Plasma CRP level is positively associated with the severity of COVID-19

Preparing for future pandemics: frailty associates with mortality in hospitalised older people during the entire COVID-19 pandemic, a Dutch multicentre cohort study

PURPOSE

Viral mutations and improved prevention or treatment options may have changed the association of frailty with mortality throughout the COVID-19 pandemic. We investigated how associations of frailty with in-hospital mortality changed throughout the pandemic in older people hospitalised for COVID-19.

METHODS

The COVID-OLD study included COVID-19 patients aged ≥ 70 years hospitalised during the first (early 2020), second (late 2020), third (late 2021) or fourth wave (early 2022). Based on the clinical frailty scale, patients were categorised as fit (1-3), pre-frail (4-5) or frail (6-9). Associations of frailty with in-hospital mortality were assessed with pairwise comparisons with fit as reference category and modelled using binary logistic regression adjusted for age and sex.

RESULTS

This study included 2362 patients (mean age 79.7 years, 60% men). In the first wave, in-hospital mortality was 46% in patients with frailty and 27% in fit patients. In-hospital mortality decreased in each subsequent wave to 25% in patients with frailty and 11% in fit patients in the fourth wave. After adjustments, an overall higher risk of in-hospital mortality was found in frail (OR 2.26, 95% CI: 1.66-3.07) and pre-frail (OR 1.73, 95% CI: 1.27-2.35) patients compared to fit patients, which did not change over time (p for interaction = 0.74).

CONCLUSIONS

Frailty remained associated with a higher risk of in-hospital mortality throughout the entire COVID-19 pandemic, although overall in-hospital mortality rates decreased. Frailty therefore remains a relevant risk factor in all stages of a pandemic and is important to consider in prevention and treatment guidelines for future pandemics.

Unveiling the Role of PAR 1: A Crucial Link with Inflammation in Diabetic Subjects with COVID-19

Inflammation is a distinguished clinical manifestation of COVID-19 and type 2 diabetes mellitus (T2DM), often associated with inflammatory dysfunctions, insulin resistance, metabolic dysregulation, and other complications. The present study aims to test the hypothesis that serum concentrations of PAR-1 levels differ between COVID-19 diabetic patients (T2DM) and non-diabetic COVID-19 patients and determine their association with different biochemical parameters and inflammatory biomarkers. T2DM patients with COVID-19 (n = 50) with glycated hemoglobin (HbA1c) levels of (9.23 ± 1.66) and non-diabetic COVID-19 patients (n = 50) with HbA1c levels (4.39 ± 0.57) were recruited in this study. The serum PAR-1 levels (ELISA method) were determined in both groups and correlated with parameters such as age, BMI, inflammatory markers including CRP, interleukin 6 (IL-6), tumor necrosis factor-alpha (TNF-α), D-dimer, homocysteine, and N-terminal pro-B-type natriuretic peptide (NT-proBNP). Demographic variables such as BMI (29.21 ± 3.52 vs. controls 21.30 ± 2.11) and HbA1c (9.23 ± 1.66 vs. controls 4.39 ± 0.57) were found to be statistically elevated in COVID-19 T2DM patients compared to non-diabetic COVID-19 patients. The concentrations of several inflammatory biomarkers and PAR-1 were remarkably increased in the COVID-19 T2DM group when compared with the non-diabetic COVID-19 group. The univariate analysis revealed that increased serum PAR-1 estimations were positively correlated with enhanced HbA1c, BMI, inflammatory cytokines, D-dimer, homocysteine, and NT-proBNP. The findings in the current study suggest that increased levels of serum PAR-1 in the bloodstream could potentially serve as an independent biomarker of inflammation in COVID-19 patients with T2DM.

Predictors of mortality in hospitalised patients with COVID-19: a 1-year case-control study

BACKGROUND

A paucity of predictive models assessing risk factors for COVID-19 mortality that extend beyond age and gender in Latino population is evident in the current academic literature.

OBJECTIVES

To determine the associated factors with mortality, in addition to age and sex during the first year of the pandemic.

DESIGN

A case-control study with retrospective revision of clinical and paraclinical variables by systematic revision of clinical records was conducted. Multiple imputations by chained equation were implemented to account for missing variables. Classification and regression trees (CART) were estimated to evaluate the interaction of associated factors on admission and their role in predicting mortality during hospitalisation. No intervention was performed.

SETTING

High-complexity centre above 2640 m above sea level (masl) in Colombia.

PARTICIPANTS

A population sample of 564 patients admitted to the hospital with confirmed COVID-19 by PCR. Deceased patients (n=282) and a control group (n=282), matched by age, sex and month of admission, were included.

MAIN OUTCOME MEASURE

Mortality during hospitalisation.

MAIN RESULTS

After the imputation of datasets, CART analysis estimated 11 clinical profiles based on respiratory distress, haemoglobin, lactate dehydrogenase, partial pressure of oxygen to inspired partial pressure of oxygen ratio, chronic kidney disease, ferritin, creatinine and leucocytes on admission. The accuracy model for prediction was 80.4% (95% CI 71.8% to 87.3%), with an area under the curve of 78.8% (95% CI 69.63% to 87.93%).

CONCLUSIONS

This study discloses new interactions between clinical and paraclinical features beyond age and sex influencing mortality in COVID-19 patients. Furthermore, the predictive model could offer new clues for the personalised management of this condition in clinical settings.

Evaluation of three common scoring systems in COVID-19 patients: neutrophil-lymphocyte ratio (NLR), The Acute Physiology and Chronic Health Evaluation II (APACHE II), and C-reactive protein (CRP)

Background

As SARS-CoV-2 becomes a major global health, the authors aimed to predict the severity of the disease, the length of hospitalization, and the death rate of COVID-19 patients based on The Acute Physiology and Chronic Health Evaluation II (APACHE II) criteria, neutrophil-lymphocyte ratio (NLR), and C-reactive protein (CRP) levels to prioritize, and use them for special care facilities.

Methods

In a retrospective study, 369 patients with COVID-19 hospitalized in the ICU from March 2021 to April 2022, were evaluated. In addition to the APACHE II score, several of laboratory factors, such as CRP and NLR, were measured.

Results

The values of CRP, NLR, and APACHE II scores were significantly higher in hospitalized and intubated patients, as well as those who died 1 month and 3 months after hospital discharge than those in surviving patients. The baseline NLR levels were the strongest factor that adversely affected death in the hospital, death 1 month and 3 months after discharge, and it was able to predict death, significantly.

Conclusion

CRP, NLR, and APACHE II were all linked to prognostic factors in COVID-19 patients. NLR was a better predictor of disease severity, the need for intubation, and death than the other two scoring tools.

Association of Inflammatory Markers With Disease Progression and the Severity of COVID-19

Introduction In December 2019, there was a massive outbreak of viral pneumonia, which had a high case fatality rate. Genetic sequencing of the virus showed similarity with severe acute respiratory syndrome coronavirus (SARS-CoV). It was later named novel coronavirus 2019 while the disease it caused was given the nomenclature of COVID-19. This deadly pneumonia outbreak was declared a pandemic by the World Health Organization (WHO). Aim To derive the strength of the correlation between blood levels of various inflammatory markers with the severity of COVID-19 pneumonia in patients affected with novel coronavirus 2019. Materials and methodology A prospective study was conducted on 300 confirmed cases of COVID-19 infection from August 2020 to July 2021 in SSG Hospital, Vadodara. Diagnosis of patients as confirmed cases of COVID-19 infection was done according to the WHO interim guidance for COVID-19. Their inflammatory markers were done for this study. All COVID-19-positive patients who had given negative consent for enrollment were excluded from the study. Patients were classified based on the severity of acute respiratory distress syndrome (ARDS). Comprehensive medical record information, encompassing biodata, clinical symptoms, comorbidities, and laboratory investigations, was systematically collected. Patients were given the standard treatment protocol as per guidelines. Patients were subjected to detailed investigations comprising complete blood counts and inflammatory markers like C-reactive protein (CRP), lactate dehydrogenase (LDH), serum ferritin, and D-dimer. Patients were further investigated by chest X-ray (posteroanterior view) or high-resolution computed tomography of the thorax. Results A total of 300 confirmed cases of COVID-19 infection were included in this study. Most of them were males (52%) with a mean age of 51 years and 48% were females with a mean age of 55 years. The majority of patients (40%) did not have ARDS, 23.3% of patients had mild, 16.7% of patients had moderate, and 20% of patients had severe ARDS. Higher CRP levels, serum ferritin, and serum D-dimer were significantly associated with the severity of COVID-19 infection as compared to those having no symptoms (p < 0.05). Increased levels were associated with severe clinical manifestations of COVID-19. The sensitivity of CRP is 69% and specificity is 100% as a diagnostic marker for COVID-19 pneumonia in terms of ARDS. The sensitivity of ferritin is 88% and specificity is 81% as a diagnostic marker for COVID-19 pneumonia in terms of ARDS. The sensitivity of D-dimer is 94% and specificity is 89% as a diagnostic marker for COVID-19 pneumonia in terms of ARDS. The sensitivity of LDH is 93% and specificity is 84% as a diagnostic marker for COVID-19 pneumonia in terms of ARDS. Conclusions Current evidence from our study showed that higher levels of inflammatory markers such as CRP, LDH, D-dimer, and ferritin are associated with the severity of COVID-19 in terms of ARDS and thus could be used as significant prognostic factors of the disease. These indicators might support clinical decisions to identify high fatality cases and poor diagnosis in the initial admission phase.

