Novel serological biomarkers for inflammation in predicting disease severity in patients with COVID-19

sTREM-1 as a Predictive Biomarker for Disease Severity and Prognosis in COVID-19 Patients

Background

Research on biomarkers associated with the severity and adverse prognosis of COVID-19 can be beneficial for improving patient outcomes. However, there is limited research on the role of soluble TREM-1 (sTREM-1) in predicting the severity and prognosis of COVID-19 patients.

Methods

A total of 115 COVID-19 patients admitted to the emergency department of Beijing Youan Hospital from February to May 2023 were included in the study. Demographic information, laboratory measurements, and blood samples for sTREM-1 levels were collected upon admission.

Results

Our study found that sTREM-1 levels in the plasma of COVID-19 patients increased with the severity of the disease (moderate vs mild, p=0.0013; severe vs moderate, p=0.0195). sTREM-1 had good predictive value for disease severity and 28-day mortality (area under the ROC curve was 0.762 and 0.805, respectively). sTREM-1 also exhibited significant correlations with age, body temperature, respiratory rate, PaO2/FiO2, PCT, CRP, and CAR. Ultimately, through multivariate logistic regression analysis, we determined that sTREM-1 (OR 1.008, 95% CI: 1.002-1.013, p=0.005), HGB (OR 0.966, 95% CI: 0.935-0.998, p=0.036), D-dimer (OR 1.001, 95% CI: 1.000-1.001, p=0.009), and CAR (OR 1.761, 95% CI: 1.154-2.688, p=0.009) were independent predictors of 28-day mortality in COVID-19 patients. The combination of these four markers yielded a strong predictive value for 28-day mortality in COVID-19 cases with an AUC of 0.919 (95% CI: 0.857 -0.981).

Conclusion

sTREM-1 demonstrated good predictive value for disease severity and 28-day mortality, serving as an independent prognostic factor for adverse patient outcomes. In the future, we anticipate conducting large-scale multicenter studies to validate our research findings.

Presepsin as a prognostic biomarker in COVID-19 patients: combining clinical scoring systems and laboratory inflammatory markers for outcome prediction

BACKGROUND

There is still limited research on the prognostic value of Presepsin as a biomarker for predicting the outcome of COVID-19 patients. Additionally, research on the combined predictive value of Presepsin with clinical scoring systems and inflammation markers for disease prognosis is lacking.

METHODS

A total of 226 COVID-19 patients admitted to Beijing Youan Hospital's emergency department from May to November 2022 were screened. Demographic information, laboratory measurements, and blood samples for Presepsin levels were collected upon admission. The predictive value of Presepsin, clinical scoring systems, and inflammation markers for 28-day mortality was analyzed.

RESULTS

A total of 190 patients were analyzed, 83 (43.7%) were mild, 61 (32.1%) were moderate, and 46 (24.2%) were severe/critically ill. 23 (12.1%) patients died within 28 days. The Presepsin levels in severe/critical patients were significantly higher compared to moderate and mild patients (p < 0.001). Presepsin showed significant predictive value for 28-day mortality in COVID-19 patients, with an area under the ROC curve of 0.828 (95% CI: 0.737-0.920). Clinical scoring systems and inflammation markers also played a significant role in predicting 28-day outcomes. After Cox regression adjustment, Presepsin, qSOFA, NEWS2, PSI, CURB-65, CRP, NLR, CAR, and LCR were identified as independent predictors of 28-day mortality in COVID-19 patients (all p-values < 0.05). Combining Presepsin with clinical scoring systems and inflammation markers further enhanced the predictive value for patient prognosis.

CONCLUSION

Presepsin is a favorable indicator for the prognosis of COVID-19 patients, and its combination with clinical scoring systems and inflammation markers improved prognostic assessment.

COVID-19 with high-sensitivity CRP associated with worse dynamic clinical parameters and outcomes

Objective

This study aimed to evaluate the relationship between high-sensitivity C-reactive protein (hsCRP) in hospitalized COVID-19 patients and their clinical outcomes, including trajectory of hsCRP changes during hospitalization.

Method and results

Patients with positive COVID-19 tests between 2021 and 2023 were admitted to two hospitals. Among 184 adult patients, approximately half (47.3%) had elevated hsCRP levels upon admission, which defined as exceeding the laboratory-specific upper limit of test (> 5.0 mg/L). Clinical outcomes included critical illness, acute kidney injury, thrombotic events, intensive care unit (ICU) requirement, and death during hospitalization. Elevated hsCRP levels had a higher risk of ICU requirement than those with normal, 39.1% versus 16.5%; adjusted odds ratio (aOR), 2.3 [95% CI, 1.05-5.01]; p = 0.036. Patients with extremely high (≥2 times) hsCRP levels had aOR, 2.65 [95% CI, 1.09-6.45]; p < 0.001. On the fifth day hospitalization, patients with high hsCRP levels associated with acute kidney injury (aOR, 4.13 [95% CI, 1.30-13.08]; p = 0.016), ICU requirement (aOR, 2.67 [95%CI, 1.02-6.99]; p = 0.044), or death (aOR, 4.24 [95% CI, 1.38-12.99]; p = 0.011). The likelihood of worse clinical outcomes increased as hsCRP levels rose; patients with elevated hsCRP had lower overall survival rate than those with normal (p = 0.02). The subset of high hsCRP patients with high viral load also had a shorter half-life compared to those with normal hsCRP level (p = 0.003).

Conclusion

Elevated hsCRP levels were found to be a significant predictor of ICU requirement, acute kidney injury, or death within 5 days after hospitalization in COVID-19 patients. This emphasized the importance of providing more intensive care management to patients with elevated hsCRP.

Circulating TIGIT±PD1+TPH, TIGIT ± PD1+TFH cells are elevated and their predicting role in systemic lupus erythematosus

It is well established that increased peripheral helper T cells (TPH) and follicular helper T cells (TFH) was found in systemic lupus erythematosus (SLE) patients. However, the expression patterns and immunomodulatory roles of TIGIT and PD1 on TPH/TFH in SLE are poorly understood. The expression patterns of TIGIT and PD1 on TPH and TFH cells were examined using flow cytometry and their expression patterns in SLE patients were then further evaluated for their correlation with auto-antibodies, disease activity and severity, B cell differentiation. Logistic regression was used to analyze the risk factors. And the receiver operating characteristic curves and logistic regression model were created to evaluate the predicting role in SLE. TIGIT±PD1+TPH, TIGIT±PD1+TFH cells in the peripheral blood of SLE patients were upregulated, whereas TIGIT+PD1-TFH was downregulated. TIGIT ± PD1+TPH, TIGIT ± PD1+TFH cells positively correlated with auto-antibodies production, disease activity and severity, whereas TIGIT+PD1-TFH cells negatively correlated. TIGIT ± PD1+TPH, TIGIT-PD1+TFH were positively correlated with the frequency of plasmablasts. Furthermore, higher TIGIT+PD1+TPH and TIGIT+PD1+TFH were shown to be risk factors for SLE, whereas TIGIT+PD1-TFH was found to be a protective factor, according to logistic regression analysis. A further logistic regression model showed that combination of TPH/TFH and routine blood indicators may has potential predicting value for SLE, with AUC of 0.957. The increased TIGIT ± PD1+TPH, increased TIGIT ± PD1+TFH, decreased TIGIT+PD1-TFH correlates with disease severity and activity, may boost our comprehending of the role of TIGIT and PD1 on TPH/TFH in SLE, and a logistic regression model based on combination of TPH/TFH and routine blood indicators shows prominent value for predicting SLE.

Analyzing the expression pattern of the noncoding RNAs (HOTAIR, PVT-1, XIST, H19, and miRNA-34a) in PBMC samples of patients with COVID-19, according to the disease severity in Iran during 2022-2023: A cross-sectional study

Background and aims

MicroRNAs (miRNAs) and long noncoding RNAs (lncRNAs) are well-known types of noncoding RNAs (ncRNAs), which have been known as the key regulators of gene expression. They can play critical roles in viral infection by regulating the host immune response and interacting with genes in the viral genome. In this regard, ncRNAs can be employed as biomarkers for viral diseases. The current study aimed to evaluate peripheral blood mononuclear cell (PBMC) ncRNAs (lncRNAs-homeobox C antisense intergenic RNA [HOTAIR], -H19, X-inactive-specific transcript [XIST], plasmacytoma variant translocation 1 [PVT-1], and miR-34a) as diagnostic biomarkers to differentiate severe COVID-19 cases from mild ones.

Methods

Candidate ncRNAs were selected according to previous studies and assessed by real-time polymerase chain reaction in the PBMC samples of patients with severe coronavirus disease 2019 (COVID-19) (n = 40), healthy subjects (n = 40), and mild COVID-19 cases (n = 40). Furthermore, the diagnostic value of the selected ncRNAs was assessed by analyzing the receiver-operating characteristic (ROC).

Results

The results demonstrated that the expression pattern of the selected ncRNAs was significantly different between the studied groups. The levels of HOTAIR, XIST, and miR-34a were remarkably overexpressed in the severe COVID-19 group in comparison with the mild COVID-19 group, and in return, the PVT-1 levels were lower than in the mild COVID-19 group. Interestingly, the XIST expression level in men with severe COVID-19 was higher compared to women with mild COVID-19. ROC results suggested that HOTAIR and PVT-1 could serve as useful biomarkers for screening mild COVID-19 from severe COVID-19.

