentrations of albumin (P = .003), total protein (P = .03), sodium (P = .005), and potassium (P = .005) were significantly lower. Additionally, nonsurvivors were significantly less likely to be febrile (≥39.4°C; P = .006). Of these variables, only plasma LDH activity ≥323 U/L, a cut-point determined by receiver operating characteristic curve analysis, was significantly associated with short-term mortality by multivariate analysis (odds ratio, 15.30; 95% CI, 1.18-198.00; P = .04).

CONCLUSION

Increased plasma LDH activity might be useful for predicting short-term mortality, guiding monitoring, and establishing prognosis in cats with FIP.

Evaluating the CURB-65 score for in-hospital mortality prediction in COVID-19 patients: insights into dysglycaemia

Introduction

While the CURB-65 score predicts mortality in community-acquired pneumonia (CAP), its performance in COVID-19 CAP is suboptimal. Hyperglycaemia correlates with an increased mortality in COVID-19. This analysis aims to enhance predictive accuracy for in-hospital mortality among COVID-19 patients by augmenting the CURB-65 score with objective variables, including markers of dysglycaemia.

Design

A single-centre retrospective observational analysis assessed the effectiveness of the CURB-65 score in predicting in-hospital mortality among adult patients with moderate to severe COVID-19 from March to September 2020. Using a binary logistic regression model, two extended CURB-65 scores which include markers of dysglycemia are proposed to enhance the predictive capability of the CURB-65 score for in-hospital mortality.

Results

Among 517 patients admitted, 117 (22.6%) died. Using the CURB-65 score, 393 patients (76%) were classified as low risk, 91 (17.6%) as medium risk and 33 (6.4%) as high risk. 37 patients were diagnosed with new-onset dysglycaemia, of which 22 (59.5%) died (p<0.001). Of those with dysglycaemia who died, 41% and 23% were classified as low risk and high risk using the CURB-65 score. The CURB-65 score demonstrated a modest area under the receiver operator characteristic curve (AUC) of 0.75 (95% CI 0.70 to 0.81) for in-hospital mortality in COVID-19 CAP. An Extended CURB-65 Score 1, incorporating an admission of fasting plasma glucose (FPG) and neutrophil to lymphocyte ratio, showed improved prognostic performance with an AUC of 0.80 (95% CI 0.76 to 0.85). When lactate and lactate dehydrogenase were added to these parameters (Extended CURB-65 Score 2), the AUC was 0.82 (95% CI 0.78 to 0.86). The integrated discrimination index showed an 11% and 24% higher discrimination slope when using the Extended CURB-65 Scores 1 and 2, respectively.

Conclusions

The addition of common biochemical parameters including an admission FPG enhances the prognostic performance of CURB-65 for in-hospital mortality among patients with COVID-19.

Efficient clinical decision-making process via AI-based multimodal data fusion: A COVID-19 case study

COVID-19 is an infectious disease that caused a global pandemic in 2020. In the critical moments of this healthcare emergencies, the medical staff needs to take important decisions in a context of limited resources that must be carefully managed. To this end, the computer-aided diagnosis methods are extremely powerful and help them to better recognize the evidences of high-risk patients. This can be done with the support of relevant information extracted from electronic health records, lab tests and imaging studies. In this work, we present a novel fully-automatic efficient method to help the clinical decision-making process in the context of COVID-19 risk estimation, using multimodal data fusion of clinical features and deep features extracted from chest X-ray images. The risk estimation is studied in two of the most relevant and critical encountered scenarios: the risk of hospitalization and mortality. This study shows which are the most important features for each scenario, the ratio of clinical and imaging features present in the top ranking and the performance of the used machine learning models. The results demonstrate a great performance by the classifiers, estimating the risk of hospitalization with an AUC-ROC of 0.8452 ± 0.0133 and the risk of death with an AUC-ROC of 0.8285 ± 0.0210, only using a subset of the original features, and highlight the significant contribution of imaging features to hospitalization risk assessment, while clinical features become more crucial for mortality risk evaluation. Furthermore, multimodal data fusion can outperform the approaches that use one data source. Despite the model's complexity, it requires fewer features, an advantage in scenarios with limited computational resources. This streamlined, fully-automated method shows promising potential to improve the clinical decision-making process and better manage medical resources, not only in the context of COVID-19, but also in other clinical scenarios.

Novel COVID-19 biomarkers identified through multi-omics data analysis: N-acetyl-4-O-acetylneuraminic acid, N-acetyl-L-alanine, N-acetyltriptophan, palmitoylcarnitine, and glycerol 1-myristate

This study aims to apply machine learning models to identify new biomarkers associated with the early diagnosis and prognosis of SARS-CoV-2 infection.Plasma and serum samples from COVID-19 patients (mild, moderate, and severe), patients with other pneumonia (but with negative COVID-19 RT-PCR), and healthy volunteers (control) from hospitals in four different countries (China, Spain, France, and Italy) were analyzed by GC-MS, LC-MS, and NMR. Machine learning models (PCA and PLS-DA) were developed to predict the diagnosis and prognosis of COVID-19 and identify biomarkers associated with these outcomes.A total of 1410 patient samples were analyzed. The PLS-DA model presented a diagnostic and prognostic accuracy of around 95% of all analyzed data. A total of 23 biomarkers (e.g., spermidine, taurine, L-aspartic, L-glutamic, L-phenylalanine and xanthine, ornithine, and ribothimidine) have been identified as being associated with the diagnosis and prognosis of COVID-19. Additionally, we also identified for the first time five new biomarkers (N-Acetyl-4-O-acetylneuraminic acid, N-Acetyl-L-Alanine, N-Acetyltriptophan, palmitoylcarnitine, and glycerol 1-myristate) that are also associated with the severity and diagnosis of COVID-19. These five new biomarkers were elevated in severe COVID-19 patients compared to patients with mild disease or healthy volunteers.The PLS-DA model was able to predict the diagnosis and prognosis of COVID-19 around 95%. Additionally, our investigation pinpointed five novel potential biomarkers linked to the diagnosis and prognosis of COVID-19: N-Acetyl-4-O-acetylneuraminic acid, N-Acetyl-L-Alanine, N-Acetyltriptophan, palmitoylcarnitine, and glycerol 1-myristate. These biomarkers exhibited heightened levels in severe COVID-19 patients compared to those with mild COVID-19 or healthy volunteers.

Increased levels of circulating cell-free DNA in COVID-19 patients with respiratory failure

Cell-free DNA (cfDNA) is released from injured cells and aggravates inflammation. Patients with coronavirus disease (COVID-19) often develop pneumonia and respiratory failure, and require oxygen therapy (OT), including mechanical ventilation (MV). It remains unclear whether cfDNA predicts the risk of receiving OT or MV in COVID-19 patients. Therefore, we hypothesized that circulating cfDNA levels could reflect the severity of respiratory failure and determine a therapeutic approach for oxygenation in patients with COVID-19. We analyzed cfDNA levels in serum samples from 95 hospitalized patients with COVID-19 at Showa University Hospital (Tokyo, Japan). cfDNA levels were assessed by measuring the copy numbers of mitochondrial DNA (mtDNA) and nuclear DNA (nDNA) using quantitative real-time PCR (qPCR). Both cf-nDNA and cf-mtDNA levels were negatively correlated with adjusted SpO2 for FiO2 (SpO2/FiO2 ratio). Elevated cf-nDNA and cf-mtDNA levels were associated with the requirement for OT or MV during patient admission. Multivariate logistic regression analysis revealed that cf-nDNA and cf-mtDNA levels were independent risk factors for OT and MV. These results suggest that both serum cf-nDNA and cf-mtDNA could serve as useful early biomarkers to indicate the necessity of OT or MV in patients with COVID-19.

Effect of early administration of dexamethasone in patients with COVID-19 pneumonia without acute hypoxemic respiratory failure and risk of development of acute respiratory distress syndrome: EARLY-DEX COVID-19 trial

Introduction and objectives

Corticosteroids are among the drugs demonstrating a mortality benefit for coronavirus disease 2019 (COVID-19). The RECOVERY trial highlighted that dexamethasone reduced 28-day mortality for hospitalized COVID-19 patients requiring either supplemental oxygen or mechanical ventilation. It is noted that approximately 30% of COVID-19 patients, initially presenting with mild symptoms, will advance to acute respiratory distress syndrome (ARDS), especially those with detectable laboratory markers of inflammation indicative of disease progression. Our research aimed to explore the efficacy of dexamethasone in preventing the progression to ARDS in patients hospitalized with COVID-19 pneumonia who do not yet require additional oxygen but are at high risk of developing ARDS, potentially leading to a reduction in morbimortality.

Methods

In this multicenter, randomized, controlled trial, we evaluated the impact of dexamethasone on adult patients diagnosed with COVID-19 pneumonia who did not need supplementary oxygen at admission but were identified as having risk factors for ARDS. The risk of ARDS was determined based on specific criteria: elevated lactate dehydrogenase levels over 245 U/L, C-reactive protein levels exceeding 100 mg/L, and a lymphocyte count below 0.80 × 109/L. Participants were randomly allocated to either receive dexamethasone or the standard care. The primary endpoints included the incidence of moderate or severe ARDS and all-cause mortality within 30 days post-enrollment.

Results

One hundred twenty-six patients were randomized. Among them, 41 were female (30.8%), with a mean age of 48.8 ± 14.4 years. Ten patients in the dexamethasone group (17.2%) and ten patients in the control group (14.7%) developed moderate ARDS with no significant differences. Mechanical ventilation was required in six patients (4.7%), with four in the treatment group and two in the control group. There were no deaths during hospitalization or during follow-up. An intermediate analysis for futility showed some differences between the control and treatment groups (Z = 0.0284). However, these findings were within the margins close to the region where the null hypothesis would not be rejected.