MBOAT7 expression is associated with disease progression in COVID-19 patients

BACKGROUND AND AIM

The emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in late 2019 caused a pandemic of acute respiratory disease, named coronavirus disease 2019 (COVID-19). COVID-19 became one of the most challenging health emergencies, hence the necessity to find different prognostic factors for disease progression, and severity. Membrane bound O-acyltransferase domain containing 7 (MBOAT7) demonstrates anti-inflammatory effects through acting as a fine-tune regulator of the amount of cellular free arachidonic acid. We aimed in this study to evaluate MBOAT7 expression in COVID-19 patients and to correlate it with disease severity and outcomes.

METHODS

This case-control study included 56 patients with confirmed SARS-CoV-2 diagnosis and 28 control subjects. Patients were further classified into moderate (n = 28) and severe (n = 28) cases. MBOAT7, tumor necrosis factor-α (TNF-α), and interleukin-1ß (IL-1ß) mRNA levels were evaluated in peripheral blood mononuclear cells (PBMC) samples isolated from patients and control subjects by real time quantitative polymerase chain reaction (RT-qPCR). In addition, circulating MBOAT7 protein levels were assayed by enzyme-linked immunosorbent assay (ELISA).

RESULTS

Significant lower levels of circulating MBOAT7 mRNA and protein were observed in COVID-19 patients compared to control subjects with severe COVID-19 cases showing significant lower levels compared to moderate cases. Moreover, severe cases showed a significant upregulation of TNF-α and IL-1ß mRNA. MBOAT7 mRNA and protein levels were significantly correlated with inflammatory markers (TNF-α, IL-1ß, C-reactive protein (CRP), and ferritin), liver enzymes, severity, and oxygen saturation levels.

CONCLUSION

COVID-19 is associated with downregulation of MBAOT7, which correlates with disease severity.

Application of artificial intelligence for the classification of the clinical outcome and therapy in patients with viral infections: The case of COVID-19

BACKGROUND

With the end of the coronavirus disease 2019 (COVID-19) pandemic, it becomes intriguing to observe the impact of innovative digital technologies on the diagnosis and management of diseases, in order to improve clinical outcomes for patients.

OBJECTIVE

The research aims to enhance diagnostics, prediction, and personalized treatment for patients across three classes of clinical severity (mild, moderate, and severe). What sets this study apart is its innovative approach, wherein classification extends beyond mere disease presence, encompassing the classification of disease severity. This novel perspective lays the foundation for a crucial decision support system during patient triage.

METHODS

An artificial neural network, as a deep learning technique, enabled the development of a complex model based on the analysis of data collected during the process of diagnosing and treating 1000 patients at the Tešanj General Hospital, Bosnia and Herzegovina.

RESULTS

The final model achieved a classification accuracy of 82.4% on the validation data set, which testifies to the successful application of the artificial neural network in the classification of clinical outcomes and therapy in patients infected with viral infections.

CONCLUSION

The results obtained show that expert systems are valuable tools for decision support in healthcare in communities with limited resources and increased demands. The research has the potential to improve patient care for future epidemics and pandemics.

Serum C-reactive protein greater than 75 mg/dL as an early available laboratory predictor of severe COVID-19: A systematic review

INTRODUCTION

Severe COVID-19 management is still challenging. Having a laboratory factor to predict the severity of a patient's condition can be very useful in how to approach each patient. There have been studies concentrating on the correlation between serum C-reactive protein (CRP) level and COVID-19 severity but we aim to reach a threshold for CRP in disease severity determination.

METHODS

We conducted a thorough search on PubMed, Web of Science and Google Scholar databases from early 2019 to October 2021, and 323 studies were assessed for eligibility in three phases. We used the Newcastle-Ottawa Scale to examine the validity of the studies. The t-test was applied for the CRP level cutoffs.

RESULTS

Eventually, 11 articles and 1615 patients were included in this systematic review. Our analysis evaluated combined mean, median, and standard deviation of severe patients' CRP to be respectively 73.37, 53.80, and 47.936. Based on the combined mean, 75 mg/dL was suggested as an initial threshold for baseline CRP in hospitalized patients for developing severe conditions.

CONCLUSION

This study recommends that COVID-19 patients with on-admission serum CRP levels of 75 mg/dL and more are likely associated with severe conditions. Thus, anti-inflammatory agents and further following may be helpful in these patients.

Increased risk of poor clinical outcome in COVID-19 patients with diabetes mellitus and in-hospital mortality predictors: A retrospective cohort from a tertiary hospital in Indonesia

AIM

To determine association between diabetes in confirmed cases of COVID-19 and intensive care admission and in-hospital mortality, evaluate several laboratory parameters as mortality predictor and develop predictors of in-hospital mortality among diabetics with COVID-19.

METHODS

This retrospective cohort recruited all cases of COVID-19 hospitalized in Fatmawati General Hospital from March to October 2020. Inclusion criterion was RT-PCR confirmed cases of COVID-19 who aged 18 years and older while exclusion criteria were incomplete medical record or cannot be found and pregnant women.

RESULTS

We enrolled 506 participants to this study with median age of 51 years (IQR:22), female (56.32%), and diabetes (28.46%). Diabetes increased intensive care admission (adjusted OR: 2.57; 95% CI: 3.52-10.43) and in-hospital mortality (adjusted OR: 2.50; 95% CI: 1.61-3.89). In predicting in-hospital mortality, ferritin and lactate dehydrogenase offered an acceptable discrimination, AUC: 0.71 (95% CI: 0.62-0.79) and AUC: 0.70 (95% CI: 0.61-0.78), respectively. The optimal cut-off of predicting mortality for ferritin was 786 g/mL and for LDH was 514.94 u/L. Factors include age above 70 years old, RBGs level on admission above 250 mg/dL or below 140 mg/dL, ferritin level above 786 ng/mL and presence of ARDS increased the odds of mortality among individuals with diabetes.

CONCLUSIONS

Diabetes increases risk intensive care admission and in hospital mortality in COVID-19. Multivariate analysis showed that older age, RBG on admission, high ferritin level, presence of ARDS increased the odds of mortality among individuals with diabetes.

Primary care during COVID-19 pandemic - a survey to establish clinical needs and lessons learned in infectious respiratory diseases in Spain

BACKGROUND

The COVID-19 pandemic has exposed gaps and areas of need in health care systems. General practitioners (GPs) play a crucial role in the response to COVID-19 and other respiratory infectious diseases (e.g., influenza). Knowing the current flow of these patients and the real needs of GPs is necessary to implement new therapeutic and diagnostic strategies. We sought to learn about the flow of COVID-19 and flu patients in Spanish primary health centers and understand the training needs in both the diagnosis and treatment of these diseases.

METHODS

A total of 451 regionally representative GPs completed an online survey between January and February 2022.

RESULTS

Most of the GPs had available infection containment measures (79%) and access to point-of-care (POC) rapid diagnostic testing (81%) in their centers. The availability of on-the-day diagnostic tests for COVID-19 was higher than that for influenza (80% vs. 20%). Most GPs referred 1 of 10 COVID-19 or flu patients with moderate to severe disease to the emergency department (80% and 90%, respectively). Training/knowledge was considered good regarding diagnostic tests and vaccines (85%) but null or low regarding antivirals (60%) and monoclonal antibodies (80%).

CONCLUSIONS

This survey identified the conditions of Spanish GPs in terms of the diagnosis and treatment of COVID-19 and flu patients. Respondents' comments suggested that quite radical system-level adjustments are needed to allow GPs to capitalize on the potential benefits of POC tests for diagnosis, reduction of referrals, and monitoring of these diseases.

Stellate Ganglion Block Relieves Long COVID-19 Symptoms in 86% of Patients: A Retrospective Cohort Study

Post-COVID-19 condition, also known as long COVID-19 syndrome and post-acute sequelae of SARS-CoV-2, encompasses an array of symptoms that persist well beyond the initial phase of the viral infection. These symptoms can range in intensity, from mild and manageable to severe and incapacitating. Due to the evolving nature of the SARS-CoV-2 pandemic, treatment protocols for the illness are in a constant state of evolution. The early stage of long COVID-19 syndrome contributes to a dearth of treatment protocols based on empirical evidence, while the absence of a conclusive pathophysiological understanding further complicates the development of such protocols. Current treatment regimens include homeopathic medicine, specialist system-focused treatments, infusion therapies, hyperbaric oxygenation, antivirals, and polypharmacy. The physiological, psychological, and societal impact of long COVID-19 cannot be approached casually and must govern the intensity with which the healthcare community approaches the treatment of long COVID-19 syndrome. In this 41-patient cohort study from a chronic pain management practice, the use of either unilateral or bilateral stellate ganglion block (SGB) was explored to manage symptoms associated with long COVID-19 syndrome. Results indicated that a substantial proportion of patients (86%) experienced a reduction of their symptoms following SGB treatment.

Inflammatory markers and COVID-19 disease progression

BACKGROUND

The COVID-19 pandemic has resulted in a global humanitarian crisis. Despite ongoing research, transmission risks and many disease characteristics remained unclear. Most patients have displayed elevated levels of certain inflammatory markers, which we sought to investigate further in relation to disease severity. The aim of this study was to examine the correlation between inflammatory markers and the severity of COVID-19 among patients.

METHODS

We conducted a cross-sectional study from April to September 2020, involving 143 COVID-19 PCR-positive patients from Ziauddin Hospital. Electronic patient records provided data on demographics, clinical status, and laboratory results.