Conclusions

Overall, different expression patterns of the selected ncRNAs and ROC curve results revealed that these factors can contribute to COVID-19 pathogenicity and can be considered diagnostic markers of COVID-19 severe outcomes.

A hematological parameter-based model for distinguishing non-puerperal mastitis from invasive ductal carcinoma

Purpose

Non-puerperal mastitis (NPM) accounts for approximately 4-5% of all benign breast lesions. Ultrasound is the preferred method for screening breast diseases; however, similarities in imaging results can make it challenging to distinguish NPM from invasive ductal carcinoma (IDC). Our objective was to identify convenient and objective hematological markers to distinguish NPM from IDC.

Methods

We recruited 89 patients with NPM, 88 with IDC, and 86 with fibroadenoma (FA), and compared their laboratory data at the time of admission. LASSO regression, univariate logistic regression, and multivariate logistic regression were used to screen the parameters for construction of diagnostic models. Receiver operating characteristic curves, calibration curves, and decision curves were constructed to evaluate the accuracy of this model.

Results

We found significant differences in routine laboratory data between patients with NPM and IDC, and these indicators were candidate biomarkers for distinguishing between the two diseases. Additionally, we evaluated the ability of some classic hematological markers reported in previous studies to differentiate between NPM and IDC, and the results showed that these indicators are not ideal biomarkers. Furthermore, through rigorous LASSO and logistic regression, we selected age, white blood cell count, and thrombin time to construct a differential diagnostic model that exhibited a high level of discrimination, with an area under the curve of 0.912 in the training set and with 0.851 in the validation set. Furthermore, using the same selection method, we constructed a differential diagnostic model for NPM and FA, which also demonstrated good performance with an area under the curve of 0.862 in the training set and with 0.854 in the validation set. Both of these two models achieved AUCs higher than the AUCs of models built using machine learning methods such as random forest, decision tree, and SVM in both the training and validation sets.

Conclusion

Certain laboratory parameters on admission differed significantly between the NPM and IDC groups, and the constructed model was designated as a differential diagnostic marker. Our analysis showed that it has acceptable efficiency in distinguishing NPM from IDC and may be employed as an auxiliary diagnostic tool.

It's in the blood: a review of the hematological system in SARS-CoV-2-associated COVID-19

The emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has led to an unprecedented global healthcare crisis. While SARS-CoV-2-associated COVID-19 affects primarily the respiratory system, patients with COVID-19 frequently develop extrapulmonary manifestations. Notably, changes in the hematological system, including lymphocytopenia, neutrophilia and significant abnormalities of hemostatic markers, were observed early in the pandemic. Hematological manifestations have since been recognized as important parameters in the pathophysiology of SARS-CoV-2 and in the management of patients with COVID-19. In this narrative review, we summarize the state-of-the-art regarding the hematological and hemostatic abnormalities observed in patients with SARS-CoV-2-associated COVID-19, as well as the current understanding of the hematological system in the pathophysiology of acute and chronic SARS-CoV-2-associated COVID-19.

A predictive model for disease severity among COVID-19 elderly patients based on IgG subtypes and machine learning

Objective

Due to the increased likelihood of progression of severe pneumonia, the mortality rate of the elderly infected with coronavirus disease 2019 (COVID-19) is high. However, there is a lack of models based on immunoglobulin G (IgG) subtypes to forecast the severity of COVID-19 in elderly individuals. The objective of this study was to create and verify a new algorithm for distinguishing elderly individuals with severe COVID-19.

Methods

In this study, laboratory data were gathered from 103 individuals who had confirmed severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection using a retrospective analysis. These individuals were split into training (80%) and testing cohort (20%) by using random allocation. Furthermore, 22 COVID-19 elderly patients from the other two centers were divided into an external validation cohort. Differential indicators were analyzed through univariate analysis, and variable selection was performed using least absolute shrinkage and selection operator (LASSO) regression. The severity of elderly patients with COVID-19 was predicted using a combination of five machine learning algorithms. Area under the curve (AUC) was utilized to evaluate the performance of these models. Calibration curves, decision curves analysis (DCA), and Shapley additive explanations (SHAP) plots were utilized to interpret and evaluate the model.

Results

The logistic regression model was chosen as the best machine learning model with four principal variables that could predict the probability of COVID-19 severity. In the training cohort, the model achieved an AUC of 0.889, while in the testing cohort, it obtained an AUC of 0.824. The calibration curve demonstrated excellent consistency between actual and predicted probabilities. According to the DCA curve, it was evident that the model provided significant clinical advantages. Moreover, the model performed effectively in an external validation group (AUC=0.74).

Conclusion

The present study developed a model that can distinguish between severe and non-severe patients of COVID-19 in the elderly, which might assist clinical doctors in evaluating the severity of COVID-19 and reducing the bad outcomes of elderly patients.

Is There a Relationship Between Epicardial Adipose Tissue, Inflammatory Markers, and the Severity of COVID-19 Pneumonia?

Objectives

Epicardial adipose tissue (EAT) is a type of visceral adipose tissue with pro-inflammatory properties. We sought to examine the relationship between the EAT volume and attenuation measured on non-contrast chest computed tomography (CT), inflammation markers, and the severity of COVID-19 pneumonia.

Methods

One hundred and twenty-five patients who are over 18 years old who applied to our hospital and were found to have COVID-19 polymerase chain reaction (+) on nasopharyngeal swab sample and COVID-19 pneumonia on chest CT were included in the study. At admission, C-reactive protein (CRP), procalcitonin, fibrinogen, leukocytes, neutrophil-lymphocyte ratio, platelet-lymphocyte ratio, lactate dehydrogenase (LDH), ferritin, and d-dimer were evaluated. EAT volume and attenuation were measured on chest CT. Patients who were hospitalized and discharged from the ward were categorized as Group 1, whereas patients who required intensive care admission and/or died were classified as Group 2. The primary endpoint of our study was defined as death, hospitalization in the intensive care unit, and discharge. The relationship between disease severity and EAT and other inflammatory markers was investigated.

Results

One hundred and six individuals were in Group 1 and 19 patients were in Group 2. Of the 125 individuals, 46 were women and 79 were men. The mean age was 58.5±15.9 years. Group 2 patients were older. Regarding measurements of the EAT volume and attenuation; there was no statistically significant difference between the groups determined. The patients in Group 2 had statistically substantially higher values for urea, creatinine, LDH, d-dimer, troponin T, procalcitonin, CRP, and neutrophil/lymphocyte ratio in their laboratory tests. When compared to patients in Group 1, patients in Group 2 had statistically significantly lower albumin values (p<0.001). In obese patients, EAT volume was statistically significantly higher and EAT attenuation was found to be lower.

Conclusion

In our study, no relationship was found between critical COVID-19 disease and EAT volume and attenuation, which is an indicator of EAT inflammation. Inflammatory markers from routine laboratory tests can be used to predict critical COVID-19 disease. No relationship was found between obesity and critical COVID-19 disease.

Risk Factors and Drug Efficacy for Severe Illness in Hemodialysis Patients Infected with the Omicron Variant of COVID-19

INTRODUCTION

The Omicron variant of the novel coronavirus (COVID-19) has been spreading more rapidly and is more infectious, posing a higher risk of death and treatment difficulty for patients undergoing hemodialysis. This study aims to explore the severity rate and risk factors for hemodialysis patients infected with the Omicron variant and to conduct a preliminary analysis of the clinical efficacy of drugs.

METHODS

Clinical and biochemical indicators of 219 hemodialysis patients infected with the Omicron variant were statistically analyzed. The patients were divided into two groups based on whether they were severely ill or not, and multiple regression analysis was conducted to determine the risk factors for severe illness. The severely ill patients were then grouped based on discharge or death, and the treatment drugs were included as influencing factors for multiple regression analysis to determine the risk factors and protective factors for death of severely ill patients, and drug efficacy analysis was conducted.

RESULTS

Analysis showed that diabetes, low oxygen saturation, and high C-reactive protein (CRP) were independent risk factors for severe illness in hemodialysis patients infected with the Omicron variant. A history of diabetes and high C-reactive significantly increased the risk of severe illness in patients (aOR: 1.450; aOR: 1.011), while a high oxygen saturation level can reduce this risk (aOR: 0.871). In addition, respiratory distress was an independent risk factor for death in severely patients, significantly reducing the probability of discharge for patients (aOR: 0.152). The drugs thymalfasin and Tanreqing significantly increased the probability of discharge for patients (aOR: 1.472; aOR: 3.104), with the latter having a higher correlation, but with a relatively longer effective course.

CONCLUSION

Hemodialysis patients infected with the Omicron variant of COVID-19 should pay special attention to their history of diabetes, CRP, and oxygen saturation levels, as well as respiratory distress symptoms, to reduce the risk of severe illness and death. In addition, thymalfasin and Tanreqing may be considered in treatment.