Conclusion

In patients with COVID-19 pneumonia without oxygen needs but at risk of progressing to severe disease, early dexamethasone administration did not lead to a decrease in ARDS development.

Clinical trial registration

ClinicalTrials.gov, identifier NCT04836780.

Thambiah S, Masiman AD, Samsudin IN, Lai YY. Refractory hypoxia and saturation gap in a COVID-19 patient

Acquired methemoglobinemia, predominantly due to oxidizing medications occurs when heme iron in hemoglobin is oxidized from ferrous to ferric ion and binds oxygen irreversibly leading to functional anemia, cyanosis, and tissue hypoxia. We report a case of a 60-year-old man with multiple comorbidities who was diagnosed with coronavirus disease 2019 (COVID-19) and developed methemoglobinemia after consumption of prescribed supplements. He presented with dyspnea and cyanosis. An oxygen saturation gap with characteristic chocolate-brown arterial blood indicated methemoglobinemia. Outsourced methemoglobin (MetHb) was increased at 9.0%. Despite aggressive intervention, he succumbed to his illness. In this case, we discuss the pathophysiology of why some individuals, especially the elderly with COVID-19 are more susceptible to develop methemoglobinemia after possibly being exposed to oxidizing agents. Laboratory methods for assessing oxygen saturation, including pulse oximetry, arterial blood gas and co-oximetry are examined in relation to this case. The importance of considering a diagnosis of methemoglobinemia based on clinical and biochemical findings although MetHb assay or co-oximetry are not readily available is also emphasized.

SARS-CoV-2 and its ORF3a, E and M viroporins activate inflammasome in human macrophages and induce of IL-1α in pulmonary epithelial and endothelial cells

Inflammasome assembly is a potent mechanism responsible for the host protection against pathogens, including viruses. When compromised, it can allow viral replication, while when disrupted, it can perpetuate pathological responses by IL-1 signaling and pyroptotic cell death. SARS-CoV-2 infection was shown to activate inflammasome in the lungs of COVID-19 patients, however, potential mechanisms responsible for this response are not fully elucidated. In this study, we investigated the effects of ORF3a, E and M SARS-CoV-2 viroporins in the inflammasome activation in major populations of alveolar sentinel cells: macrophages, epithelial and endothelial cells. We demonstrated that each viroporin is capable of activation of the inflammasome in macrophages to trigger pyroptosis-like cell death and IL-1α release from epithelial and endothelial cells. Small molecule NLRP3 inflammasome inhibitors reduced IL-1 release but weakly affected the pyroptosis. Importantly, we discovered that while SARS-CoV-2 could not infect the pulmonary microvascular endothelial cells it induced IL-1α and IL-33 release. Together, these findings highlight the essential role of macrophages as the major inflammasome-activating cell population in the lungs and point to endothelial cell expressed IL-1α as a potential novel component driving the pulmonary immunothromobosis in COVID-19.

A generalizable and easy-to-use COVID-19 stratification model for the next pandemic via immune-phenotyping and machine learning

Introduction

The coronavirus disease 2019 (COVID-19) pandemic has affected billions of people worldwide, and the lessons learned need to be concluded to get better prepared for the next pandemic. Early identification of high-risk patients is important for appropriate treatment and distribution of medical resources. A generalizable and easy-to-use COVID-19 severity stratification model is vital and may provide references for clinicians.

Methods

Three COVID-19 cohorts (one discovery cohort and two validation cohorts) were included. Longitudinal peripheral blood mononuclear cells were collected from the discovery cohort (n = 39, mild = 15, critical = 24). The immune characteristics of COVID-19 and critical COVID-19 were analyzed by comparison with those of healthy volunteers (n = 16) and patients with mild COVID-19 using mass cytometry by time of flight (CyTOF). Subsequently, machine learning models were developed based on immune signatures and the most valuable laboratory parameters that performed well in distinguishing mild from critical cases. Finally, single-cell RNA sequencing data from a published study (n = 43) and electronic health records from a prospective cohort study (n = 840) were used to verify the role of crucial clinical laboratory and immune signature parameters in the stratification of COVID-19 severity.

Results

Patients with COVID-19 were determined with disturbed glucose and tryptophan metabolism in two major innate immune clusters. Critical patients were further characterized by significant depletion of classical dendritic cells (cDCs), regulatory T cells (Tregs), and CD4+ central memory T cells (Tcm), along with increased systemic interleukin-6 (IL-6), interleukin-12 (IL-12), and lactate dehydrogenase (LDH). The machine learning models based on the level of cDCs and LDH showed great potential for predicting critical cases. The model performances in severity stratification were validated in two cohorts (AUC = 0.77 and 0.88, respectively) infected with different strains in different periods. The reference limits of cDCs and LDH as biomarkers for predicting critical COVID-19 were 1.2% and 270.5 U/L, respectively.

Conclusion

Overall, we developed and validated a generalizable and easy-to-use COVID-19 severity stratification model using machine learning algorithms. The level of cDCs and LDH will assist clinicians in making quick decisions during future pandemics.

A GMR enzymatic assay for quantifying nuclease and peptidase activity

Hydrolytic enzymes play crucial roles in cellular processes, and dysregulation of their activities is implicated in various physiological and pathological conditions. These enzymes cleave substrates such as peptide bonds, phosphodiester bonds, glycosidic bonds, and other esters. Detecting aberrant hydrolase activity is vital for understanding disease mechanisms and developing targeted therapeutic interventions. This study introduces a novel approach to measuring hydrolase activity using giant magnetoresistive (GMR) spin valve sensors. These sensors change resistance in response to magnetic fields, and here, they are functionalized with specific substrates for hydrolases conjugated to magnetic nanoparticles (MNPs). When a hydrolase cleaves its substrate, the tethered magnetic nanoparticle detaches, causing a measurable shift in the sensor's resistance. This design translates hydrolase activity into a real-time, activity-dependent signal. The assay is simple, rapid, and requires no washing steps, making it ideal for point-of-care settings. Unlike fluorescent methods, it avoids issues like autofluorescence and photobleaching, broadening its applicability to diverse biofluids. Furthermore, the sensor array contains 80 individually addressable sensors, allowing for the simultaneous measurement of multiple hydrolases in a single reaction. The versatility of this method is demonstrated with substrates for nucleases, Bcu I and DNase I, and the peptidase, human neutrophil elastase. To demonstrate a clinical application, we show that neutrophil elastase in sputum from cystic fibrosis patients hydrolyze the peptide-GMR substrate, and the cleavage rate strongly correlates with a traditional fluorogenic substrate. This innovative assay addresses challenges associated with traditional enzyme measurement techniques, providing a promising tool for real-time quantification of hydrolase activities in diverse biological contexts.

Point-of-care lung ultrasound predicts hyperferritinemia and hospitalization, but not elevated troponin in SARS-CoV-2 viral pneumonitis in children

SARS-CoV-2 often causes viral pneumonitis, hyperferritinemia, elevations in D-dimer, lactate dehydrogenase (LDH), transaminases, troponin, CRP, and other inflammatory markers. Lung ultrasound is increasingly used to diagnose and stratify viral pneumonitis severity. We retrospectively reviewed 427 visits in patients aged 14 days to 21 years who had had a point-of-care lung ultrasound in our pediatric emergency department from 30/November/2019 to 14/August/2021. Lung ultrasounds were categorized using a 6-point ordinal scale. Lung ultrasound abnormalities predicted increased hospitalization with a threshold effect. Increasingly abnormal laboratory values were associated with decreased discharge from the ED and increased admission to the ward and ICU. Among patients SARS-CoV-2 positive patients ferritin, LDH, and transaminases, but not CRP or troponin were significantly associated with abnormalities on lung ultrasound and also with threshold effects. This effect was not demonstrated in SARS-CoV-2 negative patients. D-Dimer, CRP, and troponin were sometimes elevated even when the lung ultrasound was normal.

Mitochondrial oxidative stress, mitochondrial ROS storms in long COVID pathogenesis

Significance

This review discusses the coronavirus disease 2019 (COVID-19) pathophysiology in the context of diabetes and intracellular reactions by COVID-19, including mitochondrial oxidative stress storms, mitochondrial ROS storms, and long COVID.

Recent advances

The long COVID is suffered in ~10% of the COVID-19 patients. Even the virus does not exist, the patients suffer the long COVID for even over a year, This disease could be a mitochondria dysregulation disease.

Critical issues

Patients who recover from COVID-19 can develop new or persistent symptoms of multi-organ complications lasting weeks or months, called long COVID. The underlying mechanisms involved in the long COVID is still unclear. Once the symptoms of long COVID persist, they cause significant damage, leading to numerous, persistent symptoms.

Future directions

A comprehensive map of the stages and pathogenetic mechanisms related to long COVID and effective drugs to treat and prevent it are required, which will aid the development of future long COVID treatments and symptom relief.

Effect of vaccination status on CORADS and computed tomography severity score in hospitalized COVID-19 patients: A retrospective study

BACKGROUND

The coronavirus disease 2019 (COVID-19) pandemic is continuing. The disease most commonly affects the lungs. Since the beginning of the pandemic thorax computed tomography (CT) has been an indispensable imaging method for diagnosis and follow-up. The disease is tried to be controlled with vaccines. Vaccination reduces the possibility of a severe course of the disease.

AIM

The aim of this study is to investigate whether the vaccination status of patients hospitalized due to COVID-19 has an effect on the CT severity score (CT-SS) and CORADS score obtained during hospitalization.

METHODS

The files of patients hospitalized between April 1, 2021 and April 1, 2022 due to COVID-19 were retrospectively reviewed. A total of 224 patients who were older than 18 years of age, whose vaccination status was accessible, whose severe acute respiratory syndrome coronavirus 2 polymerase chain reaction result was positive, and who had a Thorax CT scan during hospitalization were included in the study.