RESULTS

The majority of PCR-positive patients were elderly males with comorbidities such as diabetes and hypertension. Almost all patients exhibited increased levels of various inflammatory markers, with procalcitonin (97.2%) being the most common. Statistically significant differences were observed in the levels of TLC (p = 0.005), CRP (p = 0.001), LDH (p = 0.001), Ferritin (p = 0.001), D-dimer (p = 0.001), and procalcitonin (p = 0.028), in relation to COVID-19 severity.

CONCLUSIONS

The data suggest a significant association between levels of inflammatory markers and COVID-19 severity. All markers, except procalcitonin, demonstrated a significant correlation with disease severity. These results could enhance our understanding of COVID-19 pathogenesis and help predict and manage severe cases.

Long-term multiple metabolic abnormalities among healthy and high-risk people following nonsevere COVID-19

Few studies have identified the metabolic consequences of the post-acute phase of nonsevere COVID-19. This prospective study examined metabolic outcomes and associated factors in nonsevere, RT-PCR-confirmed COVID-19. The participants' metabolic parameters, the prevalence of long-term multiple metabolic abnormalities (≥ 2 components), and factors influencing the prevalence were assessed at 1, 3, and 6 months post-onset. Six hundred individuals (mean age 45.5 ± 14.5 years, 61.7% female, 38% high-risk individuals) with nonsevere COVID-19 attended at least one follow-up visit. The prevalence of worsening metabolic abnormalities was 26.0% for BMI, 43.2% for glucose, 40.5% for LDL-c, 19.1% for liver, and 14.8% for C-reactive protein. Except for lipids, metabolic-component abnormalities were more prevalent in high-risk hosts than in healthy individuals. The prevalence of multiple metabolic abnormalities at the 6-month follow-up was 41.3% and significantly higher in high-risk than healthy hosts (49.2% vs 36.5%; P = 0.007). Factors independently associated with a lower risk of these abnormalities were being female, having dyslipidemia, and receiving at least 3 doses of the COVID-19 vaccine. These findings suggest that multiple metabolic abnormalities are the long-term consequences of COVID-19. For both high-risk and healthy individuals with nonsevere COVID-19, healthcare providers should monitor metabolic profiles, encourage healthy behaviors, and ensure complete vaccination.

Predictors of intensive care unit admission in adult cancer patients presenting to the emergency department with COVID-19 infection: A retrospective study

BACKGROUND

Adult cancer patients with COVID-19 were shown to be at higher risk of Intensive Care Unit (ICU) admission. Previously published prediction models showed controversy and enforced the importance of heterogeneity among different populations studied. Therefore, this study aimed to identify predictors of ICU admission (demographic, clinical, and COVID-19 targeted medications) in cancer patients with active COVID-19 infection presenting to the Emergency Department (ED).

METHODS

This is a retrospective cohort study. It was conducted on adult cancer patients older than 18 years who presented to the American University of Beirut Medical Center ED from February 21, 2020, till February 21, 2021, and were found to have COVID-19 infection. Relevant data were extracted from electronic medical records. The association between different variables and ICU admission was tested. Logistic regression was done to adjust for confounding variables. A p-value less than 0.05 was considered significant.

RESULTS

Eighty-nine distinct patients were included. About 37% were admitted to the ICU (n = 33). Higher ICU admission was seen in patients who had received chemotherapy within one month, had a respiratory rate at triage above 22 breaths per minute, oxygen saturation less than 95%, and a higher c-reactive protein upon presentation to the ED. After adjusting for confounding variables, only recent chemotherapy and higher respiratory rate at triage were significantly associated with ICU admission.

CONCLUSION

Physicians need to be vigilant when taking care of COVID-19 infected cancer patients. Patients who are tachypneic at presentation and those who have had chemotherapy within one month are at high risk for ICU admission.

Pathological Effects of SARS-CoV-2 Associated with Hematological Abnormalities

The SARS coronavirus 2 (SARS-CoV-2) is the causative agent of the 2019 coronavirus disease (COVID-19) pandemic that has claimed the lives of 6.9 million people and infected over 765 million. It has become a major worldwide health problem and is also known to cause abnormalities in various systems, including the hematologic system. COVID-19 infection primarily affects the lower respiratory tract and can lead to a cascade of events, including a cytokine storm, intravascular thrombosis, and subsequent complications such as arterial and venous thromboses. COVID-19 can cause thrombocytopenia, lymphopenia, and neutrophilia, which are associated with worse outcomes. Prophylactic anticoagulation is essential to prevent complications and death rates associated with the virus's effect on the coagulation system. It is crucial to recognize these complications early and promptly start therapeutic anticoagulation to improve patient outcomes. While rare, COVID-19-induced disseminated intravascular coagulation (DIC) exhibits some similarities to DIC induced by sepsis. Lactate dehydrogenase (LDH), D-dimer, ferritin, and C-reactive protein (CRP) biomarkers often increase in serious COVID-19 cases and poor prognosis. Understanding the pathophysiology of the disease and identifying risk factors for adverse outcomes is critical for effective management of COVID-19.

Being Eaten Alive: How Energy-Deprived Cells Are Disposed of, Mediated by C-Reactive Protein-Including a Treatment Option

In medicine, C-reactive protein (CRP) has become established primarily as a biomarker, predicting patient prognosis in many indications. Recently, however, there has been mounting evidence that it causes inflammatory injury. As early as 1999, CRP was shown to induce cell death after acute myocardial infarction (AMI) in rats and this was found to be dependent on complement. The pathological effect of CRP was subsequently confirmed in further animal species such as rabbit, mouse and pig. A conceptual gap was recently closed when it was demonstrated that ischemia in AMI or ischemia/hypoxia in the severe course of COVID-19 causes a drastic lack of energy in involved cells, resulting in an apoptotic presentation because these cells cannot repair/flip-flop altered lipids. The deprivation of energy leads to extensive expression on the cell membranes of the CRP ligand lysophosphatidylcholine. Upon attachment of CRP to this ligand, the classical complement pathway is triggered leading to the swift elimination of viable cells with the appearance of an apoptotic cell by phagocytes. They are being eaten alive. This, consequently, results in substantial fibrotic remodeling within the involved tissue. Inhibiting this pathomechanism via CRP-targeting therapy has been shown to be beneficial in different indications.

NLRP3, the inflammasome and COVID-19 infection

Severe coronavirus disease 2019 (COVID-19) is characterized by respiratory failure, shock or multiorgan dysfunction, often accompanied by systemic hyperinflammation and dysregulated cytokine release. These features are linked to the intense and rapid stimulation of the innate immune response. The NACHT, LRR and PYD domains-containing protein 3 (NLRP3) inflammasome is a central player in inflammatory macrophage activation which via caspase-1 activation leads to the release of the mature forms of the proinflammatory cytokines interleukin (IL)-1β and IL-18, and via cleavage of Gasdermin D pyroptosis, an inflammatory form of cell death. Here, we discuss the role of NLRP3 activation in COVID-19 and clinical trials currently underway to target NLRP3 to treat severe COVID-19.

Development and Validation of a Prediction Model of the Risk of Pneumonia in Patients with SARS-CoV-2 Infection

Objective

To establish a prediction model of pneumonia risk in SARS-CoV-2-infected patients to reduce unnecessary chest CT scans.

Materials and Methods

The model was constructed based on a retrospective cohort study. We selected SARS-CoV-2 test-positive patients and collected their clinical data and chest CT images from the outpatient and emergency departments of Hunan Provincial People's Hospital, China. Univariate and multivariate logistic regression and least absolute shrinkage and selection operator (LASSO) regression were utilized to identify predictors of pneumonia risk for patients infected with SARS-CoV-2. These predictors were then incorporated into a nomogram to establish the model. To ensure its performance, the model was evaluated from the aspects of discrimination, calibration, and clinical validity. In addition, a smoothed curve was fitted using a generalized additive model (GAM) to explore the association between the pneumonia grade and the model's predicted probability of pneumonia.

Results

We selected 299 SARS-CoV-2 test-positive patients, of whom 205 cases were in the training cohort and 94 cases were in the validation cohort. Age, CRP natural log-transformed value (InCRP), and monocyte percentage (%Mon) were found to be valid predictors of pneumonia risk. This predictive model achieved good discrimination of AUC in the training and validation cohorts which was 0.7820 (95% CI: 0.7254-0.8439) and 0.8432 (95% CI: 0.7588-0.9151), respectively. At the cut-off value of 0.5, it had a sensitivity and specificity of 70.75% and 66.33% in the training cohort and 76.09% and 73.91% in the validation cohort, respectively. With suitable calibration accuracy shown in calibration curves, decision curve analysis indicated high clinical value in predicting pneumonia probability in SARS-CoV-2-infected patients. The probability of pneumonia predicted by the model was positively correlated with the actual pneumonia classification.

Conclusion

This study has developed a pneumonia risk prediction model that can be utilized for diagnostic purposes in predicting the probability of pneumonia in patients infected with SARS-CoV-2.