Association between fibrinogen level and length of stay in patients with lower extremity atherosclerotic disease: a retrospective cohort study

The level of fibrinogen in patients with lower extremity atherosclerosis (LEAD) has been widely identified as a risk factor contributing to adverse outcomes. However, some knowledge gaps remain regarding fibrinogen levels and downstream adverse outcomes, such as length of stay (LOS). We conducted this study to examine the association between fibrinogen level and LOS in LEAD patients. The retrospective cohort study included 1428 LEAD patients between January 2014 and November 2021 in China. Several generalized linear models with a negative binomial link function were used to evaluate the association between fibrinogen level and LOS. The area under the curve (AUC) was used to evaluate the predicting effect of fibrinogen level on a LOS greater than 10 days (median LOS). The median age of the patients was 70 years old, and 1153 (80.74%) were males. Fibrinogen level was positively associated with LOS (β = 1.14; 95% CI, 0.42-1.86; p = 0.002) in LEAD patients after controlling for age, gender, number of historical hospitalizations, surgical history, vascular disease history, drinking history, smoking history, insurance type, surgical approach, lesion site, weight loss, Fontaine classification, age-adjusted Charlson comorbidity index, urea, total protein, activated partial thromboplastin time, thrombin time, prothrombin time-international normalized ratio, calcium, triglyceride, albumin/globulin ratio, phosphorus, and D-dimer. The fibrinogen-added prediction model demonstrated good discrimination and calibration, with an AUC value of 0.807. Fibrinogen level was positively associated with LOS in LEAD patients. The fibrinogen level is a widely available and easy-to-measure biochemical indicator, and it could be used as a suitable indicator for the prognosis and prophylaxis of prolonged LOS in patients with LEAD during hospitalization.

A score for predicting invasive pulmonary aspergillosis in immunocompetent critically ill patients

BACKGROUND

Delayed treatment leads to increased mortality in critically ill patients with invasive pulmonary aspergillosis (IPA). We aimed to develop and validate a prediction score based on novel biomarkers and clinical risk factors to identify IPA in immunocompetent patients in the intensive care unit (ICU).

METHODS

A retrospective study was conducted to collect medical information and novel biomarkers upon ICU admission. Risk factors adopted for the final prediction score were identified using multivariate logistic regression analysis.

RESULTS

We retrospectively collected 1841 critical ill patients between January 2018 and August 2022. Patients with IPA had higher C-reactive protein-to-albumin ratio (CAR), neutrophil-to-lymphocyte ratio, systemic immune-inflammation index and lower prognostic nutritional index (PNI). Chronic obstructive pulmonary disease (COPD), continuous renal replacement therapy (CRRT), high dose of corticosteroids, broad-spectrum antibiotics, blood galactomannan (GM) positivity and high CAR were independent risk factors for IPA and were entered into the final prediction score. The score had good discrimination, with the area under receiver operating characteristic curve of 0.816 and 0.780 for the training and validation cohorts, respectively, and good calibration.

CONCLUSION

A score based on six clinical and novel immunological biomarkers showed promising predictive value for antifungal treatment in immunocompetent ICU patients.

Correlation of systemic inflammation biomarkers and disease severity in pregnant women with COVID-19

OBJECTIVE

The aim of this study was to evaluate the prognostic value of whole blood parameters, systemic inflammatory indices, and systemic inflammatory markers in pregnant women with COVID-19.

METHODS

In this cross-sectional study, the demographic, clinical, and laboratory data (i.e., whole blood parameters, C-reactive protein, procalcitonin, ferritin, and D-dimer) of 464 pregnant women with COVID-19 who attended a tertiary hospital between January and April 2021 were reviewed. Systemic inflammatory indices (i.e., neutrophil/lymphocyte ratio, platelet/lymphocyte ratio, platelet/neutrophil ratio, and systemic immune inflammation index) were calculated. Asymptomatic and mildly symptomatic pregnant women were classified as Group 1 (n=413), and those with severe disease were classified as Group 2 (n=51).

RESULTS

Lymphocyte count and lymphocyte percentage in whole blood parameters were significantly lower (p<0.05), and C-reactive protein, ferritin, and procalcitonin values were higher in Group 2 (p<0.05). Systemic inflammatory indices [neutrophil/lymphocyte ratio (4.7±2.9 (1.1-21.2) vs 7.5±4.7 (2.13-23.2)), platelet/lymphocyte ratio (191.1±104.3 (53.0-807.1) vs 269.5±118.9 (105.0-756.0)), systemic immune inflammation index (1,000±663 (209-5,231) vs 1,630±1,314 (345-7,006))] were found statistically significantly higher in severe disease group (p<0.001).

CONCLUSION

Evidence in this study indicates that neutrophil/lymphocyte ratio, platelet/lymphocyte ratio, and systemic immune inflammation index at first admission are simple, rapid, and inexpensive indices in predicting the prognosis of COVID-19 in pregnant women.

Systemic inflammation index, disease severity, and mortality in patients with COVID-19: a systematic review and meta-analysis

Introduction

An excessive systemic pro-inflammatory state increases the risk of severe disease and mortality in patients with coronavirus disease 2019 (COVID-19). However, there is uncertainty regarding whether specific biomarkers of inflammation can enhance risk stratification in this group. We conducted a systematic review and meta-analysis to investigate an emerging biomarker of systemic inflammation derived from routine hematological parameters, the systemic inflammation index (SII), in COVID-19 patients with different disease severity and survival status.

Methods

A systematic literature search was conducted in PubMed, Web of Science, and Scopus, between the 1st of December 2019 and the 15th of March 2023. Risk of bias and certainty of evidence were assessed using the Joanna Briggs Institute Critical Appraisal Checklist and the Grades of Recommendation, Assessment, Development and Evaluation, respectively (PROSPERO registration number: CRD42023420517).

Results

In 39 studies, patients with a severe disease or non-survivor status had significantly higher SII values on admission compared to patients with a non-severe disease or survivor status (standard mean difference (SMD)=0.91, 95% CI 0.75 to 1.06, p<0.001; moderate certainty of evidence). The SII was also significantly associated with the risk of severe disease or death in 10 studies reporting odds ratios (1.007, 95% CI 1.001 to 1.014, p=0.032; very low certainty of evidence) and in six studies reporting hazard ratios (1.99, 95% CI 1.01 to 3.92, p=0.047; very low certainty of evidence). Pooled sensitivity, specificity, and area under the curve for severe disease or mortality were 0.71 (95% CI 0.67 to 0.75), 0.71 (95% CI 0.64 to 0.77), and 0.77 (95% CI 0.73 to 0.80), respectively. In meta-regression, significant correlations were observed between the SMD and albumin, lactate dehydrogenase, creatinine, and D-dimer.

Discussion

Our systematic review and meta-analysis has shown that the SII on admission is significantly associated with severe disease and mortality in patients with COVID-19. Therefore, this inflammatory biomarker derived from routine haematological parameters can be helpful for early risk stratification in this group.

Systematic review registration

https://www.crd.york.ac.uk/PROSPERO, identifier CRD42023420517.

The association between vitamin D intake with inflammatory and biochemical indices and mortality in critically ill patients with COVID-19: A case-control study

BACKGROUND

The coronavirus disease-2019 (COVID-19) has become a worldwide health issue with widespread hospitalization and dependence on the intensive care unit (ICU). Vitamin D has a key role in modulating immune cells and modulating the inflammatory responses. This study aimed to investigate the association of vitamin D supplementation with inflammatory, biochemical, and mortality indices in critically ill patients with COVID-19.

METHODS

This case-control study was conducted on critically ill COVID-19 patients hospitalized in the ICU including the survived >30 day patients as the case group and dead patients as the control group. The status of vitamin D supplementation and inflammatory and biochemical indices of the patients were retrieved from the medical records. Logistic regression method was used to assess the association between 30 days survival and vitamin D supplement intake.

RESULTS

Compared to the group of COVID-19 patients who died in <30 day, the survived patients had a lower eosinophile level (2.2 ± 0.5 vs. 6 ± 0.0, p < .001) and higher vitamin D supplementation duration (9 ± 4.4 vs. 3.3 ± 1.9 day, p = .001). Vitamin D supplementation had a positive association with survival in COVID-19 patients (OR: 1.98, 95% CI: 1.15-3.40, p < .05). The association remained significant after adjustments fot age, sex, underlying diseases, and smoking.

CONCLUSION

Vitamin D supplementation in critically ill patients with COVID-19 has the potential to increase survivability within the first 30 days of hospitalization.

A scoring system based on novel biomarkers and clinical risk factors to predict invasive candidiasis in immunocompetent critically ill patients

Background

Delayed diagnosis further increases the mortality of invasive candidiasis (IC) in intensive care unit (ICU) patients. This study aimed to develop and validate a score based on novel serological biomarkers and clinical risk factors for predicting IC in immunocompetent ICU patients.

Methods

We retrospectively collected clinical data and novel serological markers on admission to ICU. Multivariate logistic regression was used to identify the risk factors associated with IC, which were adopted to establish a scoring system.

Results

Patients with IC had a higher C-reactive protein-to-albumin ratio (CAR) and neutrophil-to-lymphocyte ratio (NLR) and lower prognostic nutritional index than those without IC. The NLR, CAR, sepsis, total parenteral nutrition, 1,3-β-D-glucan (BDG)-positivity, and Sequential Organ Failure Assessment score were identified as independent risk factors for IC by multivariate logistic regression analysis and entered into the final scoring system. The area under receiver operating characteristic curve of the score were 0.883 and 0.892, respectively, in the development and validation cohort, higher than Candida score (0.883 vs.0.730, p &lt; 0.001).