RESULTS

Among the patients included in the study, 52.2% were female and the mean age was 61.85 years. The patients applied to the hospital on the average 7th day of their complaints. While 63 patients were unvaccinated (Group 1), 20 were vaccinated with a single dose of CoronaVac (Group 2), 24 with a single dose of BioNTech (Group 3), 38 with 2 doses of CoronaVac (Group 4), 40 with 2 doses of BioNTech (Group 5), and 39 with 3 doses of vaccine (2 doses of CoronaVac followed by a single dose of BioNTech, Group 6). CT-SS ranged from 5 to 23, with a mean of 12.17.CT-SS mean of the groups were determined as 14.17, 13.35, 11.58, 10.87, 11.28, 10.85, respectively. Accordingly, as a result of the comparisons between the groups, the CT-SS levels of the unvaccinated patients found to be significantly higher than the other groups. As the vaccination rates increased, the rate of typical COVID-19 findings on CT was found to be significantly lower.

CONCLUSION

Increased vaccination rates in COVID-19 patients reduce the probability of typical COVID-19 symptoms in the lungs. It also reduces the risk of severe disease and decreases CT Severity Scores. This may lead to a loss of importance of Thorax CT in the diagnosis of COVID-19 pneumonia as the end of the pandemic approaches.

Severity of oxidative stress as a hallmark in COVID-19 patients

INTRODUCTION

Understanding the mechanisms and identifying effective treatments for the COVID-19 outbreak are imperative. Therefore, this study aimed to assess the antioxidant status and oxidative stress parameters as potential pivotal mechanisms in asymptomatic, non-severe, and severe COVID-19 patients.

METHODS

This study is a case-control study that was performed on patients referred to the Persian Gulf Martyrs Hospital of Bushehr University of Medical Sciences, Bushehr, Iran, from May 2021 to September 2021. A total of 600 COVID-19 patients (non-severe and severe group) and 150 healthy volunteers of the same age and sex were selected during the same period. On the first day of hospitalization, 10 ml of venous blood was taken from subjects. Then, hematological, biochemical, serological, antioxidant and oxidative stress parameters were determined.

RESULTS

Our results indicated that ESR, CRP, AST, ALT, and LDH significantly augmented in the severe group as compared to the non-severe and normal groups (P ≤ 0.05). It was observed that the levels of FRAP, G6PD activity, and SOD activity significantly reduced in the non-severe patients in comparison with the severe and normal groups (P ≤ 0.05). We found that MDA content and NO metabolite markedly increased in severe patients as compared to the non-severe group.

CONCLUSIONS

Taken together, it seems that the balance between antioxidants and oxidants was disturbed in COVID-19 patients in favor of oxidant markers. In addition, this situation caused more aggravation in severe patients as compared to the non-severe group.

Role of biomarkers in prognostication of moderate and severe COVID-19 cases

Background

COVID-19 pandemic demanded upgrading of laboratory medicine to limit morbidity, disability and mortality from moderate and severe SARS-COV-2 infections.

Objective

To assess among moderate and severe COVID-19 patients, C-reactive protein (CRP), procalcitonin (PCT), ferritin, D-dimer, interleukin 6 (IL-6), lactate dehydrogenase (LDH), total and differential leucocyte count (TLC and DLC), neutrophil-to-lymphocyte ratio (NLR), absolute platelet count (APC), prothrombin time (PT), activated partial thromboplastin time (APTT) and international normalized ratio (INR) to find their interdependence and role in prognosis.

Methods

This open label analytical cross-sectional noninterventional study evaluated array of independent biochemical, haematological and coagulopathy markers, viz. CRP, PCT, ferritin, D-dimer, IL-6, LDH, TLC, DLC, NLR, absolute platelet count, PT, APTT and INR on consecutive 100 patients with diagnosis of moderate and severe COVID-19 from July to August 2021.

Results

In our study, on consecutive designated 100 cases (55 cases moderate and 45 cases severe), more severity were reported as the age progressed; gender difference was not noted. Among independent markers, CRP, PCT, ferritin, D-dimer, IL-6 and LDH had statistically significant relation in comparison with severity of the disease as Chi-square calculated value (P < 0.05). TLC, DLC and APC showed no significant relation in comparison with severity of the disease; NLR had highly significant relation. PT showed significant relation in comparison with severity, though APTT and INR did not show significant relation.

Conclusion

Our research group felt that CRP, PCT, ferritin, D-dimer, IL-6, LDH and NLR should be in included in clinical practice guidelines to prognosticate COVID-19 cases. Furthermore, translational researches are needed at all levels of healthcare to improve validity for practices of primary care physicians.

Epidemiological and laboratory characteristics of Omicron infection in a general hospital in Guangzhou: a retrospective study

The COVID-19 pandemic caused by SARS-CoV-2 has emerged as a major global public health concern. In November 2022, Guangzhou experienced a significant outbreak of Omicron. This study presents detailed epidemiological and laboratory data on Omicron infection in a general hospital in Guangzhou between December 1, 2022, and January 31, 2023. Out of the 55,296 individuals tested, 12,346 were found to be positive for Omicron. The highest prevalence of positive cases was observed in the 20 to 39 age group (24.6%), while the lowest was in children aged 0 to 9 years (1.42%). Females had a higher incidence of infection than males, accounting for 56.6% of cases. The peak time of Omicron infection varied across different populations. The viral load was higher in older adults and children infected with Omicron, indicating age-related differences. Spearman's rank correlation analysis revealed positive correlations between Ct values and laboratory parameters in hospitalized patients with Omicron infection. These parameters included CRP (rs = 0.059, p = 0.009), PT (rs = 0.057, p = 0.009), INR (rs = 0.055, p = 0.013), AST (rs = 0.067, p = 0.002), LDH (rs = 0.078, p = 0.001), and BNP (rs = 0.063, p = 0.014). However, EO (Eosinophil, rs = -0.118, p < 0.001), BASO (basophil, rs = -0.093, p < 0.001), and LY (lymphocyte, rs = -0.069, p = 0.001) counts showed negative correlations with Ct values. Although statistically significant, the correlation coefficients between Ct values and these laboratory indices were very low. These findings provide valuable insights into the epidemiology of Omicron infection, including variations in Ct values across gender and age groups. However, caution should be exercised when utilizing Ct values in clinical settings for evaluating Omicron infection.

A comparative NMR-based metabolomics study of lung parenchyma of severe COVID-19 patients

COVID-19 was the most significant infectious-agent-related cause of death in the 2020-2021 period. On average, over 60% of those admitted to ICU facilities with this disease died across the globe. In severe cases, COVID-19 leads to respiratory and systemic compromise, including pneumonia-like symptoms, acute respiratory distress syndrome, and multiorgan failure. While the upper respiratory tract and lungs are the principal sites of infection and injury, most studies on the metabolic signatures in COVID-19 patients have been carried out on serum and plasma samples. In this report we attempt to characterize the metabolome of lung parenchyma extracts from fatal COVID-19 cases and compare them with that from other respiratory diseases. Our findings indicate that the metabolomic profiles from fatal COVID-19 and non-COVID-19 cases are markedly different, with the former being the result of increased lactate and amino acid metabolism, altered energy pathways, oxidative stress, and inflammatory response. Overall, these findings provide additional insights into the pathophysiology of COVID-19 that could lead to the development of targeted therapies for the treatment of severe cases of the disease, and further highlight the potential of metabolomic approaches in COVID-19 research.

Lactate Dehydrogenase and Hemorrhagic Stroke During Extracorporeal Membrane Oxygenation for COVID-19

PURPOSE

Hemorrhagic stroke (HS) is a devastating complication during extracorporeal membrane oxygenation (ECMO) but markers of risk stratification during COVID-19 are unknown. Lactate dehydrogenase (LDH) is a readily available biomarker of cell injury and permeability. We sought to determine whether an elevated LDH before ECMO placement is related to the occurrence of HS during ECMO for COVID-19.

METHODS

Adult patients with COVID-19 requiring ECMO between March 2020 and February 2022 were included. LDH values prior to ECMO placement were captured. Patients were categorized into high (> 750 U/L) or low (≤ 750 U/L) LDH groups. Multivariable regression modeling was used to determine the association between LDH and HS during ECMO.

RESULTS

There were 520 patients that underwent ECMO placement in 17 centers and 384 had an available LDH. Of whom, 122 (32%) had a high LDH. The overall incidence of HS was 10.9%, and patients with high LDH had a higher incidence of HS than those with low LDH level (17% vs 8%, p = 0.007). At 100 days, the probability of a HS was 40% in the high LDH group and 23% in those with a low LDH, p = 0.002. After adjustment for clinical covariates, high LDH remained associated with subsequent HS (aHR: 2.64, 95% CI 1.39-4.92). Findings were similar when restricting to patients supported by venovenous ECMO only.

CONCLUSION

Elevated LDH prior to ECMO cannulation is associated with a higher incidence of HS during device support. LDH can risk stratify cases for impending cerebral bleeding during ECMO.

Changes and Rate of Change in Neutrophil-Lymphocyte Ratio (∆NLR) as an Early Prognostic Marker for the Severity of Outcomes in Patients With COVID-19 and Its Applicability in Other Viral and Bacterial Diseases

INTRODUCTION

COVID-19 is a global pandemic that has spread rapidly and resulted in numerous deaths worldwide. Many inflammatory markers such as neutrophil-lymphocyte ratio (NLR), D-dimer, serum ferritin, C-reactive protein (CRP), and interleukin-6 (IL-6) were used for the diagnosis and prognosis of COVID-19.