New Viral Diseases and New Possible Remedies by Means of the Pharmacology of the Renin-Angiotensin System

All strains of SARS-CoV-2, as well as previously described SARS-CoV and MERS-CoV, bind to ACE2, the cell membrane receptor of β-coronaviruses. Monocarboxypeptidase ACE2 activity stops upon viral entry into cells, leading to inadequate tissue production of angiotensin 1-7 (Ang1-7). Acute lung injury due to the human respiratory syncytial virus (hRSV) or avian influenza A H7N9 and H5N1 viruses is also characterized by significant downregulation of lung ACE2 and increased systemic levels of angiotensin II (Ang II). Restoration of Ang1-7 anti-inflammatory, antifibrotic, vasodilating, and natriuretic properties was attempted at least in some COVID-19 patients through i.v. infusion of recombinant human ACE2 or intranasal administration of the modified ACE2 protein, with inconsistent clinical results. Conversely, use of ACE inhibitors (ACEis), which increase ACE2 cell expression, seemed to improve the prognosis of hypertensive patients with COVID-19. To restore Ang1-7 tissue levels in all these viral diseases and avoid the untoward effects frequently seen with ACE2 systemic administration, a different strategy may be hypothesized. Experimentally, when metallopeptidase inhibitors block ACE2, neprilysin (NEP), highly expressed in higher and lower airways, starts cleaving angiotensin I (Ang I) into Ang1-7. We suggest a discerning use of ACEis in normohypertensive patients with β-coronavirus disease as well as in atypical pneumonia caused by avian influenza viruses or hRSV to block the main ACE-dependent effects: Ang II synthesis and Ang1-7 degradation into angiotensin 1-5. At the same time, i.v.-infused Ang I, which is not hypertensive provided ACE is inhibited, may become the primary substrate for local Ang1-7 synthesis via ubiquitous NEP; i.e., NEP could replace inadequate ACE2 function if Ang I was freely available. Moreover, inhibitors of chymase, a serine endopeptidase responsible for 80% of Ang II-forming activity in tissues and vessel walls, could protect patients with atypical pneumonia from Ang II-mediated microvascular damage without reducing arterial blood pressure.

Cerebral small vessel disease pathology in COVID-19 patients: A systematic review

Cerebral small vessel disease (CSVD) is the leading cause of vascular cognitive impairment and is associated with COVID-19. However, contributing factors that often accompany CSVD pathology in COVID-19 patients may influence the incidence of cerebrovascular complications. Thus, a mechanism linking COVID-19 and CSVD has yet to be uncovered and differentiated from age-related comorbidities (i.e., hypertension), and medical interventions during acute infection. We aimed to evaluate CSVD in acute and recovered COVID-19 patients and to differentiate COVID-19-related cerebrovascular pathology from the above-mentioned contributing factors by assessing the localization of microbleeds and ischemic lesions/infarctions in the cerebrum, cerebellum, and brainstem. A systematic search was performed in December 2022 on PubMed, Web of Science, and Embase using a pre-established search criterion related to history of, or active COVID-19 with CSVD pathology in adults. From a pool of 161 studies, 59 met eligibility criteria and were included. Microbleeds and ischemic lesions had a strong predilection for the corpus callosum and subcortical/deep white matter in COVID-19 patients, suggesting a distinct CSVD pathology. These findings have important implications for clinical practice and biomedical research as COVID-19 may independently, and through exacerbation of age-related mechanisms, contribute to increased incidence of CSVD.

Inflammation associated with lung function abnormalities in COVID-19 survivors

BACKGROUND

Activation of inflammatory pathways promotes organ dysfunction in COVID-19. Currently, there are reports describing lung function abnormalities in COVID-19 survivors; however, the biological mechanisms remain unknown. The aim of this study was to analyze the association between serum biomarkers collected during and following hospitalization and pulmonary function in COVID-19 survivors.

METHODS

Patients recovering from severe COVID-19 were prospectively evaluated. Serum biomarkers were analyzed from admission to hospital, peak during hospitalization, and at the time of discharge. Pulmonary function was measured approximately 6 weeks after discharge.

RESULTS

100 patients (63% male) were included (age 48 years, SD ± 14) with 85% having at least one comorbidity. Patients with a restrictive spirometry pattern (n = 46) had greater inflammatory biomarkers compared to those with normal spirometry (n = 54) including peak Neutrophil-to-Lymphocyte ratio (NLR) value [9.3 (10.1) vs. 6.5 (6.6), median (IQR), p = 0.027] and NLR at hospital discharge [4.6 (2.9) vs. 3.2 (2.9) p = 0.005] and baseline C-reactive protein value [164.0 (147.0) vs. 106.5 (139.0) mg/dL, p = 0.083). Patients with an abnormal diffusing capacity (n = 35) had increased peak NLR [8.9 (5.9) vs. 5.6 (5.7) mg/L, p = 0.029]; baseline NLR [10.0 (19.0) vs. 4.0 (3.0) pg/ml, p = 0.002] and peak Troponin-T [10.0 (20.0) vs. 5.0 (5.0) pg/ml, p = 0.011] compared to patients with normal diffusing capacity (n = 42). Multivariable linear regression analysis identified predictors of restrictive spirometry and low diffusing capacity, but only accounted for a low degree of variance in pulmonary function outcome.

CONCLUSION

Overexpression of inflammatory biomarkers is associated with subsequent lung function abnormalities in patients recovered from severe COVID-19.

Assessment of C-reactive protein levels as an indicator for lung infiltrates in patients with COVID-19 pneumonia

Lung infiltrates are frequently observed in patients with COVID-19 infection and require specialized management. Identifying reliable laboratory parameters to reduce the need for chest CT scans in non-desaturation patients is of great interest. This study aimed to investigate the potential of C-reactive protein (CRP) as an indicator to identify the presence of lung infiltrates in early COVID-19 infection. The study was conducted at Al-Azhar University hospitals from May 2021 to March 2022 and included 210 patients with COVID-19 infection confirmed by positive PCR, all of whom were previously healthy, non-smokers, and non-hypoxemic. CRP levels were assessed and correlated with lung infiltrates observed in CT chest examinations. The mean value of CRP was 40.3±14.3 mg/L in males and 36.6±15.2 mg/L among females. One hundred sixty-two patients had pneumonic infiltrates, while 48 had no infiltrates. The mean value of CRP was 45.02±10.2 mg/L in patients with radiological infiltrates and 18.8±7.8 mg/L in patients without radiological infiltrates. Based on our findings, a CRP value greater than 29.8 mg/L was suggested as a cut-off value to indicate the presence of lung infiltrates. CRP is a simple laboratory marker that, at certain limits, may point to the presence of pneumonic infiltrates in early non-hypoxemic patients with COVID-19 infection.

C-reactive protein, D-dimer, erythrocyte sedimentation rate, and troponin in intensive care unit patients with COVID-19 in Iran

Background

The coronavirus disease 2019 (COVID-19) pandemic in Iran has led to a lack of intensive care unit (ICU) facilities. This study examines C-reactive protein (CRP), D-dimer, erythrocyte sedimentation rate (ESR), and troponin in ICU patients with COVID-19 in comparison to COVID-19 patients admitted to the wards in Iran.

Materials and Methods

In a case-control study, troponin, CRP, ESR, and D-dimer were compared in the case samples of 109 COVID-19 patients admitted to the ICU, and in the control group, 140 COVID-19 patients admitted to the wards.

Results

The mean of CRP (P < 0.001) and D-dimer (P < 0.001) was higher, whereas troponin (P < 0.001) was lower in patients admitted to the ICU, but no significant difference was observed between the values of ESR (P = 0.292) in the two groups.

Conclusion

This study showed that the values of CRP and D-dimer were higher in patients admitted to the ICU, but no significant difference was observed between the values of ESR in the two groups.

Epidemiological, Clinical, and Laboratory Features of Children with SARS-CoV-2 in Ukraine

INTRODUCTION

In December 2019, the Chinese city of Wuhan reported the first cases of pneumonia from a new type of beta coronavirus named SARS-CoV-2. In the early days of the COVID-19 outbreak, paediatric patients were thought to be immune to the new virus; however, further studies have shown people of all ages to be susceptible to the virus.

OBJECTIVE

Identify and describe the clinical and epidemiological features of COVID-19 among hospitalized children in Ukraine.

MATERIALS AND METHODS

Retrospective study of 171 children aged 2 months to 18 years who were hospitalized with laboratory-confirmed SARS-CoV-2.

RESULTS

Most patients in the study had a moderate progression of the disease (77.78%, or n=133), whereas a severe course was noted in 22.22% (n=38). Across age groups, children aged 6-12 was the predominant age group affected (35.67%, or n=61). The most common symptoms were fever in 88.2% of patients, sore throat in 69.2% and cough in 60.9%. Symptoms associated with dyspnoea and cyanosis were significantly more common in children with the severe course (p<0.05). Almost half of children had at least one comorbidity, the most prevalent being chronic tonsillitis (11.8% of patients) and anemia (6.5% of patients). A positive correlation (r=0.7 p<0.05) was found between CRP levels and COVID-19 severity. X-ray changes in the lungs were present in 76.61% of examined children and ground-glass opacity symptom was registered in 50.88%.

CONCLUSIONS

COVID-19 among hospitalized children in Ukraine usually has a moderate course of illness and a good prognosis.

Prognostic Value of C-Reactive Protein in SARS-CoV-2 Infection: A Simplified Biomarker of COVID-19 Severity in Northern Ethiopia

Purpose

To evaluate the role of C-reactive protein (CRP) in predicting severe COVID-19 patients.

Methods

A prospective observational cohort study was conducted from July 15 to October 28, 2020, at Kuyha COVID-19 isolation and treatment center hospital, Mekelle City, Northern Ethiopia. A total of 670 blood samples were collected serially. SARS-CoV-2 infection was confirmed by RT-PCR from nasopharyngeal swabs and CRP concentration was determined using Cobas Integra 400 Plus (Roche). Data were analyzed using STATA version 14. P-value <0.05 was considered statistically significant.