Conclusion

We established a parsimonious score based on NLR, CAR, BDG-positivity, and clinical risk factors, which can accurately identify IC in ICU patients to give treatment on time and reduce mortality.

Efficacy of blood urea nitrogen-to-albumin ratio for predicting prognostic outcomes of inpatients with COVID-19: A meta-analysis

BACKGROUND

The associations between blood urea nitrogen (BUN)/albumin ratio and poor prognosis in patients with diagnosis of coronavirus disease 2019 (COVID-19) remain to be clarified.

METHODS

A search based on 4 electronic databases (i.e., EMBASE, Google scholar, MEDLINE, and Cochrane Library) was performed on June 23, 2022. The association of BUN/Albumin ratio with poor prognostic outcomes, defined as patients with mortality/severe illnesses, were analyzed.

RESULTS

Results from analysis of 7 cohort studies (3600 individuals with COVID-19) published between 2020 and 2022 showed a higher BUN/Albumin ratio in the poor-prognosis group (Mean difference:  = 2.838, 95% confidence interval: 2.015-3.66, P < .001, I2 = 92.5%) than the good-prognosis group. Additional investigation into the connection between BUN/Albumin ratio as a binary variable (i.e., high or low) and the risk of poor outcome also supported an association between a higher BUN/Albumin ratio and a poor prognostic risk (odd ratio = 3.009, 95% confidence interval: 1.565-5.783, P = .001, I2 = 93.7%, 5 studies). Merged analysis of poor prognosis produced a sensitivity of 0.76, specificity of 0.72, and area under curve of 0.81.

CONCLUSION

This meta-analysis demonstrated a positive correlation between BUN/albumin ratio and poor outcome in patients with COVID-19. Additional large-scale prospective studies are needed to verify our findings.

The role of indices in predicting disease severity and outcomes of multisystem inflammatory syndrome in children

BACKGROUND

The aim of this study was to evaluate the role of the systemic immune inflammation index (SII), C-reactive protein/albumin ratio (CAR), the monocyte/lymphocyte ratio (MLR), and the neutrophil/lymphocyte ratio (NLR) in predicting disease severity, treatment, and prognosis in multisystem inflammatory syndrome in children (MIS-C).

METHODS

This medical record review retrospectively evaluated the clinical and laboratory findings of 191 MIS-C patients followed in the Department of Pediatric Rheumatology at Ankara City Hospital, Turkey. The patients were grouped by disease severity: mild, moderate, and severe. SII, CAR, MLR, and NLR were calculated for each group.

RESULTS

All patients had fever at the time of admission; 153 (80.1%) had gastrointestinal tract involvement, 74 (38.7%) had rash, 63 (33%) had conjunctivitis, 107 (56%) had cardiac involvement, 32 (15.6%) had renal involvement, and 143 (74.9%) had hematological involvement. According to logistic regression analysis, SII, NLR, MLR, and CAR were found to be predictive indexes for disease severity, need for intensive care, need for inotropes, and anakinra treatment in MIS-C. The cut-off values of ≥1605.3 for SII, ≥9.1 for NLR, and ≥3.9 for CAR increased the risk of severe disease by 3.4, 7.1, and 5.7 times, respectively.

CONCLUSION

NLR, SII, MLR, and CAR are effective and useful for predicting the severity of MIS-C, the need for intensive care, and the need for anakinra treatment.

Prognostic value of novel serum biomarkers, including C-reactive protein to albumin ratio and fibrinogen to albumin ratio, in COVID-19 disease: A meta-analysis

With COVID-19 still hovering around and threatening the lives of many at-risk patients, an effective, quick, and inexpensive prognostic method is required. Few studies have shown fibrinogen to albumin ratio (FAR) and C-reactive protein to albumin ratio (CAR) to be promising as prognostic markers for COVID-19 disease. However, their implications remain unclear. This meta-analysis aimed to elucidate the prognostic role of FAR and CAR in COVID-19 disease. A systematic literature search was undertaken using PubMed and Embase till April 2022. Inverse variance standardised mean difference (SMD) was calculated to report the overall effect size using random effect models. The generic inverse variance random-effects method was used to pool the area under the curve (AUC) values. All statistical analyses were performed on Revman and MedCalc Software. A total of 23 studies were included. COVID-19 non-survivors had a higher CAR on admission compared with survivors (SMD = 1.79 [1.04, 2.55]; p < 0.00001; I2  = 97%) and patients with a severe COVID-19 infection had a higher CAR on admission than non-severe patients (SMD = 1.21 [0.54, 1.89]; p = 0.0004; I2  = 97%). Similarly, higher mean FAR values on admission were significantly associated with COVID-19 mortality (SMD = 0.55 [0.32, 0.78]; p < 0.00001; I2  = 82%). However, no significant association was found between mean FAR on admission and COVID-19 severity (SMD = 0.54 [-0.09, 1.18]; p = 0.09; I2  = 91%). The pooled AUC values found that CAR had a good discriminatory-power to predict COVID-19 severity (AUC = 0.81 [0.75, 0.86]; p < 0.00001; I2  = 80%) and mortality (AUC = 0.81 [0.74, 0.87]; p < 0.00001; I2  = 86%). FAR had a fair discriminatory-power to predict COVID-19 severity (AUC = 0.73 [0.64, 0.82]; p < 0.00001; I2  = 89%). Overall, CAR was a good predictor of both severity and mortality associated with COVID-19 infection. Similarly, FAR was a satisfactory predictor of COVID-19 mortality but not severity.

Role of systemic immune-inflammatory index in early diagnosis of sepsis in newborns with CHD

OBJECTIVE

Congenital heart diseases (CHD) are the most common causes of birth defects that have increased the risk of infections. Neonatal sepsis is a life-threatening condition and early diagnosis can be life-saving. We aimed to evaluate the potential role of the systemic immune-inflammatory index in the early diagnosis of neonatal sepsis.

METHODS

A retrospective cohort study was conducted on 166 newborns with a diagnosis of neonatal sepsis who were admitted to our hospital with CHD between January 2017 and June 2021. Haematological indices including neutrophil/lymphocyte ratio, platelet/lymphocyte ratio, and systemic immune-inflammatory index were calculated for all patients at the time of diagnosis of neonatal sepsis (sepsis). The sepsis values of these indices were compared with the admission values (pre-sepsis) of the patients.

RESULTS

The mean gestational age and birth weight of the patients were 38.36 ± 1.42 weeks and 3057.75 ± 484.68 g. It was found that absolute neutrophil count, systemic immune-inflammatory index, neutrophil/lymphocyte ratio, but not platelet/lymphocyte ratio were significantly increased at the time of sepsis. The receiver operating characteristic curve showed that systemic immune-inflammatory index, neutrophil/lymphocyte ratio, and absolute neutrophil count have predictive ability to define neonatal sepsis among newborns with CHD. The systemic immune-inflammatory index produced an area under the curve receiver operating characteristic curve of 0.76 (70% sensitivity, 70.5% specificity). To discriminate neonatal sepsis, the cut-off values of systemic immune-inflammatory index, neutrophil/lymphocyte ratio, and absolute neutrophil count were 517.19, 2.62, and 9210/mm³, respectively.

CONCLUSION

As an easily accessible and reliable indicator, systemic immune-inflammatory index may be used in combination with the other parameters in the early diagnosis of neonatal sepsis.

Predictors of the Outcomes Following the Tocilizumab Treatment for Severe COVID-19

Background: Tocilizumab is used in severe COVID-19 yet has significant rates of treatment failure.

Objectives: This retrospective study aimed to identify early predictors of the response to tocilizumab therapy.

Methods: Biochemical and clinical characteristics of adult patients who received tocilizumab for severe COVID-19 pneumonia were retrospectively examined. A multivariable logistic regression model was constructed to identify factors that could predict the failure of tocilizumab therapy. A predictive nomogram was also created using the selected model.

Results: Out of 101 eligible patients, 30 had treatment failure, and 71 survived on a 28-day follow-up. The partial pressure of oxygen to fraction of inspired oxygen ratio (PFR) on the day of tocilizumab administration (100 vs 80.5), lactate dehydrogenase (LDH; 668 vs 507 U/L), neutrophil-to-lymphocyte ratio (NL ratio; 24.7 vs 10), and creatine kinase myocardial band (CKMB; 30.9 vs 22.7 U/L) were significantly different among the non-survivors and survivors, respectively. A logistic regression model was created, identifying LDH, NL ratio, pro-brain natriuretic peptide (ProBNP), and PFR on the day of tocilizumab administration as best predictors of mortality with an optimism-corrected area under the receiver operator characteristics (ROC) curve of 0.82. The model-implied odds ratios for mortality were 1.89 (95% CI 1.13-3.15) for every 100 U/L rise in serum LDH, 2.29 (95% CI 2.2-4.39) for every 10 unit rise in NL ratio, 1.23 (95% CI 0.95-1.58) for every 100 pg/ml increase in ProBNP, and 0.36 (95% CI 0.13-0.95) for every mmHg rise in PFR at intervention.

Conclusion: This study identified NL ratio, LDH, CKMB, and PFR at intervention as important markers of risk of treatment failure following the tocilizumab therapy. A multivariable logistic regression model including LDH, NL ratio, ProBNP, and PFR at intervention best predicted the risk of mortality in patients with severe COVID-19 pneumonia treated with tocilizumab.