METHODS

We have proposed using Delta NLR (0-48 hours) (∆NLR) as an early diagnostic marker for COVID-19 and other inflammatory disorders. We have created a prediction model based on six variables: overall severity, death, shifting to the ICU, length of stay, oxygen requirement, and ventilator support. Prediction models help us prepare for future pandemics through early diagnosis and management.

RESULTS

A total of 1,865 patient records were retrieved from the database. The final sample available for analysis was 461. Change in NLR or ∆NLR was significant for all the models (except for length of stay) created by logistic regression.

CONCLUSION

An independent predictor of the poor prognosis of COVID-19 is the severity of the disease in the initial one or two days. ∆NLR is a unique marker, and its scope of use in other disorders' prognoses must be further researched. The prediction models also help us in decision-making strategies and also prepare us for future pandemics.

Oxygen Requirement in Overweight/Obese Kidney Transplant Recipients with COVID-19: An Observational Cohort Study

INTRODUCTION

Obesity is one of the components of the cardiometabolic syndrome that contributes to COVID-19 progression and mortality. Immunosuppressed individuals are at greater risk of the COVID-19 burden. Therefore, we sought to investigate the impact of the combination of overweight/obesity and kidney transplant on oxygen (O2) requirements in the COVID-19 setting.

METHODS

Retrospective analysis of 284 kidney transplant recipients (KTRs) from March/2020 to August/2020 in a single center. We investigated the risk factors associated with O2 requirements in overweight/obese KTRs.

RESULTS

Overall, 65.1% had a BMI (body mass index) ≥ 25 kg/m2, 52.4% were male, the mean age was 53.3 ± 11 years old, 78.4% had hypertension, and 41.1% had diabetes mellitus. BMI was an independent risk factor for O2 requirements (OR = 1.07, p = 0.02) alongside age, lymphopenia, and hyponatremia. When overweight/obese KTRs were older, smokers, they presented higher levels of lactate dehydrogenase (LDH), and lower levels of estimated glomerular filtration rate (eGFR), lymphocytes, and sodium at admission, and they needed O2 more often.

CONCLUSION

Being overweight/obese is associated with greater O2 requirements in KTRs, in particular in older people and smokers, with worse kidney allograft functions, more inflammation, and lower sodium levels. Therefore, the early identification of factors that predict a worse outcome in overweight/obese KTRs affected by COVID-19 contributes to risk stratification and therapeutic decisions.

Serum LDH levels may predict poor neurological outcome after aneurysmal subarachnoid hemorrhage

INTRODUCTION

Serum lactate dehydrogenase (LDH) levels are often elevated in cardiovascular diseases. Their prognostic role after subarachnoid hemorrhage (SAH) remains poorly evaluated.

METHODS

This is a retrospective single-center study of patients with non-traumatic SAH admitted to the intensive care unit (ICU) of an University Hospital from 2007 to 2022. Exclusion criteria were pregnancy and incomplete medical records or follow-up data. Baseline information, clinical data, radiologic data, the occurrence of neurological complications as well as serum LDH levels during the first 14 days of ICU stay were collected. Unfavorable neurological outcome (UO) at 3 months was defined as a Glasgow Outcome Scale of 1-3.

RESULTS

Five hundred and forty-seven patients were included; median serum LDH values on admission and the highest LDH values during the ICU stay were 192 [160-230] IU/L and 263 [202-351] IU/L, respectively. The highest LDH value was recorded after a median of 4 [2-10] days after ICU admission. LDH levels on admission were significantly higher in patients with UO. When compared with patients with favorable outcome (FO), patients with UO had higher serum LDH values over time. In the multivariate logistic regression model, the highest LDH value over the ICU stay (OR 1.004 [95% CI 1.002 - 1.006]) was independently associated with the occurrence of UO; the area under the receiving operator (AUROC) curve for the highest LDH value over the ICU stay showed a moderate accuracy to predict UO (AUC 0.76 [95% CI 0.72-0.80]; p < 0.001), with an optimal threshold of > 272 IU/L (69% sensitivity and 74% specificity).

CONCLUSIONS

The results in this study suggest that high serum LDH levels are associated with the occurrence of UO in SAH patients. As a readily and available biomarker, serum LDH levels should be evaluated to help with the prognostication of SAH patients.

A metabolic blueprint of COVID-19 and long-term vaccine efficacy

Viruses are obligatory protein-coated units and often utilize the metabolic functions of the cells they infect. Viruses hijack cellular metabolic functions and cause consequences that can range from minor to devastating, as we have all witnessed during the COVID-19 pandemic. For understanding the virus-driven pathogenesis and its implications on the host, the cellular metabolism needs to be elucidated. How SARS-CoV-2 triggers metabolic functions and rewires the metabolism remains unidentified but the implications of the metabolic patterns are under investigation by several researchers. In this review, we have described the SARS-CoV-2-mediated metabolic alterations from in vitro studies to metabolic changes reported in victims of COVID-19. We have also discussed potential therapeutic targets to diminish the viral infection and suppress the inflammatory response, with respect to evidenced studies based on COVID-19 research. Finally, we aimed to explain how we could extend vaccine-induced immunity in people by targeting the immunometabolism.

Severity of Illness Scores and Biomarkers for Prognosis of Patients with Coronavirus Disease 2019

The spectrum of disease severity and the insidiousness of clinical presentation make it difficult to recognize patients with coronavirus disease 2019 (COVID-19) at higher risk of worse outcomes or death when they are seen in the early phases of the disease. There are now well-established risk factors for worse outcomes in patients with COVID-19. These should be factored in when assessing the prognosis of these patients. However, a more precise prognostic assessment in an individual patient may warrant the use of predictive tools. In this manuscript, we conduct a literature review on the severity of illness scores and biomarkers for the prognosis of patients with COVID-19. Several COVID-19-specific scores have been developed since the onset of the pandemic. Some of them are promising and can be integrated into the assessment of these patients. We also found that the well-known pneumonia severity index (PSI) and CURB-65 (confusion, uremia, respiratory rate, BP, age ≥ 65 years) are good predictors of mortality in hospitalized patients with COVID-19. While neither the PSI nor the CURB-65 should be used for the triage of outpatient versus inpatient treatment, they can be integrated by a clinician into the assessment of disease severity and can be used in epidemiological studies to determine the severity of illness in patient populations. Biomarkers also provide valuable prognostic information and, importantly, may depict the main physiological derangements in severe disease. We, however, do not advocate the isolated use of severity of illness scores or biomarkers for decision-making in an individual patient. Instead, we suggest the use of these tools on a case-by-case basis with the goal of enhancing clinician judgment.

IFNL3/4 polymorphisms as a two-edged sword: An association with COVID-19 outcome

Coronavirus Disease 2019 (COVID-19) has been ranked among the most fatal infectious diseases worldwide, with host's immune response significantly affecting the prognosis. With an aim to timely predict the most likely outcome of SARS-CoV-2 infection, we investigated the association of IFNL3 and IFNL4 polymorphisms, as well as other potentially relevant factors, with the COVID-19 mortality. This prospective observational case-control study involved 178 COVID-19 patients, hospitalized at Corona Center or Clinic for Infectious Diseases of University Clinical Centre Kragujevac, Serbia, followed up until hospital discharge or in-hospital death. Demographic and clinical data on all participants were retrieved from the electronic medical records, and TaqMan assays were employed in genotyping for IFNL3 and IFNL4 single nucleotide polymorphisms (SNPs), namely rs12980275, rs8099917, rs12979860, and rs368234815. 21.9% and 65.0% of hospitalized and critically ill COVID-19 patients, respectively, died in-hospital. Multivariable logistic regression analysis revealed increased Charlson Comorbidity Index (CCI), N/L, and lactate dehydrogenase (LDH) level to be associated with an increased likelihood of a lethal outcome. Similarly, females and the carriers of at least one variant allele of IFNL3 rs8099917 were almost 36-fold more likely not to survive SARS-CoV-2 infection. On the other hand, the presence of at least one ancestral allele of IFNL4 rs368234815 decreased more than 15-fold the likelihood of mortality from COVID-19. Our results suggest that, in addition to LDH level, N/L ratio, and CCI, IFNL4 rs368234815 and IFNL3 rs8099917 polymorphisms, but also patients' gender, significantly affect the outcome of COVID-19.

Increased lactate dehydrogenase reflects the progression of COVID-19 pneumonia on chest computed tomography and predicts subsequent severe disease

Chest computed tomography (CT) is effective for assessing the severity of coronavirus disease 2019 (COVID-19). However, the clinical factors reflecting the disease progression of COVID-19 pneumonia on chest CT and predicting a subsequent exacerbation remain controversial. We conducted a retrospective cohort study of 450 COVID-19 patients. We used an automated image processing tool to quantify the COVID-19 pneumonia lesion extent on chest CT at admission. The factors associated with the lesion extent were estimated by a multiple regression analysis. After adjusting for background factors by propensity score matching, we conducted a multivariate Cox proportional hazards analysis to identify factors associated with severe disease after admission. The multiple regression analysis identified, body-mass index (BMI), lactate dehydrogenase (LDH), C-reactive protein (CRP), and albumin as continuous variables associated with the lesion extent on chest CT. The standardized partial regression coefficients for them were 1.76, 2.42, 1.54, and 0.71. The multivariate Cox proportional hazards analysis identified LDH (hazard ratio, 1.003; 95% confidence interval, 1.001-1.005) as a factor independently associated with the development of severe COVID-19 pneumonia. Increased serum LDH at admission may be useful in real-world clinical practice for the simple screening of COVID-19 patients at high risk of developing subsequent severe disease.

Dose response relationship between D-dimer level and mortality in critically ill COVID-19 patients: a retrospective observational study

BACKGROUND

Coronavirus disease 2019 (COVID-19) is a global pandemic. Coagulopathy is one of the most common complications characterized by increased D-dimer level. We aimed to investigate the dose-response relationship between elevated D-dimer level and mortality in critically ill COVID-19 patients.