Results

Overall, COVID-19 patients had significantly elevated CRP at baseline when compared to PCR-negative controls [median 11.1 (IQR: 2.0-127.8) mg/L vs 0.9 (IQR: 0.5-1.9) mg/L; p=0.0004)]. Those with severe COVID-19 clinical presentation had significantly higher median CRP levels compared to those with non-severe cases [166.1 (IQR: 48.6-332.5) mg/L vs 2.4 (IQR: 1.2-7.6) mg/L; p<0.00001)]. Moreover, COVID-19 patients exhibited higher median CRP levels at baseline [58 (IQR: 2.0-127.8) mg/L] that decreased significantly to 2.4 (IQR: 1.4-3.9) mg/L after 40 days after symptom onset (p<0.0001). Performance of CRP levels determined using ROC analysis distinguished severe from non-severe COVID-19 patients, with an AUC value of 0.83 (95% CI: 0.73-0.91; p=0.001; 77.4% sensitivity and 89.4% specificity). In multivariable analysis, CRP levels above 30 mg/L were significantly associated with an increased risk of developing severe COVID-19 for those who have higher ages and comorbidities (ARR 3.99, 95% CI: 1.35-11.82; p=0.013).

Conclusion

CRP was found to be an independent determinant factor for severe COVID-19 patients. Therefore, CRP levels in COVID-19 patients in African settings may provide a simple, prompt, and inexpensive assessment of the severity status at baseline and monitoring of treatment outcomes.

Dynamic changes in radiological parameters, immune cells, selected miRNAs, and cytokine levels in peripheral blood of patients with severe COVID‑19

The present study aimed to investigate the dynamic changes in peripheral blood leucocyte subpopulations, cytokine and miRNA levels, and changes in computed tomography (CT) scores in patients with severe coronavirus disease 2019 (COVID-19) (n=14) and age-matched non-COVID-19 volunteers (n=17), which were included as a reference control group. All data were collected on the day of patient admission (day 0) and on the 7th, 14th and 28th days of follow-up while CT of the lungs was performed on weeks 2, 8, 24 and 48. On day 0, lymphopenia and leucopenia were detected in most patients with COVID-19, as well as an increase in the percentage of banded neutrophils, B cells, and CD4+ Treg cells, and a decrease in the content of PD-1low T cells, classical, plasmacytoid, and regulatory dendritic cells. On day 7, the percentage of T and natural killer cells decreased with a concurrent increase in B cells, but returned to the initial level after treatment discharge. The content of different T and dendritic cell subsets among CD45+ cells increased during two weeks and remained elevated, suggesting the activation of an adaptive immune response. The increase of PD-1-positive subpopulations of T and non-T cells and regulatory CD4 T cells in patients with COVID-19 during the observation period suggests the development of an inflammation control mechanism. The levels of interferon γ-induced protein 10 (IP-10), tumor necrosis factor-α (TNF-α) and interleukin (IL)-6 decreased on day 7, but increased again on days 14 and 28. C-reactive protein and granulocyte colony-stimulating factor (G-CSF) levels decreased gradually throughout the observation period. The relative expression levels of microRNA (miR)-21-5p, miR-221-3p, miR-27a-3p, miR-146a-5p, miR-133a-3p, and miR-126-3p were significantly higher at the beginning of hospitalization compared to non-COVID-19 volunteers. The plasma levels of all miRs, except for miR-126-3p, normalized within one week of treatment. At week 48, CT scores were most prominently correlated with the content of lymphocytes, senescent memory T cells, CD127+ T cells and CD57+ T cells, and increased concentrations of G-CSF, IP-10, and macrophage inflammatory protein-1α.

Characteristics and outcomes of COVID-19 patients during the BA.5 omicron wave in Tehran, Iran: a prospective observational study

BACKGROUND

Omicron (B.1.1.529) is the fifth variant of concern of SARS-CoV-2, which has several subvariants. Clinical features of BA.1 and BA.2 infections have been described in the literature, but we have limited information about the clinical profile of BA.5, which caused the seventh wave in Iran.

METHODS

A prospective observational study was conducted on the BA.5 confirmed patients referred to Imam Khomeini Hospital Complex, Tehran, Iran, from 11th to 31st August 2022. The patients were divided into the two groups of outpatients and hospitalized patients, and their clinical, radiological, and laboratory data and outcomes were recorded and analyzed.

RESULTS

We included 193 patients with confirmed BA.5 infection, of whom 48 patients (24·8%) were hospitalized. The mean age of the patients was 45·3 ± 16·5 years, and 113 patients (58·5%) were female. The mean number of days patients had symptoms was 6·8 ± 2·4 days. The most common symptoms were weakness (69·9%), sore throat (67·4%), myalgia (66·3%), hoarseness (63·7%), headache (55·4%), fatigue (54·9%), and dry cough (50·3%). Fever and dyspnea were significantly more observed in the hospitalized patients (p < 0·0001). The COVID-19 vaccination rate was significantly lower in hospitalized patients than in outpatients (35/48-72·9% vs. 140/145 - 96·6%, p < 0·0001). The most common underlying diseases were hypertension (16·1%), diabetes mellitus (9·8%), and cardiovascular diseases (9·8%), all of which were significantly more common in hospitalized patients. Lung opacities were observed in 81·2% of hospitalized patients. By the end of our study, 1·5% of patients died despite receiving critical care services.

CONCLUSIONS

Our findings suggested that BA.5 symptoms are more non-respiratory and usually improve within 7 days. Although the proportion of hospitalized patients is still significant, very few patients require intensive care. COVID-19 vaccination is effective in reducing the hospitalization rate.

TRIAL REGISTRATION

Not applicable. This study is not a clinical trial.

COVID-19 Biomarkers at the Crossroad between Patient Stratification and Targeted Therapy: The Role of Validated and Proposed Parameters

Clinical knowledge about SARS-CoV-2 infection mechanisms and COVID-19 pathophysiology have enormously increased during the pandemic. Nevertheless, because of the great heterogeneity of disease manifestations, a precise patient stratification at admission is still difficult, thus rendering a rational allocation of limited medical resources as well as a tailored therapeutic approach challenging. To date, many hematologic biomarkers have been validated to support the early triage of SARS-CoV-2-positive patients and to monitor their disease progression. Among them, some indices have proven to be not only predictive parameters, but also direct or indirect pharmacological targets, thus allowing for a more tailored approach to single-patient symptoms, especially in those with severe progressive disease. While many blood test-derived parameters quickly entered routine clinical practice, other circulating biomarkers have been proposed by several researchers who have investigated their reliability in specific patient cohorts. Despite their usefulness in specific contexts as well as their potential interest as therapeutic targets, such experimental markers have not been implemented in routine clinical practice, mainly due to their higher costs and low availability in general hospital settings. This narrative review will present an overview of the most commonly adopted biomarkers in clinical practice and of the most promising ones emerging from specific population studies. Considering that each of the validated markers reflects a specific aspect of COVID-19 evolution, embedding new highly informative markers into routine clinical testing could help not only in early patient stratification, but also in guiding a timely and tailored method of therapeutic intervention.

Mortality rates of severe COVID-19-related respiratory failure with and without extracorporeal membrane oxygenation in the Middle Ruhr Region of Germany

The use of extracorporeal membrane oxygenation (ECMO) is discussed to improve patients' outcome in severe COVID-19 with respiratory failure, but data on ECMO remains controversial. The aim of the study was to determine the characteristics of patients under invasive mechanical ventilation (IMV) with or without veno-venous ECMO support and to evaluate outcome parameters. Ventilated patients with COVID-19 with and without additional ECMO support were analyzed in a retrospective multicenter study regarding clinical characteristics, respiratory and laboratory parameters in day-to-day follow-up. Recruitment of patients was conducted during the first three COVID-19 waves at four German university hospitals of the Ruhr University Bochum, located in the Middle Ruhr Region. From March 1, 2020 to August 31, 2021, the charts of 149 patients who were ventilated for COVID-19 infection, were included (63.8% male, median age 67 years). Fifty patients (33.6%) received additional ECMO support. On average, ECMO therapy was initiated 15.6 ± 9.4 days after symptom onset, 10.6 ± 7.1 days after hospital admission, and 4.8 ± 6.4 days after the start of IMV. Male sex and higher SOFA and RESP scores were observed significantly more often in the high-volume ECMO center. Pre-medication with antidepressants was more often detected in survivors (22.0% vs. 6.5%; p = 0.006). ECMO patients were 14 years younger and presented a lower rate of concomitant cardiovascular diseases (18.0% vs. 47.5%; p = 0.0004). Additionally, cytokine-adsorption (46.0% vs. 13.1%; p < 0.0001) and renal replacement therapy (76.0% vs. 43.4%; p = 0.0001) were carried out more frequently; in ECMO patients thrombocytes were transfused 12-fold more often related to more than fourfold higher bleeding complications. Undulating C-reactive protein (CRP) and massive increase in bilirubin levels (at terminal stage) could be observed in deceased ECMO patients. In-hospital mortality was high (Overall: 72.5%, ECMO: 80.0%, ns). Regardless of ECMO therapy half of the study population deceased within 30 days after hospital admission. Despite being younger and with less comorbidities ECMO therapy did not improve survival in severely ill COVID-19 patients. Undulating CRP levels, a massive increase of bilirubin level and a high use of cytokine-adsorption were associated with worse outcomes. In conclusion, ECMO support might be helpful in selected severe cases of COVID-19.