C-Reactive Protein-to-Albumin Ratio and Clinical Outcomes in COVID-19 Patients: A Systematic Review and Meta-Analysis

C-reactive protein-to-albumin ratio (CAR) is an independent risk factor in cardiovascular, cerebrovascular, and infectious diseases. Through this study, we investigated the CAR values with respect to the severity and mortality of COVID-19 patients. We performed a systematic review and meta-analysis to retrieve studies that evaluated CAR values upon hospital admission in relation to the severity or mortality of COVID-19 patients. We adopted a random-effect model to calculate the pooled mean difference (MD) and their 95% confidence intervals (CI). Quality assessment was appraised using a Newcastle−Ottawa scale and publication bias was assessed using the Begg-test and funnel plot. We equally performed a subgroup analysis using study location and a sensitivity analysis only with studies with low risk of bias. We analyzed 32 studies (n = 12445). Severe COVID-19 patients had higher on-admission CAR values than non-severe COVID-19 patients (MD: 1.69; 95% CI: 1.35−2.03; p < 0.001; I2 = 89%). Non-survivor patients with COVID-19 had higher CAR values than survivor patients (MD: 2.59; 95% CI: 1.95−3.23; p < 0.001; I2 = 92%). In sensitivity analysis, the relationship remained with a decreasing of heterogeneity for severity (MD: 1.22; 95% CI: 1.03−1.40; p < 0.001; I2 = 13%) and for mortality (MD: 2.99; 95% CI: 2.47−3.51; p < 0.001; I2 = 0%). High CAR values were found in COVID-19 patients who developed severe disease or died.

Predictive Value of Systemic Immune-inflammation Index in Determining Mortality in COVID-19 Patients

Aim

The aim of this study was to evaluate whether systemic immune-inflammation index (SII) could predict mortality in patients with novel coronavirus 2019 (COVID-19) disease.

Methods

This two-center, retrospective study included a total of 191 patients with confirmed diagnosis of COVID-19 via nucleic acid test (NAT). The SII was calculated based on the complete blood parameters (neutrophil × platelet/lymphocyte) during hospitalization. The relationship between the SII and other inflammatory markers and mortality was investigated.

Results

The mortality rate was 18.3%. The mean age was 54.32±17.95 years. The most common symptoms were fever (70.7%) and dry cough (61.3%), while 8 patients (4.2%) were asymptomatic. The most common comorbidities were hypertension (37.7%), diabetes (23.0%), chronic renal failure (14.7%), and heart failure (7.9%) which all significantly increased the mortality rate (p<0.001). There was a highly positive correlation between the SII and polymorphonuclear leukocyte (PNL), neutrophil-to-lymphocyte ratio (NLR), and platelet-to-lymphocyte ratio (PLR) (r=0.754, p<0.001; r=0.812, p<0.001; r=0.841, p<0.001, respectively), while a moderate, positive correlation was found between the SII and C-reactive protein (CRP) (r=0.439, p<0.001). There was a significant correlation between the SII and mortality (U=1,357, p<0.001). The cut-off value of SII was 618.8 (area under the curve=0.751, p<0.001) with 80.0% sensitivity and 61.5% specificity. A cut-off value of >618.8 was associated with a 4.68-fold higher mortality.

Conclusion

Similar to NLR and PLR, the SII is a proinflammatory marker of systemic inflammation and can be effectively used in independent predicting COVID-19 mortality.

The Role of Neutrophil-to-Lymphocyte Ratio in Risk Stratification and Prognostication of COVID-19: A Systematic Review and Meta-Analysis

Several studies have proposed that the neutrophil−lymphocyte ratio (NLR) is one of the various biomarkers that can be useful in assessing COVID-19 disease-related outcomes. Our systematic review analyzes the relationship between on-admission NLR values and COVID-19 severity and mortality. Six different severity criteria were used. A search of the literature in various databases was conducted from 1 January 2020 to 1 May 2021. We calculated the pooled standardized mean difference (SMD) for the collected NLR values. A meta-regression analysis was performed, looking at the length of hospitalization and other probable confounders, such as age, gender, and comorbidities. A total of sixty-four studies were considered, which included a total of 15,683 patients. The meta-analysis showed an SMD of 3.12 (95% CI: 2.64−3.59) in NLR values between severe and non-severe patients. A difference of 3.93 (95% CI: 2.35−5.50) was found between survivors and non-survivors of the disease. Upon summary receiver operating characteristics analysis, NLR showed 80.2% (95% CI: 74.0−85.2%) sensitivity and 75.8% (95% CI: 71.3−79.9%) specificity for the prediction of severity and 78.8% (95% CI: 73.5−83.2%) sensitivity and 73.0% (95% CI: 68.4−77.1%) specificity for mortality, and was not influenced by age, gender, or co-morbid conditions. Conclusion: On admission, NLR predicts both severity and mortality in COVID-19 patients, and an NLR > 6.5 is associated with significantly greater the odds of mortality.

Systemic inflammation indices predict mortality in patients with COVID-19

Aim: In recent years, inflammation-based indices obtained from hematologic parameters have been shown to have prognostic value in various inflammatory diseases and cancer types. In this study, we aimed to investigate whether inflammation indices could be used to predict mortality in patients with COVID-19. Material and Method: A total of 295 patients with a proven diagnosis of COVID-19 who were followed up in the intensive care unit were included in this retrospective, cross-sectional study. The patients were divided into two groups, survivors and non-survivors. Results: D-dimer (HR:1.001, 95% CI:1-1.001) and troponin (HR: 1.001 95% CI: 1-1.001) levels of non-survivors were significantly higher in univariate analyses (p&lt;0.05). Procalcitonin levels of whom were found to be high in univariate (HR: 1.018 95% CI: 1.003 – 1.034) and multivariate (HR:1.02 95% CI: 1.004-1.037) analyses (p&lt;0.05). There was no significant difference between the groups in terms of median values of PLR, SIRI, and AISI indices (p&gt;0.05). The median NLR value of the survivors was 7.45, while it was 11.39 in the non-survivors, and this difference was statistically significant (p&lt;0.001). The median value of the SII index of the non-survivors was found as 2421.02, which was significantly higher than the survivors (p&lt;0.001). The value of NLR and SII indices in predicting mortality in COVID-19 was evaluated using ROC analysis (NLR: AUC=0.644, 95%CI: 0.581-0.708, p&lt;0.001; SII: AUC=0.584, 95%CI: 0.517-0.651, p=0.017). When the cut-off value for NLR was accepted as 9.574, the sensitivity was 59.3% and the specificity was 67% in predicting mortality. When the cut-off value for SII was accepted as 2285,846, it was found that it could predict mortality with a sensitivity of 52.38% and specificity of 66.04%. Conclusion: SII and NLR indices can predict mortality in patients with COVID-19 followed up in the intensive care unit.

COVID-19 hastalarında koagülopati için C-reaktif protein/albumin oranının tanısal doğruluğu

Amaç: Bu çalışma, COVİD-19'da D-dimer yüksekliğini öngörmede C-reaktif proteinin (CRP) albümine oranının (CAR) tanısal faydasını değerlendirmek amaçlamıştır. Gereç ve Yöntem: Bu retrospektif kohort çalışmasında, bir üniversite hastanesinde COVID-19 olduğu doğrulanmış 145 yatan hastadan veri topladık. Hastalar D-dimer düzeylerine göre D-dimer düzeyi yüksek olanlar ve D-dimer düzeyi normal olanlar olarak iki gruba ayrıldı. Hastaların tıbbi kayıtlarından demografik veriler, komorbiditeler, klinik semptomlar, CAR ve laboratuvar sonuçları elde edildi ve gruplar arasında kıyaslamalar yapıldı. Bulgular: Hastaların yaş ortalaması 52,9±17,9 yıl olup, 76'sı erkek idi. CAR medyanı, D-dimer değeri yüksek olanlarda anlamlı olarak daha yüksekti (134,1'e karşı 20,7,). D-dimeri yüksek hastalarda CRP, prokalsitonin, lökosit, nötrofil, laktat dehidrojenaz, ferritin ve fibrinojen daha yüksekti. CAR ve D-Dimer arasında oldukça anlamlı pozitif korelasyon vardı. Lojistik regresyon analizi, CAR'ın D-dimer yüksekliği için önemli bir belirleyici olduğunu ortaya koydu. ROC eğrisi altında kalan alan (AUC) CAR için 0,741 idi. COVİD-19 hastalarında D-dimer yüksekliğini öngörmek için CAR'ın doğrulanmış eşik değeri, %58 duyarlılık ve %70 özgüllük ile 81,8 idi. Sonuç: Çalışmamız, CAR'ın D-dimer ile önemli ölçüde korele olduğunu ve COVİD-19’u olan hastalarda D-dimer yüksekliğini öngörmek için kullanılabileceğini göstermiştir.