METHODS

This was a retrospective observational study in 259 critically ill COVID-19 patients requiring intensive care unit admission between March and December 2020. We compared the mortality rate between patients with and without elevated D-dimer. Receiver operating characteristic (ROC) curve analysis, Fagan's nomogram, and dose-response relationship were performed to determine the association between D-dimer level and mortality.

RESULTS

Overall mortality rate was 40.9% (106 patients). Median D-dimer level was higher in non-survivor group (10,170 ng/mL vs 4,050 ng/mL, p=0.028). The association remained significant after multivariate logistic regression analysis (p=0.046). The optimal cut-off for D-dimer level to predict mortality from ROC curve analysis was 9,020 ng/mL (OR (odds ratio) 3.73 [95% CI (confidence interval) 1.91 - 7.28], p<0.001). D-dimer level >9,020 ng/mL confers 67% posterior probability of mortality and D-dimer level <9,020 ng/mL had 35% probability of mortality.

CONCLUSIONS

There was a non-linear dose-response relationship between D-dimer level and mortality with P nonlinearity of 0.004. D-dimer level was associated with mortality in critically ill COVID-19 patients in the non-linear dose-response relationship.

Utility of laboratory and immune biomarkers in predicting disease progression and mortality among patients with moderate to severe COVID-19 disease at a Philippine tertiary hospital

Purpose

This study was performed to determine the clinical biomarkers and cytokines that may be associated with disease progression and in-hospital mortality in a cohort of hospitalized patients with RT-PCR confirmed moderate to severe COVID-19 infection from October 2020 to September 2021, during the first wave of COVID-19 pandemic before the advent of vaccination.

Patients and methods

Clinical profile was obtained from the medical records. Laboratory parameters (complete blood count [CBC], albumin, LDH, CRP, ferritin, D-dimer, and procalcitonin) and serum concentrations of cytokines (IL-1β, IL-2, IL-4, IL-6, IL-8, IL-10, IL-18, IFN-γ, IP-10, TNF-α) were measured on Days 0-3, 4-10, 11-14 and beyond Day 14 from the onset of illness. Regression analysis was done to determine the association of the clinical laboratory biomarkers and cytokines with the primary outcomes of disease progression and mortality. ROC curves were generated to determine the predictive performance of the cytokines.

Results

We included 400 hospitalized patients with COVID-19 infection, 69% had severe to critical COVID-19 on admission. Disease progression occurred in 139 (35%) patients, while 18% of the total cohort died (73 out of 400). High D-dimer >1 µg/mL (RR 3.5 95%CI 1.83-6.69), elevated LDH >359.5 U/L (RR 1.85 95%CI 1.05-3.25), lymphopenia (RR 1.91 95%CI 1.14-3.19), and hypoalbuminemia (RR 2.67, 95%CI 1.05-6.78) were significantly associated with disease progression. High D-dimer (RR 3.95, 95%CI 1.62-9.61) and high LDH (RR 5.43, 95%CI 2.39-12.37) were also significantly associated with increased risk of in-hospital mortality. Nonsurvivors had significantly higher IP-10 levels at 0 to 3, 4 to 10, and 11 to 14 days from illness onset (p<0.01), IL-6 levels at 0 to 3 days of illness (p=0.03) and IL-18 levels at days 11-14 of illness (p<0.001) compared to survivors. IP-10 had the best predictive performance for disease progression at days 0-3 (AUC 0.81, 95%CI: 0.68-0.95), followed by IL-6 at 11-14 days of illness (AUC 0.67, 95%CI: 0.61-0.73). IP-10 predicted mortality at 11-14 days of illness (AUC 0.77, 95%CI: 0.70-0.84), and IL-6 beyond 14 days of illness (AUC 0.75, 95%CI: 0.68-0.82).

Conclusion

Elevated D-dimer, elevated LDH, lymphopenia and hypoalbuminemia are prognostic markers of disease progression. High IP-10 and IL-6 within the 14 days of illness herald disease progression. Additionally, elevated D-dimer and LDH, high IP-10, IL-6 and IL-18 were also associated with mortality. Timely utilization of these biomarkers can guide clinical monitoring and management decisions for COVID-19 patients in the Philippines.

Early prediction of COVID-19 outcome using artificial intelligence techniques and only five laboratory indices

We aimed to develop a prediction model for intensive care unit (ICU) hospitalization of Coronavirus disease-19 (COVID-19) patients using artificial neural networks (ANN). We assessed 25 laboratory parameters at first from 248 consecutive adult COVID-19 patients for database creation, training, and development of ANN models. We developed a new alpha-index to assess association of each parameter with outcome. We used 166 records for training of computational simulations (training), 41 for documentation of computational simulations (validation), and 41 for reliability check of computational simulations (testing). The first five laboratory indices ranked by importance were Neutrophil-to-lymphocyte ratio, Lactate Dehydrogenase, Fibrinogen, Albumin, and D-Dimers. The best ANN based on these indices achieved accuracy 95.97%, precision 90.63%, sensitivity 93.55%. and F1-score 92.06%, verified in the validation cohort. Our preliminary findings reveal for the first time an ANN to predict ICU hospitalization accurately and early, using only 5 easily accessible laboratory indices.

Plasma-induced nanoparticle aggregation for stratifying COVID-19 patients according to disease severity

Stratifying patients according to disease severity has been a major hurdle during the COVID-19 pandemic. This usually requires evaluating the levels of several biomarkers, which may be cumbersome when rapid decisions are required. In this manuscript we show that a single nanoparticle aggregation test can be used to distinguish patients that require intensive care from those that have already been discharged from the intensive care unit (ICU). It consists of diluting a platelet-free plasma sample and then adding gold nanoparticles. The nanoparticles aggregate to a larger extent when the samples are obtained from a patient in the ICU. This changes the color of the colloidal suspension, which can be evaluated by measuring the pixel intensity of a photograph. Although the exact factor or combination of factors behind the different aggregation behavior is unknown, control experiments demonstrate that the presence of proteins in the samples is crucial for the test to work. Principal component analysis demonstrates that the test result is highly correlated to biomarkers of prognosis and inflammation that are commonly used to evaluate the severity of COVID-19 patients. The results shown here pave the way to develop nanoparticle aggregation assays that classify COVID-19 patients according to disease severity, which could be useful to de-escalate care safely and make a better use of hospital resources.

Global Hemostasis Potential in COVID-19 Positive Patients Performed on St-Genesia Show Hypercoagulable State

BACKGROUND

At the dawn of the pandemic, severe forms of COVID-19 were often complicated by thromboembolisms. However, routine laboratory tests cannot be used to predict thromboembolic events. The objective of this study was to investigate the potential value of the thrombin generation test (TGT) in predicting hypercoagulability and thrombotic risk in the aforementioned set of patients.

METHODS

The study panel comprised 52 patients divided into two groups (26 COVID-19 positive and 26 COVID-19 negative); COVID-19-positive patients were further grouped in "severe" (n = 11) and "non-severe" (n = 15) categories based on clinical criteria. The routine blood tests and TGT of these patients were retrospectively analyzed.

RESULTS

All 26 COVID-19-positive patients showed decreased lymphocyte, monocyte and basophil counts and increased lactate dehydrogenase (LDH), aspartate aminotransferase (AST), and alanine transaminase (ALT) compared with control patients. Conversely, we did not observe statistically significant differences between severe and non-severe patients despite anecdotal variations in the distribution patterns. TGT without thrombomodulin (TM) addition showed statistically significant differences in the thrombin peak heights between COVID-19-positive and negative patients. After addition of TM, peak height, Endogenous Thrombin Potential (ETP) and velocity index were increased in all COVID-19-positive patients while the percentage of inhibition of ETP was reduced. These trends correlated with the severity of disease, showing a greater increase in peak height, ETP, velocity index and a drastic reduction in the percentage of ETP inhibition in more severely affected patients.

CONCLUSIONS

Our data suggest that all COVID-19 patients harbor a hypercoagulable TGT profile and that this is further pronounced in severely affected patients.

Assessment of inflammatory markers and their association with disease mortality in severe COVID-19 patients of tertiary care hospital in South India

Background

COVID-19 infection involves a complex interplay of the immunological and inflammatory responses. Low blood-oxygen levels have been a hallmark in COVID-19 patients. The lung tissue damage infiltered by the viral-mediated inflammation decreases oxygen saturation to cause silent hypoxia and cell death. This study aimed to evaluate the association of inflammatory biomarkers with oxygen saturation (SpO₂) and mortality in severe COVID-19 patients.

Methods

A total of 190 severe COVID-19 patients were included in this study after confirmed by the RT-PCR assay. The laboratory tests were performed for biochemical assessment. Serum levels of C-reactive protein (CRP), lactate dehydrogenase (LDH), and ferritin were determined and compared between survivors and nonsurvivors using independent sample t-test. The correlation of these inflammatory markers was studied using Spearman’s correlation, and their association with mortality was studied using logistic regression.

Results

All the COVID-19 patients were severe with SpO₂< 90% and respiratory rate > 30/min. While the serum levels of CRP, LDH, ferritin, aspartate transaminase (AST), urea, and random blood sugar (RBS) were elevated, hemoglobin (Hb) and SpO₂ levels were reduced in COVID-19 patients. LDH and ferritin levels were significantly higher in nonsurvivors compared to survivors with p values of 0.001 and 0.022 respectively. Spearman’s correlation showed a significant correlation of the inflammatory markers with SpO₂, serum electrolytes (potassium, chloride), liver enzymes (AST and alanine transaminase (ALT)), and markers of kidney damage (urea, creatinine).