Multidimensional Machine Learning for Assessing Parameters Associated With COVID-19 in Vietnam: Validation Study

BACKGROUND

Machine learning (ML) is a type of artificial intelligence strategy. Its algorithms are used on big data sets to see patterns, learn from their results, and perform tasks autonomously without being instructed on how to address problems. New diseases like COVID-19 provide important data for ML. Therefore, all relevant parameters should be explicitly quantified and modeled.

OBJECTIVE

The purpose of this study was to determine (1) the overall preclinical characteristics, (2) the cumulative cutoff values and risk ratios (RRs), and (3) the factors associated with COVID-19 severity in unidimensional and multidimensional analyses involving 2173 SARS-CoV-2 patients.

METHODS

The study population consisted of 2173 patients (1587 mild status [mild group] and asymptomatic patients, 377 moderate status patients [moderate group], and 209 severe status patients [severe group]). The status of the patients was recorded from September 2021 to March 2022. Two correlation tests, relative risk, and RR were used to eliminate unbalanced parameters and select the most remarkable parameters. The independent methods of hierarchical cluster analysis and k-means were used to classify parameters according to their r values. Finally, network analysis provided a 3-dimensional view of the results.

RESULTS

COVID-19 severity was significantly correlated with age (mild-moderate group: RR 4.19, 95% CI 3.58-4.95; P<.001), scoring index of chest x-ray (mild-moderate group: RR 3.29, 95% CI 2.76-3.92; P<.001; moderate-severe group: RR 3.03, 95% CI 2.4023-3.8314; P<.001), percentage of neutrophils (mild-moderate group: RR 3.18, 95% CI 2.73-3.70; P<.001; moderate-severe group: RR 3.32, 95% CI 2.6480-4.1529; P<.001), quantity of neutrophils (moderate-severe group: RR 3.15, 95% CI 2.6153-3.8025; P<.001), albumin (moderate-severe group: RR 0.46, 95% CI 0.3650-0.5752; P<.001), C-reactive protein (mild-moderate group: RR 3.4, 95% CI 2.91-3.97; P<.001), and ratio of lymphocytes (moderate-severe group: RR 0.34, 95% CI 0.2743-0.4210; P<.001). Significant inversion of correlations among the severity groups is important. Alanine transaminase and leucocytes showed a significant negative correlation (r=-1; P<.001) in the mild group and a significant positive correlation in the moderate group (r=1; P<.001). Transferrin and anion Cl showed a significant positive correlation (r=1; P<.001) in the mild group and a significant negative correlation in the moderate group (r=-0.59; P<.001). The clustering and network analysis showed that in the mild-moderate group, the closest neighbors of COVID-19 severity were ferritin and age. C-reactive protein, scoring index of chest x-ray, albumin, and lactate dehydrogenase were the next closest neighbors of these 3 factors. In the moderate-severe group, the closest neighbors of COVID-19 severity were ferritin, fibrinogen, albumin, quantity of lymphocytes, scoring index of chest x-ray, white blood cell count, lactate dehydrogenase, and quantity of neutrophils.

CONCLUSIONS

This multidimensional study in Vietnam showed possible correlations between several elements and COVID-19 severity to provide clinical reference markers for surveillance and diagnostic management.

Risk of mortality in COVID-19 patients: a meta- and network analysis

Understanding the most relevant hematological/biochemical characteristics, pre-existing health conditions and complications in survivors and non-survivor will aid in predicting COVID-19 patient mortality, as well as intensive care unit (ICU) referral and death. A literature review was conducted for COVID-19 mortality in PubMed, Scopus, and various preprint servers (bioRxiv, medRxiv and SSRN), with 97 observational studies and preprints, consisting of survivor and non-survivor sub-populations. This meta/network analysis comprised 19,014 COVID-19 patients, consisting of 14,359 survivors and 4655 non-survivors. Meta and network analyses were performed using META-MAR V2.7.0 and PAST software. The study revealed that non-survivors of COVID-19 had elevated levels of gamma-glutamyl transferase and creatinine, as well as a higher number of neutrophils. Non-survivors had fewer lymphocytes and platelets, as well as lower hemoglobin and albumin concentrations. Age, hypertension, and cerebrovascular disease were shown to be the most influential risk factors among non-survivors. The most common complication among non-survivors was heart failure, followed by septic shock and respiratory failure. Platelet counts, creatinine, aspartate aminotransferase, albumin, and blood urea nitrogen levels were all linked to ICU admission. Hemoglobin levels preferred non-ICU patients. Lower levels of hemoglobin, lymphocytes, and albumin were associated with increased mortality in ICU patients. This meta-analysis showed that inexpensive and fast biochemical and hematological tests, as well as pre-existing conditions and complications, can be used to estimate the risk of mortality in COVID-19 patients.

A patient-centric modeling framework captures recovery from SARS-CoV-2 infection

The biology driving individual patient responses to severe acute respiratory syndrome coronavirus 2 infection remains ill understood. Here, we developed a patient-centric framework leveraging detailed longitudinal phenotyping data and covering a year after disease onset, from 215 infected individuals with differing disease severities. Our analyses revealed distinct 'systemic recovery' profiles, with specific progression and resolution of the inflammatory, immune cell, metabolic and clinical responses. In particular, we found a strong inter-patient and intra-patient temporal covariation of innate immune cell numbers, kynurenine metabolites and lipid metabolites, which highlighted candidate immunologic and metabolic pathways influencing the restoration of homeostasis, the risk of death and that of long COVID. Based on these data, we identified a composite signature predictive of systemic recovery, using a joint model on cellular and molecular parameters measured soon after disease onset. New predictions can be generated using the online tool http://shiny.mrc-bsu.cam.ac.uk/apps/covid-19-systemic-recovery-prediction-app , designed to test our findings prospectively.

Clinical Features of COVID-19 and Differentiation from Other Causes of CAP

Community-acquired pneumonia (CAP) is a significant cause of morbidity and mortality, one of the most common reasons for infection-related death worldwide. Causes of CAP include numerous viral, bacterial, and fungal pathogens, though frequently no specific organism is found. Beginning in 2019, the COVID-19 pandemic has caused incredible morbidity and mortality. COVID-19 has many features typical of CAP such as fever, respiratory distress, and cough, and can be difficult to distinguish from other types of CAP. Here, we highlight unique clinical features of COVID-19 pneumonia such as olfactory and gustatory dysfunction, lymphopenia, and distinct imaging appearance.

Photonic sensor to detect rapid changes in CRP levels

One of the most important biomarkers used to determine inflammation is C-reactive protein (CRP). Its level, when it is within the range that does not define inflammation, informs about the risk of cardiovascular events. If the norm is exceeded and inflammation is detected in the body, CRP level can increase 1000 times within a few hours. The type of infection can also be determined based on the level of elevated CRP. All this makes CRP a very important element of diagnostics. A sensor based on low coherence interference is presented. Preliminary studies have shown that its sensitivity is 5.65 μg/L and the measurement time is short, <10 min. The entire system is built of commercially available components, which allow production cost minimalization. In addition, the user-friendly operation allows it to be operated by unqualified people. Due to these features, our solution is a promising alternative to commercially used enzyme-linked immunosorbent assay, which needs trained personnel to perform time-consuming measurement procedures.

Predictivity of CRP, Albumin, and CRP to Albumin Ratio on the Development of Intensive Care Requirement, Mortality, and Disease Severity in COVID-19

BACKGROUND

The C-reactive protein (CRP) to albumin ratio (CAR) is a new index calculated by dividing CRP by the albumin level. It has been claimed to have predictive value in determining morbidity and mortality in many critical diseases Aim: In this research, we aimed to elucidate the importance of CRP, albumin, and CAR as parameters that can predict the clinical course in COVID-19 patients.

MATERIALS & METHOD

In this retrospective analysis, the clinical, laboratory, and radiological findings of patients over the age of 18 who were diagnosed with SARS-CoV-2 infection with a positive reverse transcription-polymerase chain reaction (RT-PCR) test were evaluated. Age, gender, laboratory examinations at admission, and CRP and albumin values at the time of diagnosis have been recorded. The relationship of these parameters with the requirement for intensive care, exitus, and serious illness in the clinical follow-up of the patients was investigated. The baseline hospitalization parameters of the patients were compared between the severe and non-severe groups.

RESULTS

Individuals with severe disease had a higher rate of additional disease than those with non-severe disease. It was observed that the mean laboratory values ​​of patients with severe disease had a statistically higher level of D-dimer, CRP, aspartate aminotransferase (AST), platelet distribution width (PDW), CRP-albumin ratio, and ferritin, compared to mild to moderate cases (p<0.05). The rate of additional disease in deceased patients was higher than in patients who were alive (p<0.05). The CAR value was found to be moderately predictive in our study revealing the severity of the disease, and the possibility that the severity of the disease might be higher in patients with a CAR value above 21.47.

CONCLUSION

The results of this study revealed that CAR is a potential parameter in distinguishing critically ill COVID-19 patients in need of intensive care. Therefore, one can say that CAR is an important biomarker in clinically determining COVID-19.