Association of Prognostic Nutritional Index with Severity and Mortality of Hospitalized Patients with COVID-19: A Systematic Review and Meta-Analysis

The associations of prognostic nutritional index (PNI) with disease severity and mortality in patients with coronavirus disease 2019 (COVID-19) remain unclear. Electronic databases, including MEDLINE, EMBASE, Google scholar, and Cochrane Library, were searched from inception to 10 May 2022. The associations of PNI with risk of mortality (primary outcome) and disease severity (secondary outcome) were investigated. Merged results from meta-analysis of 13 retrospective studies (4204 patients) published between 2020 and 2022 revealed a lower PNI among patients in the mortality group [mean difference (MD): −8.65, p < 0.001] or severity group (MD: −5.19, p < 0.001) compared to those in the non-mortality or non-severity groups. A per-point increase in PNI was associated with a reduced risk of mortality [odds ratio (OR) = 0.84, 95% CI: 0.79 to 0.9, p < 0.001, I2 = 67.3%, seven studies] and disease severity (OR = 0.84, 95% CI: 0.77 to 0.92, p < 0.001, I2 = 83%, five studies). The pooled diagnostic analysis of mortality yielded a sensitivity of 0.76, specificity of 0.71, and area under curve (AUC) of 0.79. Regarding the prediction of disease severity, the sensitivity, specificity, and AUC were 0.8, 0.61, and 0.65, respectively. In conclusion, this study demonstrated a negative association between PNI and prognosis of COVID-19. Further large-scale trials are warranted to support our findings.

Expression and Clinical Significance of the m6A RNA-Binding Proteins YTHDF2 in Peripheral Blood Mononuclear Cells From New-Onset Ankylosing Spondylitis

This study has focused on determining the association of m6A methyltransferase [methyltransferase-like 3 (METTL3), methyltransferase-like 14 (METTL14), and Wilms tumor 1-associating protein (WTAP)], demethylase [fat mass and obesity-associated protein (FTO) and alkylation repair homolog protein 5 (ALKBH5)], RNA-binding proteins [YT521-B homology domains 2 (YTHDF2)], and ankylosing spondylitis (AS). A total of 154 specimens, containing 79 patients with new-onset AS and 75 healthy controls (HCs), participated in the study. The mRNA expressions of these m6A methyltransferase, demethylase, and RNA-binding protein in peripheral blood mononuclear cells (PBMCs) were detected by quantitative real-time PCR (qRT-PCR). The data showed that the mRNA expressions of YTHDF2 and ALKBH5 in PBMC from patients with new-onset AS were significantly decreased, and there was a positive correlation between RNA-binding proteins (YTHDF2) and demethylase (ALKBH5) in patients with new-onset AS. Logistic regression analysis demonstrated that the expression of YTHDF2 mRNA in PBMC is a risk factor of AS. Receiver operating characteristic (ROC) analysis of the area under the curve (AUC) for mRNA YTHDF2 in new-onset AS and HC was 0.692, with a cutoff value of &lt;0.8724, a sensitivity of 67%, and a specificity of 63%. Moreover, we constructed a novel predictive model based on a combination of mRNA YTHDF2 and systemic immune-inflammation index (SII) for AS diagnosis (AUC = 0.865, sensitivity = 79.45%, specificity = 84.00%), and the predictive model correlated with the activity and severity of AS. This study indicates that the mRNA expression of YTHDF2 in PBMC may be involved in AS pathogenesis and a predictive model based on a combination of mRNA YTHDF2 and SII acts as a marker for diagnosis and progression of diseases.

Significance of hemogram‐derived ratios for predicting in‐hospital mortality in COVID‐19: A multicenter study

Background

To address the problem of resource limitation, biomarkers having a potential for mortality prediction are urgently required. This study was designed to evaluate whether hemogram‐derived ratios could predict in‐hospital deaths in COVID‐19 patients.

Materials and Methods

This multicenter retrospective study included hospitalized COVID‐19 patients from four COVID‐19 dedicated hospitals in Sylhet, Bangladesh. Data on clinical characteristics, laboratory parameters, and survival outcomes were analyzed. Logistic regression models were fitted to identify the predictors of in‐hospital death.

Results

Out of 442 patients, 55 (12.44%) suffered in‐hospital death. The proportion of male was higher in nonsurvivor group (61.8%). The mean age was higher in nonsurvivors (69 ± 13 vs. 59 ± 14 years, p < 0.001). Compared to survivors, nonsurvivors exhibited higher frequency of comorbidities, such as chronic kidney disease (34.5% vs. 15.2%, p ≤ 0.001), chronic obstructive pulmonary disease (23.6% vs. 10.6%, p = 0.011), ischemic heart disease (41.8% vs. 19.4%, p < 0.001), and diabetes mellitus (76.4% vs. 61.8%, p = 0.05). Leukocytosis and lymphocytopenia were more prevalent in nonsurvivors (p < 0.05). Neutrophil‐to‐lymphocyte ratio (NLR), derived NLR (d‐NLR), and neutrophil‐to‐platelet ratio (NPR) were significantly higher in nonsurvivors (p < 0.05). After adjusting for potential covariates, NLR (odds ratio [OR] 1.05; 95% confidence interval [CI] 1.009‐1.08), d‐NLR (OR 1.08; 95% CI 1.006‐1.14), and NPR (OR 1.20; 95% CI 1.09‐1.32) have been found to be significant predictors of mortality in hospitalized COVID‐19 patients. The optimal cut‐off points for NLR, d‐NLR, and NPR for prediction of in‐hospital mortality for COVID‐19 patients were 7.57, 5.52 and 3.87, respectively.

Conclusion

Initial assessment of NLR, d‐NLR, and NPR values at hospital admission is of good prognostic value for predicting mortality of patients with COVID‐19.

COVID-19 related thrombosis: A mini-review

Introduction

COVID-19 associated VTE is a new disease entity with high morbidity and mortality. The aim of this paper is to review contemporary emerging literature on the incidence, pathophysiology, predictive prognostic indicators, and management consensus for Covid-19 related thrombotic complications, in particular DVT and PE.

Methods

A literature review was performed according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement. All searches were done via PubMed. References of review articles were further screened according to the exclusion criteria.

Results

In total, 154 records were identified and 20 duplicates were removed. A final 68 articles were included in the qualitative analysis. COVID-19 related thrombosis can affect multiple organs of the body, presenting in the form of arterial or venous thrombosis such as ischemic stroke, myocardial infarction, mesenteric ischemia, limb ischemia, DVT, or PE. DVT and PE has an overall incidence of 6–26%, and severely ill COVID-19 patients have even higher incidence of thromboembolism. On the other hand, incidence of arterial thromboembolism is much lower with incidence of 0.7%–3.7%. D-dimer is found to be an independent risk factor, and IMPROVE score, Caprini score, and Padua score have all been used as predictors. International guidelines suggest the use of low molecular weight heparin (LMWH) or fondaparinux for prophylaxis of VTE, and therapeutic dosage of weight adjusted LMWH for treatment if confirmed diagnosis.

Conclusions

Contemporary rapidly evolving evidence shows that COVID-19 associated thrombosis was a novel clinical entity, especially in severely ill COVID-19 patients. There are multiple society-driven guidelines only, but without any level 1 evidence for management regimen. The ideal dose for prophylaxis is not established and may vary depending on balance of bleeding and thrombosis risk. The risk of bleeding may be increased in patients in intensive care unit.

Risk of Death in Comorbidity Subgroups of Hospitalized COVID-19 Patients Inferred by Routine Laboratory Markers of Systemic Inflammation on Admission: A Retrospective Study

Our study objective was to construct models using 20 routine laboratory parameters on admission to predict disease severity and mortality risk in a group of 254 hospitalized COVID-19 patients. Considering the influence of confounding factors in this single-center study, we also retrospectively assessed the correlations between the risk of death and the routine laboratory parameters within individual comorbidity subgroups. In multivariate regression models and by ROC curve analysis, a model of three routine laboratory parameters (AUC 0.85; 95% CI: 0.79–0.91) and a model of six laboratory factors (AUC 0.86; 95% CI: 0.81–0.91) were able to predict severity and mortality of COVID-19, respectively, compared with any other individual parameter. Hierarchical cluster analysis showed that inflammatory laboratory markers grouped together in three distinct clusters including positive correlations: WBC with NEU, NEU with neutrophil-to-lymphocyte ratio (NLR), NEU with systemic immune-inflammation index (SII), NLR with SII and platelet-to-lymphocyte ratio (PLR) with SII. When analyzing the routine laboratory parameters in the subgroups of comorbidities, the risk of death was associated with a common set of laboratory markers of systemic inflammation. Our results have shown that a panel of several routine laboratory parameters recorded on admission could be helpful for early evaluation of the risk of disease severity and mortality in COVID-19 patients. Inflammatory markers for mortality risk were similar in the subgroups of comorbidities, suggesting the limited effect of confounding factors in predicting COVID-19 mortality at admission.