Conclusion

Inflammatory markers could effectively discriminate the risk of mortality in severe COVID-19 patients. As CRP, LDH, and ferritin levels determine the tissue oxygen availability, they seem to be valuable biomarkers in the prognosis of COVID-19.

Biosensors based detection of novel biomarkers associated with COVID-19: Current progress and future promise

The pandemic situation of COVID-19 has caused global alarm in health care, devastating loss of lives, strangled economy, and paralysis of normal livelihood. The high inter-individual transmission rate created havoc in the global community. Although tremendous efforts are pitching in from across the globe to understand this disease, the clinical features seemed to have a wide range including fever, cough, and fatigue are the prominent features. Congestion, rhinorrhea, sore throat, and diarrhea are other less common features observed. The challenge of this disease lies in the difficulty in maneuvering the clinical course causing severe complications. One of the major causative factors for multi-organ failure in patients with severe COVID-19 complications is systemic vasculitis and cytokine-mediated coagulation disorders. Hence, effective markers trailing the disease severity and disease prognosis are urgently required for prompt medical treatment. In this review article, we have emphasized currently identified inflammatory, hematological, immunological, and biochemical biomarkers of COVID-19. We also discussed currently available biosensors for the detection of COVID-19-associated biomarkers & risk factors and the detection methods as well as their performances. These could be effective tools for rapid and more promising diagnoses in the current pandemic situation. Effective biomarkers and their rapid, scalable, & sensitive detection might be beneficial for the prevention of serious complications and the clinical management of the disease.

Severity and Mortality Predictors of COVID-19 Patients with Thrombotic Events-Evidence from the "COVID-One" Hospital in Albania

COVID-19 vaccination leads to lower infection, morbidity, and mortality rates. However, COVID-19 infection leads to the development of coagulopathy-related manifestations in the form of both venous and arterial thromboembolism. This study aimed to assess the severity and mortality predictors of COVID-19 patients with thrombotic events in hospitalized patients in Albania. This is a retrospective study conducted in the “Mother Tereza” University Hospital of Tirana. Data were retrieved from the electronic databases of the hospital and only COVID-19 cases admitted to the infectious department during August−December 2020 were selected. Patients who, at admission, had a C-reactive protein (CRP) (mg/L) more than double and a D-dimer (ng/mL) more than triple according to international standards were included in the study. We performed univariate and multivariable logistic regression analysis, calculating unadjusted and adjusted odds ratios (ORs). A p-value < 0.05 was considered statistically significant. The study population included 60 hospitalized persons with a mean age of 64.4 years. Increased lactate dehydrogenase (LDH) (OR = 2.93; 95% CI = 0.82−10.42, p-value = 0.1) and increased creatine kinase (CK) (OR = 2.17; 95% CI = 0.63−7.46, p-value = 0.22) were related with increased probability of death. Moreover, a decreased number of lymphocytes was associated with increased mortality but with no statistical significance (OR = 0.40; 95% CI = 0.11−1.40, p-value = 0.15). The survival rate was higher for patients without comorbidities (p = 0.045). These results could serve as a baseline and as a reference for healthcare personnel who provides services to hospitalized patients with COVID-19. Further studies should take into consideration the vaccination of the population as well as including more hospitals and patients.

Effects of COVID-19 on the liver: The experience of a single center

BACKGROUND

The coronavirus disease 2019 (COVID-19) was perhaps the most severe global health crisis in living memory. Alongside respiratory symptoms, elevated liver enzymes, abnormal liver function, and even acute liver failure were reported in patients suffering from severe acute respiratory disease coronavirus 2 pneumonia. However, the precise triggers of these forms of liver damage and how they affect the course and outcomes of COVID-19 itself remain unclear.

AIM

To analyze the impact of liver enzyme abnormalities on the severity and outcomes of COVID-19 in hospitalized patients.

METHODS

In this study, 684 depersonalized medical records from patients hospitalized with COVID-19 during the 2020-2021 period were analyzed. COVID-19 was diagnosed according to the guidelines of the National Institutes of Health (2021). Patients were assigned to two groups: those with elevated liver enzymes (Group 1: 603 patients), where at least one out of four liver enzymes were elevated (following the norm of hospital laboratory tests: alanine aminotransferase (ALT) ≥ 40, aspartate aminotransferase (AST) ≥ 40, gamma-glutamyl transferase ≥ 36, or alkaline phosphatase ≥ 150) at any point of hospitalization, from admission to discharge; and the control group (Group 2: 81 patients), with normal liver enzymes during hospitalization. COVID-19 severity was assessed according to the interim World Health Organization guidance (2022). Data on viral pneumonia complications, laboratory tests, and underlying diseases were also collected and analyzed.

RESULTS

In total, 603 (88.2%) patients produced abnormal liver test results. ALT and AST levels were elevated by a factor of less than 3 in 54.9% and 74.8% of cases with increased enzyme levels, respectively. Patients in Group 1 had almost double the chance of bacterial viral pneumonia complications [odds ratio (OR) = 1.73, P = 0.0217], required oxygen supply more often, and displayed higher biochemical inflammation indices than those in Group 2. No differences in other COVID-19 complications or underlying diseases were observed between groups. Preexisting hepatitis of a different etiology was rarely documented (in only 3.5% of patients), and had no impact on the severity of COVID-19. Only 5 (0.73%) patients experienced acute liver failure, 4 of whom died. Overall, the majority of the deceased patients (17 out of 20) had elevated liver enzymes, and most were male. All deceased patients had at least one underlying disease or combination thereof, and the deceased suffered significantly more often from heart diseases, hypertension, and urinary tract infections than those who made recoveries. Alongside male gender (OR = 1.72, P = 0.0161) and older age (OR = 1.02, P = 0.0234), diabetes (OR = 3.22, P = 0.0016) and hyperlipidemia (OR = 2.67, P = 0.0238), but not obesity, were confirmed as independent factors associated with more a severe COVID-19 infection in our cohort.

CONCLUSION

In our study, the presence of liver impairment allows us to predict a more severe inflammation with a higher risk of bacterial complication and worse outcomes of COVID-19. Therefore, patients with severe disease forms should have their liver tests monitored regularly and their results should be considered when selecting treatment to avoid further liver damage or even insufficiency.

Predictors of New-Onset Diabetes in Hospitalized Patients with SARS-CoV-2 Infection

The pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is one of the world's most disruptive health crises. The presence of diabetes plays an important role in the severity of the infection, and a rise in newly diagnosed diabetes cases has been identified. The aim of this retrospective study was to determine the incidence of new-onset diabetes (NOD) and predictive factors with their cut-off values for patients hospitalized with COVID-19. All patients (n = 219) hospitalized for COVID-19 during three consecutive months were included. NOD was diagnosed in 26.48% of patients. The severity of the infection, hospital admission values for fasting plasma glucose, lactate dehydrogenase (LDH), PaO2/FiO2 ratio, the peak values for leucocytes, neutrophils, C-reactive protein, triglycerides, and the need for care in the intensive care unit were predictors for the occurrence of NOD in univariate analysis, while only LDH level remained a significant predictor in the multivariable analysis. In conclusion, the results of the study showed a high incidence of NOD in patients hospitalized with COVID-19 and identified LDH levels at hospital admission as a significant predictor of NOD during SARS-CoV-2 infection. However, the persistence of NOD after the COVID-19 infection is not known, therefore, the results must be interpreted with caution.

Pulmonary Involvement in SARS-CoV-2 Infection Estimates Myocardial Injury Risk

Background and Objectives: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection represents a pathology with primary pulmonary involvement and multisystemic impact, including cardiovascular injuries. The present study aimed to assess the value of clinical, biochemical, and imaging factors in COVID-19 patients in determining the severity of myocardial involvement, and to create a model that can be used toevaluate myocardial injury risk based on clinical, biochemical and imaging factors. Materials and Methods: We performed an observational cohort study on 150 consecutive patients, evaluating their age, sex, hospitalization period, peripheral oxygen saturation (SpO₂) in ambient air, systolic and diastolic blood pressure, heart rate, respiratory rate, biochemical markers of cardiac dysfunction (TnI, and NT-proBNP), inflammatory markers (C reactive protein (CRP), fibrinogen, serum ferritin, interleukin-6 (IL-6), tumor necrosis factor alpha (TNFα)), D-dimers, lactate dehydrogenase (LDH), myoglobin and radio-imaging parameters. All patients underwent computerized tomography chest scan in the first two days following admission. Results: We observed elevated heart and respiratory rates, higher systolic blood pressure, and a lower diastolic blood pressure in the patients with cardiac injury; significant differences between groups were registered in TnI, NT-proBNP, LDH, CRP, and D-dimers. For the radiological parameters, we found proportional correlations with the myocardial injury for the severity of lung disease, number of pulmonary segments with alveolar consolidation, number of pulmonary lobes with pneumonia, crazy paving pattern, type of lung involvement, the extent of fibroatelectatic lesions and the mediastinal adenopathies. Conclusions: Myocardial injury occurred in 12% of patients in the study group. Ground glass opacities, interstitial interlobular septal thickening (crazy paving pattern), fibroatelectasic lesions and alveolar consolidations on CT scan were correlated with myocardial injury. Routine lung sectional imaging along with non-specific biomarkers (LDH, D-dimers, and CRP) can be further valuable in the characterization of the disease burden, thus impacting patient care.