Biochemical and hematological factors associated with COVID-19 severity among Gabonese patients: A retrospective cohort study

The COVID-19 disease presents a large range of clinical manifestations and includes asymptomatic, mild, and severe cases. The level of severity is related to parameters associated with immunity, genetics, and biochemistry. Africa shows one of the lowest COVID-19 fatality rates but very few data on the biochemical markers of COVID-19 in patients and the factors associated with disease severity are available for the continent. In Gabon, the COVID-19 fatality rate is only 0.63% but almost no data on biomarkers in COVID-19 patients have been published. Both the number of COVID-19 cases and the mortality rate reported in Africa in general, and in Gabon in particular, are lower than in non-African countries. As such, understanding the factors associated with disease severity in Gabonese patients is a crucial step to better understand the disease in the African context and prepare for future COVID-19 waves and other epidemics of emerging diseases. Here, we compared biochemical and hematological markers among 753 Gabonese COVID-19 patients with asymptomatic (184/753), mild/moderate (420/753), and severe/critical (149/753) forms of the disease using an Analysis of Variance (ANOVA) or a Kruskal-Wallis (KW) test. We modeled these parameters together with comorbidities, age, and sex to predict factors associated with disease severity by using a "binomial generalized linear model" utilizing the "package" stats of R software version 4.0.2. Our results showed that almost all the biochemical and hematological parameters (except creatinine, phosphorus, D-dimers, platelets, and monocytes) varied according to disease severity. However, age and the dysfunction of organs like the kidney, liver, and lung together with the decrease of electrolytes (chloride, potassium, and sodium) are the best predictors of disease severity in Gabonese patients.

A Simple Label-Free Aptamer-Based Electrochemical Biosensor for the Sensitive Detection of C-Reactive Proteins

The level of C-reactive protein (CRP) in the human body is closely associated with cardiovascular diseases and inflammation. In this study, a label-free functionalized aptamer sensor was attached to an electrode trimmed with in-gold nanoparticles and carboxylated graphene oxide (AuNPs/GO-COOH) to achieve sensitive measurements relative to CRP. Gold nanoparticles were selected for this study due to super stability, remarkably high electrical conductivity, and biocompatibility. In addition, carboxylated graphene oxide was utilized to promote the anchorage of inducer molecules and to increase detection accuracies. The sensing signal was recorded using differential pulse voltammetry (DPV), and it produced a conspicuous peak current obtained at approximately -0.4 V. Furthermore, the adapted sensor manifested a broad linear span from 0.001 ng/mL to 100 ng/mL. The results also demonstrated that this aptamer sensor had superior stability, specificity, and reproducibility. This aptamer-based electrochemical sensor has enormous potential in complex application situations with interfering substances.

Studying C-reactive protein and D-dimer levels in blood may prevent severe complications: A study in Bangladeshi COVID-19 patients

The ongoing COVID-19 pandemic has been a scientific, medical and social challenge. Since clinical course of this disease is largely unpredictable and can develop rapidly causing severe complications, it is important to identify laboratory biomarkers, which may help to classify patient's severity during initial stage. Previous studies have suggested C-reactive protein (inflammatory) and D-dimer (biochemical) as an effective biomarker. The differential severity in patients across the world and our limited understanding in the progression of the disease calls for a multi-country analysis for biomarkers. Therefore, we have analyzed these biomarkers among 228 Bangladeshi COVID-19 patients. We observed significant association of COVID-19 severity with these two biomarkers. Thus, we suggest to use these biomarkers for Bangladeshi COVID-19 patients for better disease monitoring. Such validated preventive measures may decrease the case fatality ratio substantially.

The Effect of Nitazoxanide on the Clinical Outcomes in Patients with COVID-19: A Systematic Review and Meta-Analysis of Randomized Controlled Trials

BACKGROUND AND OBJECTIVE

Nitazoxanide, a US Food and Drug Administration-approved antiparasitic agent, was reported to be effective in treating coronavirus disease 2019 (COVID-19). The lack of effective and precise treatments for COVID-19 infection earlier in the pandemic forced us to depend on symptomatic, empirical, and supportive therapy, which overburdened intensive care units and exhausted hospital resources. Therefore, the aim of this systematic review and meta-analysis was  to assess the efficacy and safety of nitazoxanide for COVID-19 treatment.

METHODS

A systematic review and meta-analysis synthesizing relevant randomized controlled trials from six databases (MedRxiv, WOS, SCOPUS, EMBASE, PubMed, and CENTRAL) until 17 May 2022 was conducted. Risk ratio (RR) for dichotomous outcomes was used and data with a 95% confidence interval (CI) are presented. The protocol was registered in PROSPERO with ID: CRD42022334658.

RESULTS

Six randomized controlled trials with 1412 patients were included in the analysis. Nitazoxanide was effective in accelerating viral clearance compared with placebo (RR: 1.30 with 95% CI 1.08, 1.56, p = 0.006) and reducing oxygen requirements (RR: 0.48 with 95% CI 0.39, 0.59, p = 0.00001), but we found no difference between nitazoxanide and placebo in improving clinical resolution (RR: 1.01 with 95% CI 0.94, 1.08, p = 0.88), reducing the mortality rate (RR: 0.88 with 95% CI 0.4, 1.91, p = 0.74), and intensive care unit admission (RR: 0.69 with 95% CI 0.43, 1.13, p = 0.14). Moreover, nitazoxanide was as safe as placebo (RR: 0.9 with 95% CI 0.72, 1.12, p = 0.34).

CONCLUSIONS

Compared with placebo, nitazoxanide was effective in expediting viral clearance and decreasing oxygen requirements. However, there was no difference between nitazoxanide and placebo regarding clinical response, all-cause mortality, and intensive care unit admission. Therefore, more large-scale studies are still needed to ascertain the clinical applicability of nitazoxanide in COVID-19.

Machine learning models to predict the maximum severity of COVID-19 based on initial hospitalization record

Background

As the worldwide spread of coronavirus disease 2019 (COVID-19) continues for a long time, early prediction of the maximum severity is required for effective treatment of each patient.

Objective

This study aimed to develop predictive models for the maximum severity of hospitalized COVID-19 patients using artificial intelligence (AI)/machine learning (ML) algorithms.

Methods

The medical records of 2,263 COVID-19 patients admitted to 10 hospitals in Daegu, Korea, from February 18, 2020, to May 19, 2020, were comprehensively reviewed. The maximum severity during hospitalization was divided into four groups according to the severity level: mild, moderate, severe, and critical. The patient's initial hospitalization records were used as predictors. The total dataset was randomly split into a training set and a testing set in a 2:1 ratio, taking into account the four maximum severity groups. Predictive models were developed using the training set and were evaluated using the testing set. Two approaches were performed: using four groups based on original severity levels groups (i.e., 4-group classification) and using two groups after regrouping the four severity level into two (i.e., binary classification). Three variable selection methods including randomForestSRC were performed. As AI/ML algorithms for 4-group classification, GUIDE and proportional odds model were used. For binary classification, we used five AI/ML algorithms, including deep neural network and GUIDE.

Results

Of the four maximum severity groups, the moderate group had the highest percentage (1,115 patients; 49.5%). As factors contributing to exacerbation of maximum severity, there were 25 statistically significant predictors through simple analysis of linear trends. As a result of model development, the following three models based on binary classification showed high predictive performance: (1) Mild vs. Above Moderate, (2) Below Moderate vs. Above Severe, and (3) Below Severe vs. Critical. The performance of these three binary models was evaluated using AUC values 0.883, 0.879, and, 0.887, respectively. Based on results for each of the three predictive models, we developed web-based nomograms for clinical use (http://statgen.snu.ac.kr/software/nomogramDaeguCovid/).

Conclusions

We successfully developed web-based nomograms predicting the maximum severity. These nomograms are expected to help plan an effective treatment for each patient in the clinical field.

Homogeneous ensemble models for predicting infection levels and mortality of COVID-19 patients: Evidence from China

Background

Persistence of long-term COVID-19 pandemic is putting high pressure on healthcare services worldwide for several years. This article aims to establish models to predict infection levels and mortality of COVID-19 patients in China.

Methods

Machine learning models and deep learning models have been built based on the clinical features of COVID-19 patients. The best models are selected by area under the receiver operating characteristic curve (AUC) scores to construct two homogeneous ensemble models for predicting infection levels and mortality, respectively. The first-hand clinical data of 760 patients are collected from Zhongnan Hospital of Wuhan University between 3 January and 8 March 2020. We preprocess data with cleaning, imputation, and normalization.

Results

Our models obtain AUC = 0.7059 and Recall (Weighted avg) = 0.7248 in predicting infection level, while AUC=0.8436 and Recall (Weighted avg) = 0.8486 in predicting mortality ratio. This study also identifies two sets of essential clinical features. One is C-reactive protein (CRP) or high sensitivity C-reactive protein (hs-CRP) and the other is chest tightness, age, and pleural effusion.

Conclusions

Two homogeneous ensemble models are proposed to predict infection levels and mortality of COVID-19 patients in China. New findings of clinical features for benefiting the machine learning models are reported. The evaluation of an actual dataset collected from January 3 to March 8, 2020 demonstrates the effectiveness of the models by comparing them with state-of-the-art models in prediction.

The relationship between C-reactive protein and levels of various cytokines in patients with COVID-19: A systematic review and correlation analysis

INTRODUCTION

C-reactive protein (CRP) and cytokines levels could alter in patients with coronavirus disease (COVID-19) due to the inflammatory response caused by the virus. This analysis aimed to assess the relationship between the CRP levels and the levels of various cytokines in COVID-19 patients.

MATERIALS AND METHODS

We searched the databases of PubMed, Cochrane, and Web of Science for relevant articles on May 29th, 2021. Applying the inclusion/exclusion criteria, the retrieved records underwent two-phase screenings; first, a title/abstract screening process, and then, a full-text screening to find the eligible studies. Data for study variables were extracted, including the CRP levels and the levels of all reported cytokines. A strong and significant relationship between Interleukins and CRP was defined as: p ≤ 0.05, 0.7 ≤ r ≤ 1.