Mallampati Score Is an Independent Predictor of Active Oxygen Therapy in Patients with COVID-19

Mallampati score has been identified and accepted worldwide as an independent predictor of difficult intubation and obstructive sleep apnea. We aimed to determine whether Mallampati score assessed on the first patient medical assessment allowed us to stratify the risk of worsening of conditions in patients hospitalized due to COVID-19. A total of 493 consecutive patients admitted between 13 November 2021 and 2 January 2022 to the temporary hospital in Pyrzowice were included in the analysis. The clinical data, chest CT scan, and major, clinically relevant laboratory parameters were assessed by patient-treating physicians, whereas the Mallampati score was assessed on admission by investigators blinded to further treatment. The primary endpoints were necessity of active oxygen therapy (AOT) during hospitalization and 60-day all-cause mortality. Of 493 patients included in the analysis, 69 (14.0%) were in Mallampati I, 57 (11.6%) were in Mallampati II, 78 (15.8%) were in Mallampati III, and 288 (58.9%) were in Mallampati IV. There were no differences in the baseline characteristics between the groups, except the prevalence of chronic kidney disease (p = 0.046). Patients with Mallampati IV were at the highest risk of AOT during the hospitalization (33.0%) and the highest risk of death due to any cause at 60 days (35.0%), which significantly differed from other scores (p = 0.005 and p = 0.03, respectively). Mallampati IV was identified as an independent predictor of need for AOT (OR 3.089, 95% confidence interval 1.65−5.77, p < 0.001) but not of all-cause mortality at 60 days. In conclusion, Mallampati IV was identified as an independent predictor of AOT during hospitalization. Mallampati score can serve as a prehospital tool allowing to identify patients at higher need for AOT.

Serum hemato-immunological biomarkers associated with increased COVID-19 mortality in the Latino population

Introduction: COVID-19 hospitalizations and deaths have raised the need of identifying prognostic factors for medical decision-making. Methods: Observational, retrospective study analyzing 191 COVID-19 patients' serum inflammatory biomarkers. Results: The median age was 48.7 ± 12.7 years, 75.9% being men. Overweight/obesity was the most common comorbidity in 83.8% of patients. 44.5% had moderate disease followed by 43.5% with severe disease. The mean percentage of pulmonary damage was 53.4% ± 28.7. Serum leukocyte-to-lymphocyte ratio >7.7, neutrophil-to-lymphocyte ratio >10, platelet-to-lymphocyte ratio ≥250 and nutritional index <362 all were independent mortality predictors for COVID-19. Conclusions: A leukocyte-to-lymphocyte ratio >7.7 as well as a nutritional index <362 at hospitalization were independently associated with an increased mortality.

Specific serological inflammatory biomarkers including leukocyte-to-lymphocyte ratio >7.7 and nutritional index <362 are important mortality predictor factors that must be used in the management of COVID-19 hospitalized patients.

Altered Lipid Profile in COVID-19 Patients and Metabolic Reprogramming

Background

Coronavirus disease 2019 (COVID-19) is a global pandemic. Previous studies have reported dyslipidemia in patients with COVID-19. Herein, we conducted a retrospective study and a bioinformatics analysis to evaluate the essential data of the lipid profile as well as the possible mechanism in patients with COVID-19.

Methods

First of all, the retrospective study included three cohorts: patients with COVID-19, a healthy population, and patients with chronic obstructive pulmonary disease (COPD). For each subject, serum lipid profiles in the biochemical data were compared, including triglycerides (TG), total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), and low-density lipoprotein cholesterol (LDL-C). Furthermore, bioinformatics analyses were performed for exploring the biological or immunological mechanisms.

Results

In line with the biochemical data of the three cohorts, the statistical result displayed that patients with COVID-19 were more likely to have lower levels of TC and HDL-C as compared with healthy individuals. The differential proteins associated with COVID-19 are involved in the lipid pathway and can target and regulate cytokines and immune cells. Additionally, a heatmap revealed that severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections were possibly involved in lipid metabolic reprogramming. The viral proteins, such as spike (S) and non-structural protein 2 (Nsp2) of SARS-CoV-2, may be involved in metabolic reprogramming.

Conclusion

The metabolic reprogramming after SARS-CoV-2 infections is probably associated with the immune and clinical phenotype of patients. Hence, metabolic reprogramming may be targeted for developing antivirals against COVID-19.

Application of coagulation parameters at the time of necrotizing enterocolitis diagnosis in surgical intervention and prognosis

Purpose

It has been shown that abnormalities of coagulation and fibrinolysis system are involved in the pathogenesis of necrotizing enterocolitis (NEC), but not well studied challenge in the context of early detection of disease progression. The present study mainly explores the predictive significance of coagulation parameters at the time of NEC diagnosis in identifying the patients who eventually received surgery and/or NEC-related deaths.

Methods

The retrospective study of 114 neonates with NEC was conducted with assessments of demographic data, laboratory results at the time of NEC diagnosis, treatment methods and prognosis. According to treatment methods, patients were divided into surgical intervention group and medical treatment group. Predictive factors were put forward and determined by receiver operating characteristic (ROC) curve analysis. An analysis of the surgical intervention and prognosis was performed.

Results

Of 114 patients, 46 (40.4%) cases received surgical intervention and 14 (12.3%) deaths. prothrombin time (PT), PT international normalized ratio, activated partial thromboplastin time (APTT), fibrinogen and platelet count at the time of NEC diagnosis were independently associated with surgical NEC. The APTT could identify patients at high risk for surgical NEC, with 67.39% sensitivity, 86.76% specificity, better than that of other serological parameters. Coagulopathy was found in 38.6% of all patients. For surgical intervention, the area under the ROC curve (AUC) of coagulopathy was 0.869 (95% confidence interval [CI]: 0.794 ~ 0.944, P < 0.001), with 82.61% sensitivity and 91.18% specificity, outperformed APTT (95% CI: 0.236 ~ 0.173, P = 0.001). Furthermore, the AUC for coagulopathy to predict mortality was 0.809 (95% CI: 0.725 ~ 0.877, P < 0.001), with 92.86% sensitivity and 69.0% specificity.

Conclusion

Coagulation parameters at the time of NEC diagnosis were conducive to early prediction of surgical NEC and -related deaths, which should be closely monitored in neonates at high risk of NEC and validated as a clinical decision-making tool.

Prognostic Nutritional Index and Oxygen Therapy Requirement Associated With Longer Hospital Length of Stay in Patients With Moderate to Severe COVID-19: Multicenter Prospective Cohort Analyses

Purpose

To evaluate whether the prognostic nutritional index (PNI) is related to the oxygen therapy requirement at hospital admission and to ascertain the prognostic effect of the PNI and the oxygen therapy requirement as predictors of hospital length of stay in patients with moderate to severe coronavirus disease 2019 (COVID-19).

Methods

This is a post-hoc analysis in hospitalized patients with moderate to severe COVID-19. The participants were categorized: (1) non-oxygen therapy (moderate COVID-19 not requiring oxygen therapy); (2) nasal cannula therapy (severe COVID-19 requiring nasal cannula oxygen therapy); and (3) high-flow therapy (severe COVID-19 requiring high-flow oxygen therapy). PNI was calculated for each patient according to the following equation: serum albumin [g/dL] × 10 + total lymphocyte count [per mm³] × 0.005. The participants were categorized into malnutrition (PNI <40), mild malnutrition (PNI 40-45), and non-malnutrition (PNI > 45).

Results

According to PNI, malnutrition was more prevalent in the high-flow therapy group (94.9%; P < 0.001) with significantly lower PNI compared to both groups even after adjusting for the center and C-reactive protein. Patients in the high-flow therapy group [9 days (95% CI 7.2, 10.7), P < 0.001] and malnutrition status [7 days (95% CI 6.6, 7.4), P = 0.016] showed a significant longer hospital length of stay compared to their counterparts. The multivariable Cox proportional hazard models showed significant associations between both oxygen therapy requirement and PNI categories and hospital discharge.

Conclusion

In addition to oxygen therapy requirement, low PNI was associated with longer hospital length of stay. Our findings suggest that PNI could be useful in the assessment of nutritional status related to the prognosis of patients with moderate to severe COVID-19.

Comparative Study of Early Impacts of Post-COVID-19 Pneumonia on Clinical Manifestations, Pulmonary Function, and Chest Radiographs

Background and Objectives: Scant data regarding early post-COVID-19 effects are available, especially in younger people. Therefore, the objective of this study was to explore the early clinical impacts of post-COVID-19 pneumonia, comparing severe and non-severe patients. Materials and Methods: A cross-sectional study was conducted in adult patients admitted with COVID-19 pneumonia from April to May 2021. Demographic data, symptoms and signs, quality of life, Hospital Anxiety and Depression Scale (HADS), chest radiograph (CXR), pulmonary function tests (spirometry, impulse oscillometry), fractional exhaled nitric oxide (FeNO), and exercise capacity were assessed one month after hospital discharge. Twenty-five healthy control subjects that were age- and gender-matched were recruited for comparisons. Results: One hundred and five patients, with a mean age of 35.6 ± 15.8 years and 54 (51.4%) males, participated and were categorized into the non-severe pneumonia (N = 68) and severe pneumonia groups (N = 37). At a one-month follow-up visit (the time from the onset of the disease symptoms = 45.4 ± 5.9 days), the severe group had more cough, fatigue, and skin rash with higher dyspnea scale, more residual CXR lesions, and lower quality of life scores. Forced vital capacity (FVC) was lower in the severe group (88.3% of predicted value) and non-severe group (94.6% of predicted value) than in the healthy controls (p = 0.001). The six-minute walk distance was significantly lower in the non-severe group, at 79.2 m, and in the severe group, at 103.8 m, than in the healthy control subjects (p < 0.001). Conclusions: Adult patients with COVID-19, especially those with clinically severe pneumonia, still had residual symptoms and chest radiographic abnormalities, together with poorer quality of life and lower exercise capacity, one month after hospital discharge.