The Predictive Score for Patients Hospitalized With COVID-19 in Resource-Limited Settings

Background and aims The second wave of coronavirus disease 2019 (COVID-19) has been devastating in India and many developing countries. The mortality reported has been 40% higher than in the first wave, overwhelming the nation's health infrastructure. Despite a better understanding of the disease and established treatment protocols including steroids and heparin, the second wave was disastrous. Subsequent waves have the potential to further cripple healthcare deliveries, also affecting non-COVID-19 care across many developing economies. It is then important to identify and triage high-risk patients to best use the limited resources. Routine tests such as neutrophil and monocyte counts have been identified but have not been successfully validated uniformly, and their utility is still being understood in COVID-19. Various predictive models that are available require online resources and calculators and additionally await validation across all populations. These, although useful, might not be available or accessible across all institutions. It is then important to identify easy-to-use scores that utilize tests done routinely. In identifying with this goal, we did a retrospective review of the institutional database to identify potential predictors of intensive care unit (ICU) admission and mortality in patients hospitalized during the second wave who accessed healthcare at our academic setup. Results Three predictors of mortality and four predictors of ICU admission were identified. Absolute neutrophil count was a common predictor of both ICU admission and mortality but with two separate cut points. An absolute neutrophil count of >4,200 predicted need for ICU admission (odds ratio (OR): 3.1 (95% confidence interval (CI): 2.0, 4.8)), and >7,200 predicted mortality (adjusted OR: 4.2 (95% CI: 1.9, 9.4)). We observed that a blood urea level greater than 45 was predictive of needing ICU care (adjusted OR: 8.0 (95% CI: 3.7, 17.6)). In our dataset, serum ferritin of >500 was predictive of ICU admission (adjusted OR: 2.7 (95% CI: 1.2, 5.9)). We noted a right shift of partial pressure (p50 is the oxygen tension at which hemoglobin is 50% saturated) (p50c) in SARS-CoV-2 as a predictor of ICU care (OR: 2.6 (95% CI: 1.7, 3.9)) when partial pressure is >26.5. In our analysis, a serum protein of less than 7 g/dL (OR: 2.8 (95% CI: 1.7, 4.4)) was a predictive variable for ICU admission. An LDH value of >675 was predictive of severity with a need for ICU admission (OR: 9.2 (95% CI: 5.4, 15.5)) in our series. We then assigned a score to each of the predictive variables based on the adjusted odds ratio. Conclusion We identified a set of easy-to-use predictive variables and scores to recognize the subset of patients hospitalized with COVID-19 with the highest risk of death or clinical worsening requiring ICU care.

SARS-COV-ATE risk assessment model for arterial thromboembolism in COVID-19

Patients with SARS-CoV-2 infection are at an increased risk of cardiovascular and thrombotic complications conferring an extremely poor prognosis. COVID-19 infection is known to be an independent risk factor for acute ischemic stroke and myocardial infarction (MI). We developed a risk assessment model (RAM) to stratify hospitalized COVID-19 patients for arterial thromboembolism (ATE). This multicenter, retrospective study included adult COVID-19 patients admitted between 3/1/2020 and 9/5/2021. Among 3531 patients from the training cohort, 15.5% developed acute in-hospital ATE, including stroke, MI, and other ATE, compared to 13.4% in the validation cohort. The 16-item final score was named SARS-COV-ATE (Sex: male = 1, Age [40–59 = 2, > 60 = 4], Race: non-African American = 1, Smoking = 1 and Systolic blood pressure elevation = 1, Creatinine elevation = 1; Over the range: leukocytes/lactate dehydrogenase/interleukin-6, B-type natriuretic peptide = 1, Vascular disease (cardiovascular/cerebrovascular = 1), Aspartate aminotransferase = 1, Troponin-I [> 0.04 ng/mL = 1, troponin-I > 0.09 ng/mL = 3], Electrolytes derangement [magnesium/potassium = 1]). RAM had a good discrimination (training AUC 0.777, 0.756–0.797; validation AUC 0.766, 0.741–0.790). The validation cohort was stratified as low-risk (score 0–8), intermediate-risk (score 9–13), and high-risk groups (score ≥ 14), with the incidence of ATE 2.4%, 12.8%, and 33.8%, respectively. Our novel prediction model based on 16 standardized, commonly available parameters showed good performance in identifying COVID-19 patients at risk for ATE on admission.

Hemostatic system and COVID-19 crosstalk: A review of the available evidence

Since the discovery of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and its resultant coronavirus disease 2019 (COVID-19) pandemic, respiratory manifestations have been the mainstay of clinical diagnosis, laboratory evaluations, and radiological investigations. As time passed, other pathological aspects of SARS-CoV-2 have been revealed. Various hemostatic abnormalities have been reported since the rise of the pandemic, which was sometimes superficial, transient, or fatal. Mild thrombocytopenia, thrombocytosis, venous, arterial thromboembolism, and disseminated intravascular coagulation are among the many hemostatic events associated with COVID-19. Venous thromboembolism necessitating therapeutic doses of anticoagulants is more frequently seen in severe cases of COVID-19, especially in patients admitted to intensive care units. Hemorrhagic complications rarely arise in COVID-19 patients either due to a hemostatic imbalance resulting from severe disease or as a complication of over anticoagulation. Although the pathogenesis of coagulation disturbance in SARS-CoV-2 infection is not yet understood, professional societies recommend prophylactic antithrombotic therapy in severe cases, especially in the presence of abnormal coagulation indices. The review article discusses the various available evidence on coagulation disorders, management strategies, outcomes, and prognosis associated with COVID-19 coagulopathy, which raises awareness about the importance of anticoagulation therapy for COVID-19 patients to guard against possible thromboembolic events.

Effect of EARLY administration of DEXamethasone in patients with COVID-19 pneumonia without acute hypoxemic respiratory failure and risk of development of acute respiratory distress syndrome (EARLY-DEX COVID-19): study protocol for a randomized controlled trial

Background

Corticosteroids are one of the few drugs that have shown a reduction in mortality in coronavirus disease 2019 (COVID-19). In the RECOVERY trial, the use of dexamethasone reduced 28-day mortality compared to standard care in hospitalized patients with suspected or confirmed COVID-19 requiring supplemental oxygen or invasive mechanical ventilation. Evidence has shown that 30% of COVID-19 patients with mild symptoms at presentation will progress to acute respiratory distress syndrome (ARDS), particularly patients in whom laboratory inflammatory biomarkers associated with COVID-19 disease progression are detected. We postulated that dexamethasone treatment in hospitalized patients with COVID-19 pneumonia without additional oxygen requirements and at risk of progressing to severe disease might lead to a decrease in the development of ARDS and thereby reduce death.

Methods/design

This is a multicenter, randomized, controlled, parallel, open-label trial testing dexamethasone in 252 adult patients with COVID-19 pneumonia who do not require supplementary oxygen on admission but are at risk factors for the development of ARDS. Risk for the development of ARDS is defined as levels of lactate dehydrogenase > 245 U/L, C-reactive protein > 100 mg/L, and lymphocyte count of < 0.80 × 10⁹/L. Eligible patients will be randomly assigned to receive either dexamethasone or standard of care. Patients in the dexamethasone group will receive a dose of 6 mg once daily during 7 days. The primary outcome is a composite of the development of moderate or more severe ARDS and all-cause mortality during the 30-day period following enrolment.

Discussion

If our hypothesis is correct, the results of this study will provide additional insights into the management and progression of this specific subpopulation of patients with COVID-19 pneumonia without additional oxygen requirements and at risk of progressing to severe disease.

Trial registration

ClinicalTrials.gov NCT04836780. Registered on 8 April 2021 as EARLY-DEX COVID-19.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13063-022-06722-x.

Circulating pyruvate is a potent prognostic marker for critical COVID-19 outcomes

Background

Coronavirus-19 (COVID-19) disease is driven by an unchecked immune response to the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus which alters host mitochondrial-associated mechanisms. Compromised mitochondrial health results in abnormal reprogramming of glucose metabolism, which can disrupt extracellular signalling. We hypothesized that examining mitochondrial energy-related signalling metabolites implicated in host immune response to SARS-CoV-2 infection would provide potential biomarkers for predicting the risk of severe COVID-19 illness.

Methods

We used a semi-targeted serum metabolomics approach in 273 patients with different severity grades of COVID-19 recruited at the acute phase of the infection to determine the relative abundance of tricarboxylic acid (Krebs) cycle-related metabolites with known extracellular signaling properties (pyruvate, lactate, succinate and α-ketoglutarate). Abundance levels of energy-related metabolites were evaluated in a validation cohort (n=398) using quantitative fluorimetric assays.

Results

Increased levels of four energy-related metabolites (pyruvate, lactate, a-ketoglutarate and succinate) were found in critically ill COVID-19 patients using semi-targeted and targeted approaches (p<0.05). The combined strategy proposed herein enabled us to establish that circulating pyruvate levels (p<0.001) together with body mass index (p=0.025), C-reactive protein (p=0.039), D-Dimer (p<0.001) and creatinine (p=0.043) levels, are independent predictors of critical COVID-19. Furthermore, classification and regression tree (CART) analysis provided a cut-off value of pyruvate in serum (24.54 µM; p<0.001) as an early criterion to accurately classify patients with critical outcomes.

Conclusion

Our findings support the link between COVID-19 pathogenesis and immunometabolic dysregulation, and show that fluorometric quantification of circulating pyruvate is a cost-effective clinical decision support tool to improve patient stratification and prognosis prediction.