RESULTS

In this study, 103 studies were included for systematic review and correlation analysis. The aggregate mean and SD of study variables were calculated and reported. The correlation between Interleukins and CRP was measured using correlation coefficient (r). It appeared that interleukin (IL)-10 has a moderate and significant relationship with CRP (p ≤ 0.05, r = 0.472). IL-10 predicted almost 10% of CRP changes.

CONCLUSION

This correlation analysis suggests IL-10 is moderately correlated with CRP levels in patients with COVID-19 infection. A better understanding of the pro-inflammatory markers could contribute to the implementation of therapeutic and preventive approaches. More prospective studies are suggested to explore the relationship between CRP and cytokines as potential markers for the early identification of COVID-19 progression and severity.

Trends of drug resistance to the commonly used antibiotics to combat the COVID-19 pandemic: Experience from a super-speciality institute of Northern India

Purpose

Coronavirus disease 2019 (COVID-19) is purely a viral illness which is not affected by the usage of antibiotics, but the risk of development of secondary bacterial infections during the course of respiratory illness or hospitalisation has led to a surge of antibiotic use. Anti-microbial resistance has taken an upward trend to some of the commonly used or over-used antibiotics. The present study was planned to focus on the trends of resistance rates noticed for the common antibiotics, namely, doxycycline, azithromycin, and so on, before and after the advent of this pandemic.

Material and Methods

The study was conducted at a tertiary care hospital of North India with 2000 samples, 1000 samples between March 2019 and March 2020 before the COVID pandemic and 1000 samples between April 2020 and April 2021 after the advent of the pandemic. Identification and zones for doxycycline and erythromycin were interpreted as per Clinical and Laboratory Standards Institute guidelines.

Results

Among the various samples, pus/aspirated fluids were in majority (47%), followed by blood (29%), respiratory specimens (18%), and urine (6%). On stratifying the various pathogens associated with the treatment of doxycycline and erythromycin, Staphylococcus species were the predominant ones in almost 82% of the cases, followed by Enterococcus (12%) and Streptococcus (6%) species. For doxycycline, the overall sensitivity was noted to be 46% in the year 2019-20 and 31% in the year 2020-21, whereas for erythromycin, the sensitivity was seen as 39% in 2019-20 and dropped down to 26% in 2020-21.

Conclusions

The authors noted a dip in the overall sensitivity towards doxycycline and azithromycin. This finding clearly indicates the increasing rates of antibiotic resistance in a developing country such as India during these COVID times. A proper anti-microbial stewardship programme during these times will help to de-escalate the increasing resistance rates and will prove to be of great help to the primary care physicians.

COVID-19 pnömonili hastalarda yaşa bağımlı bir prognostik faktör olarak CRP/albümin oranı

Amaç: Çalışmamızın amacı, Covid-19 pnömonisinde C-reaktif protein/albüminin yaşa bağlı bir belirteç olup olmadığını belirlemekti. Gereç ve Yöntem: Covid-19 pnömonisi olan 296 (166 erkek/ 130 kadın) hasta üzerinde retrospektif bir araştırma yaptık. Katılımcılar

Inflammatory Biomarkers Associated with In-Hospital Mortality in Critical COVID-19 Patients

The COVID-19 pandemic poses global healthcare challenges due to its unpredictable clinical course. The aim of this study is to identify inflammatory biomarkers and other routine laboratory parameters associated with in-hospital mortality in critical COVID-19 patients. We performed a retrospective observational study on 117 critical COVID-19 patients. Following descriptive statistical analysis of the survivor and non-survivor groups, optimal cut-off levels for the statistically significant parameters were determined using the ROC method, and the corresponding Kaplan-Meier survival curves were calculated. The inflammatory parameters that present statistically significant differences between survivors and non-survivors are IL-6 (p = 0.0004, cut-off = 27.68 pg/mL), CRP (p = 0.027, cut-off = 68.15 mg/L) and IL-6/Ly ratio (p = 0.0003, cut-off = 50.39). Additionally, other statistically significant markers are creatinine (p = 0.031, cut-off = 0.83 mg/dL), urea (p = 0.0002, cut-off = 55.85 mg/dL), AST (p = 0.0209, cut-off = 44.15 U/L), INR (p = 0.0055, cut-off = 1.075), WBC (p = 0.0223, cut-off = 11.68 × 10⁹/L) and pH (p = 0.0055, cut-off = 7.455). A survival analysis demonstrated significantly higher in-hospital mortality rates of patients with values of IL-6, IL-6/Ly, AST, INR, and pH exceeding previously mentioned thresholds. In our study, IL-6 and IL-6/Ly have a predictive value for the mortality of critically-ill patients diagnosed with COVID-19. The integration of these parameters with AST, INR and pH could contribute to a prognostic score for the risk stratification of critical patients, reducing healthcare costs and facilitating clinical decision-making.

Elevated Salivary Inflammatory Biomarkers are Associated with SARS-CoV-2 Infection Severity

High levels of inflammatory cytokines in serum have been reported in patients with severe SARS-CoV-2 infection. There is growing interest in recognizing the role of inflammatory biomarkers in saliva in diagnosing systemic diseases. This study assumed that estimating biomarkers in saliva samples from patients infected with SARS-CoV-2 would distinguish between mild and severe cases. Saliva was collected from 142 controls and 158 SARS-CoV-2 patients (mild 72 and severe 86) to measure interleukin-6 (IL-6), C-reactive protein (CRP), and C-X-C motif chemokine ligand-10 (CXCL-10). IL-6 and CXCL-10 were significantly increased in patients with mild and severe SARS-CoV-2 infections. CRP was significantly increased only in severe SARS-CoV-2 cases. All biomarkers were significantly higher in severe cases than in mild cases (p < 0.001). Among patients with SARS-CoV-2 infection, men showed significantly higher CRP and CXCL-10 levels than females (p < 0.01 and 0.05, respectively). In addition, elderly patients (40–80 years) had significantly higher IL-6, CRP, and CXCL-10 (p < 0.001). Patients with diabetes and hypertension showed elevated IL-6, CRP, and CXCL-10 (p < 0.001). There was a significant positive correlation between IL-6, CRP, CXCL-10, and between age, IL-6, CRP, and CXCL-10. Saliva may have a future value in measuring the inflammatory biomarkers associated with the severity of SARS-CoV2 infection and therapeutic monitoring.

Association between periodontitis and COVID-19 severity in a tertiary hospital: A retrospective cohort study

Introduction

Periodontitis is a chronic inflammatory disease caused by biofilm accumulation resulting in loss of periodontal attachment which could be linked to systemic implications. Coronavirus disease of 2019 (COVID-19) is a disease caused by SARS-CoV-2 that triggers damage to the lungs and other organs. COVID-19 and periodontitis share similar risk factors such as smoking, obesity, old age, and diabetes mellitus. Studies noted that periodontitis along with some systemic diseases has increased mortality. Thus, this study aims to examine the association of periodontitis with COVID-19 outcomes.

Methods

This observational study included periodontitis group and non-periodontitis group for COVID-19 outcome assessment. Inclusion criteria were applied to select adults (≥18 years old) who showed at least one dental visit, and were isolated or admitted due to a COVID-19 complication (i.e. in-ward, ICU, or death). Exclusion criteria were patients with no active dental records. The periodontal status was examined from posterior bitewings and panoramic radiographs. The primary outcome assessed was COVID-19 complications versus no admission.

Results and discussion

This study was the first of its kind as a retrospective cohort study to assess the association between periodontitis and COVID-19 severity in Riyadh, Saudi Arabia. Our findings revealed that periodontitis is statistically associated with COVID-19 severity. Periodontitis patients were three times more likely to have COVID-19 complications (p = 0.025). Diabetes (p = 0.004) and hypertension (p = 0.016) patients were 3.5 times more likely to have COVID-19 complications.

Conclusion

Understanding the potential association between periodontitis and COVID-19 through systemic inflammation might be a pathway to achieve high quality medical care.

Detection of SARS-CoV-2 Genome in Stool and Plasma Samples of Laboratory Confirmed Iranian COVID-19 Patients

Coronavirus disease 2019 (COVID19), caused by the severe acute respiratory syndrome coronavirus 2 (SARSCoV2), was first discovered in China in late 2019 and quickly spread worldwide. Although nasopharyngeal swab sampling is still the most popular approach identify SARS-CoV-2 carriers, other body samples may reveal the virus genome, indicating the potential for virus transmission via non-respiratory samples. In this study, researchers looked at the presence and degree of SARS-CoV-2 genome in stool and plasma samples from 191 Iranian COVID-19 patients, and looked for a link between these results and the severity of their disease. SARS-CoV-2 RNA shedding in feces and plasma of COVID-19 patients was assessed by reverse transcription-quantitative polymerase chain reaction (RT-qPCR). Medical data were collected and evaluated, including Clinical features, demographics, radiological, and laboratory findings of the patients. Plasma samples from 117 confirmed laboratory patients were evaluated and 24 out of 117 patients (20.51%) tested positive for SARS-COV-2 RNA. Besides, 20 out of 74 patients (27.03%) tested positive for SARS-COV-2 RNA in stool samples. There seems to be no relationship between the presence of SARS-CoV-2 genome in fecal and plasma samples of Covid-19 patients and the severity of illness. We provide evidence of the SARS-CoV-2 genome presence in stool and plasma samples of Iranian COVID-19 patients.