Clinical, Laboratory, and Imaging Findings of Pregnant Women with Possible Vertical Transmission of SARS-CoV-2-Case Series

The Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) pandemic significantly impacted the general population's health. At times, the infection has unfavorably influenced pregnancy evolution and the result of birth. However, vertical transmission of the virus is rare and generates controversial discussions. The study aimed to highlight the clinical, laboratory, and imaging findings of pregnant women with confirmed Coronavirus Disease 2019 (COVID-19) with possible vertical transmission and identify possible factors that encourage vertical transmission. Between 1 April 2020 and 31 December 2021, 281 pregnant women diagnosed with COVID-19 gave birth in the Obstetrics and Gynecology Departments of the tertiary unit of County Emergency Clinical Hospital from Timisoara. Three newborns (1.06%) tested positive. The characteristic of these three cases was described as a short series. In two cases, the patients were asymptomatic. In one case, the patient developed a mild form of COVID-19 with a favorable evolution in all cases. We did not identify the presence of smoking history, vaccine before admission, atypical presentation, fever, or chest X-ray abnormalities. We note possible factors that encourage vertical transmission: Pregnancy-induced hypertension, thrombophilia, asymptomatic cough, an asymptomatic or mild form of the disease, a ruptured membrane, and cesarean. The laboratory results highlight the inconstant presence of some changes found in the list of potential predictors of the severity of the infection: Lymphopenia, high values of C-reactive protein, D-dimer, fibrinogen, platelets, Aspartate Aminotransferase, Lactate dehydrogenase, and ferritin. The study's conclusion of this small group suggests that there may have been an intrauterine infection in late pregnancy and described characteristics of the pregnant women. Possible risk factors that could encourage vertical transmission have been identified.

Mortality Predictors in Severe SARS-CoV-2 Infection

Background and Objectives: The severe forms of SARS-CoV-2 pneumonia are associated with acute hypoxic respiratory failure and high mortality rates, raising significant challenges for the medical community. The objective of this paper is to present the importance of early quantitative evaluation of radiological changes in SARS-CoV-2 pneumonia, including an alternative way to evaluate lung involvement using normal density clusters. Based on these elements we have developed a more accurate new predictive score which includes quantitative radiological parameters. The current evolution models used in the evaluation of severe cases of COVID-19 only include qualitative or semi-quantitative evaluations of pulmonary lesions which lead to a less accurate prognosis and assessment of pulmonary involvement. Materials and Methods: We performed a retrospective observational cohort study that included 100 adult patients admitted with confirmed severe COVID-19. The patients were divided into two groups: group A (76 survivors) and group B (24 non-survivors). All patients were evaluated by CT scan upon admission in to the hospital. Results: We found a low percentage of normal lung densities, PaO2/FiO2 ratio, lymphocytes, platelets, hemoglobin and serum albumin associated with higher mortality; a high percentage of interstitial lesions, oxygen flow, FiO2, Neutrophils/lymphocytes ratio, lactate dehydrogenase, creatine kinase MB, myoglobin, and serum creatinine were also associated with higher mortality. The most accurate regression model included the predictors of age, lymphocytes, PaO2/FiO2 ratio, percent of lung involvement, lactate dehydrogenase, serum albumin, D-dimers, oxygen flow, and myoglobin. Based on these parameters we developed a new score (COV-Score). Conclusions: Quantitative assessment of lung lesions improves the prediction algorithms compared to the semi-quantitative parameters. The cluster evaluation algorithm increases the non-survivor and overall prediction accuracy.COV-Score represents a viable alternative to current prediction scores, demonstrating improved sensitivity and specificity in predicting mortality at the time of admission.

Admission Hyperglycemia as a Predictor of COVID-19 Pneumonia, Cytokine Release Syndrome Progression, and Clinical Outcomes in a Tertiary Care Hospital

Introduction Diabetes and coronavirus disease 2019 (COVID-19) are interrelated. The presence of hyperglycemia per se during COVID-19 infection regardless of diabetes status has been associated with poor prognosis and increased risk of mortality. Objectives The main aim of the current study was to assess the association between admission hyperglycemia and COVID-19 outcomes. Methods This is a retrospective cohort study including 315 patients, mainly employed in the facility, who presented to the emergency department or were admitted with confirmed COVID-19 infection from April 2020 to August 2021. Results The mean age of the studied cohort was 40.2±12.5 years, where 59.68% were males and 37.7% were symptomatic. Older age, male gender, history of diabetes and hypertension, and elevated C-reactive protein (CRP) and lactate dehydrogenase (LDH) levels were associated with a significantly increased risk of developing cytokine release syndrome (CRS). Admission hyperglycemia was significantly associated with poor outcomes. The time to negativity was 9.30±0.1 days for asymptomatic patients; however, it increased significantly according to clinical presentation, presence of comorbidities, and severe outcomes, in patients with cytokine release syndrome. Conclusions Admission hyperglycemia was associated with an increased risk of progression to critical condition in patients hospitalized with COVID-19 independent of the history of diabetes. Therefore, it should not be overlooked but instead should be detected and appropriately treated to improve outcomes. In addition, post-COVID-19 care should be individualized, where severe cases require almost double the time needed by mild cases to convert to negative.

Pathophysiological Changes in Erythrocytes Contributing to Complications of Inflammation and Coagulation in COVID-19

Higher thrombotic burden in the acute phase of COVID-19 relies on a complex interplay between pro-inflammatory cytokine/chemokine release, increased endothelial dysfunction/damage, and potential sepsis-induced coagulopathy development in severe cases, all promoting coagulation activation. Plasma levels of cytokines and chemokines are known to be increased in COVID-19 however, are much higher in severe infections. Increased levels of IL-1β, IL-6, and IL-8 are known to play an important role in both acute and chronic inflammation, resulting in pathological clotting. However, little has been published on the effects of these interleukins on red blood cells (RBCs). Evidence shows that cytokines have a negative effect on the RBCs ultrastructure and introduce signs of eryptosis. Eryptosis can be described as a form of suicidal death of RBCs characterized by distinct findings of cell shrinkage, membrane blebbing, activation of proteases, and phosphatidylserine exposure at the outer membrane leaflet. Red blood cells from COVID-19 patients had increased levels of glycolytic intermediates, accompanied by oxidation and fragmentation of ankyrin, spectrin beta, and the N-terminal cytosolic domain of band 3 (AE1). Significantly altered lipid metabolism was also observed, in particular, short- and medium-chain saturated fatty acids, acyl-carnitines, and sphingolipids. Emerging research suggests that RBCs may contribute to a precision medicine approach to sepsis and have diagnostic value in monitoring complement dysregulation in COVID-19-sepsis and non-COVID sepsis as research indicates that complement activation products and viral antigens are present on RBCs in patients with COVID-19.

The Incidence of Venous Thromboembolism in Critically Ill Patients with SARS-CoV-2 Infection Compared with Critically Ill Influenza and Community-Acquired Pneumonia Patients: A Retrospective Chart Review

The rate of venous thromboembolism in COVID-19 patients has been reported to be 30% (deep vein thrombosis 20% and pulmonary embolism 18%). This has been shown to be higher in COVID-19 patients admitted to the ICU. Prophylactic anticoagulation may be sufficient at ward level, but not in intensive care. A retrospective chart review was undertaken in a large university hospital. The review included 276 patients from COVID-19 Wave 1, COVID-19 Wave 2, influenza, and community-acquired pneumonia groups. The timeframe included patients admitted between 23 February 2014 and 12 May 2021. Clinical characteristics, outcomes, blood results, rates of venous thromboembolism, and anticoagulation status were recorded. The incidence of venous thromboembolism in COVID-19 Wave 1, COVID-19 Wave 2, influenza, and community-acquired pneumonia was 10.91%, 13.69%, 13.33%, and 6.81%, respectively (p = 0.481). The incidence of pulmonary embolism was 7.27%, 10.95%, 3.33%, and 5.68%, respectively (p = 0.350). The incidence of deep vein thrombosis was 5.45%, 5.48%, 10.00%, and 1.14%, respectively (p = 0.117). Although most patients were prophylactically anticoagulated, venous thromboembolism still occurred. Venous thromboembolism remains an important differential to consider in critically ill COVID-19 patients. The current literature does not advise therapeutic anticoagulation for thromboprophylaxis in the ICU.

Clinical analysis on diagnostic accuracy of Bosch Vivalytic SARS-CoV-2 point-of-care test and evaluation of cycle threshold at admission for COVID-19 risk assessment

BACKGROUND

Point-of-care (POC) polymerase chain reaction (PCR) tests have the ability to improve testing efficiency in the Coronavirus disease 2019 (COVID-19) pandemic. However, real-world data on POC tests is scarce.

OBJECTIVE

To evaluate the efficiency of a novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) POC test in a clinical setting and examine the prognostic value of cycle threshold (CT) on admission on the length of hospital stay (LOS) in COVID-19 patients.

METHODS

Patients hospitalised between January and May 2021 were included in this prospective cohort study. Patients' nasopharyngeal swabs were tested for SARS-CoV-2 with Allplex™2019-nCoV (Seegene Inc.) real-time (RT) PCR assay as gold standard as well as a novel POC test (Bosch Vivalytic SARS-CoV-2 [Bosch]) and the SARS-CoV-2 Rapid Antigen Test (Roche) accordingly. Clinical sensitivity and specificity as well as inter- and intra-assay variability were analyzed.

RESULTS

120 patients met the inclusion criteria with 46 (38%) having a definite COVID-19 diagnosis by RT-PCR. Bosch Vivalytic SARS-CoV-2 POC had a sensitivity of 88% and specificity of 96%. The inter- and intra- assay variability was below 15%. The CT value at baseline was lower in patients with LOS ≥ 10 days when compared to patients with LOS < 10 days (27.82 (± 4.648) vs. 36.2 (25.9-39.18); p = 0.0191). There was a negative correlation of CT at admission and LOS (r[44]s = - 0.31; p = 0.038) but only age was associated with the probability of an increased LOS in a multiple logistic regression analysis (OR 1.105 [95% CI, 1.03-1.19]; p = 0.006).

CONCLUSION

Our data indicate that POC testing with Bosch Vivalytic SARS-CoV-2 is a valid strategy to identify COVID-19 patients and decrease turnaround time to definite COVID-19 diagnosis. Also, our data suggest that age at admission possibly with CT value as a combined parameter could be a promising tool for risk assessment of increased length of hospital stay and severity of disease in COVID-19 patients.