Development and validation of prognostic scoring system for COVID-19 severity in South India

Background

Development of a prediction model using baseline characteristics of COVID-19 patients at the time of diagnosis will aid us in early identification of the high-risk groups and devise pertinent strategies accordingly. Hence, we did this study to develop a prognostic-scoring system for predicting the COVID-19 severity in South India.

Methods

We undertook this retrospective cohort study among COVID-19 patients reporting to Hindu Mission Hospital, India. Multivariable logistic regression using the LASSO procedure was used to select variables for the model building, and the nomogram scoring system was developed with the final selected model. Model discrimination, calibration, and decision curve analysis (DCA) was performed.

Results

In total, 35.1% of the patients in the training set developed severe COVID-19 during their follow-up period. In the basic model, nine variables (age group, sex, education, chronic kidney disease, tobacco, cough, dyspnea, olfactory-gustatory dysfunction [OGD], and gastrointestinal symptoms) were selected and a nomogram was built using these variables. In the advanced model, in addition to these variables (except OGD), C-reactive protein, lactate dehydrogenase, ferritin, d-dimer, and CT severity score were selected. The discriminatory power (c-index) for basic model was 0.78 (95%CI: 0.74–0.82) and advanced model was 0.83 (95%CI: 0.79–0.87). DCA showed that both the models are beneficial at a threshold probability around 10–95% than treat-none or treat-all strategies.

Conclusion

The present study has developed two separate prognostic-scoring systems to predict the COVID-19 severity. This scoring system could help the clinicians and policymakers to devise targeted interventions and in turn reduce the COVID-19 mortality in India.

Supplementary information

The online version contains supplementary material available at 10.1007/s11845-021-02876-w.

Association between lead and cadmium co-exposure and systemic immune inflammation in residents living near a mining and smelting area in NW China

Exposure to both cadmium (Cd) and lead (Pb) can promote systemic inflammation. However, the effects of combined exposure to environmental levels of Cd and Pb on systemic immune inflammation have not been fully clarified. A total of 486 subjects (313 women and 173 men) living in either a control area or heavy metal-polluted area were included. Blood Cd and Pb and immune inflammation biomarkers were determined, including the eosinophil-lymphocyte ratio (ELR), neutrophil-lymphocyte ratio (NLR), platelet-lymphocyte ratio (PLR), lymphocyte-monocyte ratio (LMR), and systemic immune-inflammation index (SII); moreover, the associations between exposure markers and systemic inflammation markers were analysed. The exposure levels in the polluted area were significantly higher than those in the control area. The NLR, PLR, and SII of subjects in the polluted area were higher and the LMR was lower than in the control area. Blood Pb and Cd levels are associated with elevated or decreased immune inflammation biomarkers in subjects from the exposed and control areas. Furthermore, co-exposure to both Cd and Pb was divided into high, middle, and low exposure groups. The subjects in the high co-exposure group displayed higher levels of ELR, NLR, and SII compared with the middle and low co-exposure group, and LMR levels displayed the opposite trend. Our data demonstrate that Cd and Pb co-exposure is associated with systemic immune inflammation, and the immune inflammatory response is aggravated with an increased co-exposure to Cd and Pb.

Hemostatic System (Fibrinogen Level, D-Dimer, and FDP) in Severe and Non-Severe Patients With COVID-19: A Systematic Review and Meta-Analysis

SARS-CoV-2 in COVID-19 triggers abnormalities in coagulation parameters that can contribute to thrombosis. The goals of this research were to determine the levels of fibrinogen, D-dimer and FDP in COVID-19 patients. Following a systematic study, among 1198 articles, 35 studies were included in the meta-analysis of fibrinogen levels in both severe and non-severe groups. The funnel plot, Egger’s regression asymmetry test, and Begg’s test used to measure the bias of publications. All meta-analysis performed by comprehensive meta-analysis version 2 (CMA2). The pooled findings of fibrinogen levels revealed a significant rise in fibrinogen levels in severe COVID-19 than non-severe patients with COVID-19. The D-dimer and FDP levels were significantly higher in severe patients than non-severe patients with COVID-19 were. The levels of fibrinogen, D-dimer, and FDP have increased significantly in ICU patients compared to non-ICU patients. Although, levels of clotting parameters do not always correlate with the severity of disease, these findings showed the diagnostic importance for fibrinogen, D-dimer, and FDP in COVID-19. The presence of a continuous rise in serial measurements of fibrinogen, D-dimer, and FDP may predict that patients with COVID-19 may become critically ill.

Low-frequency, exhausted immune status of CD56dim NK cells and disordered inflammatory cytokine secretion of CD56bright NK cells associated with progression of severe HFMD, especially in EV71-infected patients

BACKGROUND

The roles of CD56^bright and CD56^dim natural killer (NK) subsets in the viral clearance and inflammatory processes of hand, foot, and mouth disease (HFMD) remain undefined.

METHODS

A total of 39 HCs and 55 patients were enrolled to analyze peripheral CD56^bright and CD56^dim NK cells according to cell number, surface receptors, cytotoxic activities, and cytokine production. The plasma concentrations of IL-2, IL-6, IL-10, IFN-γ, TNF-α,and MCP-1 were detected using ELSA.

RESULTS

Peripheral blood NK cells was significantly lower in severe patients than in HCs due to the dramatic loss of CD56^dim NK cells with no changes in the cell count of CD56^bright NK cells. For mild patients, decreased NKp46 expression coincided with enhanced cytolysis (CD107a, GNLY, and GrB) in CD56^dim NK cells and decreased NKG2A expression with enhanced IL-10 production in CD56^bright NK cells. In contrast, severe patients showed the dominant expression of NKG2A and decreased expression of NKG2D accompanied by cytotoxic dysfunction in CD56^dim NK cells. Imbalanced receptor expression coincided with the increased concentrations of TNF-α in CD56^bright NK cells. Moreover, EV71+ patients showed significantly decreased counts of CD56^dim NK cells with cytolysis dysfunction, displayed cytokine hypersecretion in CD56^bright NK cells, while the EV71- patients displayed significantly higher plasma cytokine concentrations. The changes in the immune function of NK subsets and their subpopulations were closely related to clinical inflammatory parameters.

CONCLUSIONS

Low-frequency, exhausted immune status of CD56^dim NK cells and disordered inflammatory cytokine secretion of CD56^bright NK cells were associated with the progression of severe HFMD, especially in EV71-infected patients. This promoted the severity of inflammatory disorders, leading to enhanced disease pathogenesis.

Novel Systemic Inflammation Markers to Predict COVID-19 Prognosis

Coronavirus disease 2019 (COVID-19) has resulted in a global pandemic, challenging both the medical and scientific community for the development of novel vaccines and a greater understanding of the effects of the SARS-CoV-2 virus. COVID-19 has been associated with a pronounced and out-of-control inflammatory response. Studies have sought to understand the effects of inflammatory response markers to prognosticate the disease. Herein, we aimed to review the evidence of 11 groups of systemic inflammatory markers for risk-stratifying patients and prognosticating outcomes related to COVID-19. Numerous studies have demonstrated the effectiveness of neutrophil to lymphocyte ratio (NLR) in prognosticating patient outcomes, including but not limited to severe disease, hospitalization, intensive care unit (ICU) admission, intubation, and death. A few markers outperformed NLR in predicting outcomes, including 1) systemic immune-inflammation index (SII), 2) prognostic nutritional index (PNI), 3) C-reactive protein (CRP) to albumin ratio (CAR) and high-sensitivity CAR (hsCAR), and 4) CRP to prealbumin ratio (CPAR) and high-sensitivity CPAR (hsCPAR). However, there are a limited number of studies comparing NLR with these markers, and such conclusions require larger validation studies. Overall, the evidence suggests that most of the studied markers are able to predict COVID-19 prognosis, however NLR seems to be the most robust marker.

Prognostic value of neutrophil-to-lymphocyte ratio in COVID-19 patients: A systematic review and meta-analysis

BACKGROUND

Neutrophil-to-lymphocyte ratio (NLR) is an accessible and widely used biomarker. NLR may be used as an early marker of poor prognosis in patients with COVID-19.

OBJECTIVE

To evaluate the prognostic value of the NLR in patients diagnosed with COVID-19.

METHODS

We conducted a systematic review and meta-analysis. Observational studies that reported the association between baseline NLR values (ie, at hospital admission) and severity or all-cause mortality in COVID-19 patients were included. The quality of the studies was assessed using the Newcastle-Ottawa Scale (NOS). Random effects models and inverse variance method were used for meta-analyses. The effects were expressed as odds ratios (ORs) and their 95% confidence intervals (CIs). Small study effects were assessed with the Egger's test.

RESULTS

We analysed 61 studies (n = 15 522 patients), 58 cohorts, and 3 case-control studies. An increase of one unit of NLR was associated with higher odds of severity (OR 6.22; 95%CI 4.93 to 7.84; P < .001) and higher odds of all-cause mortality (OR 12.6; 95%CI 6.88 to 23.06; P < .001). In our sensitivity analysis, we found that 41 studies with low risk of bias and moderate heterogeneity (I2  = 53% and 58%) maintained strong association between NLR values and both outcomes (severity: OR 5.36; 95% CI 4.45 to 6.45; P < .001; mortality: OR 10.42 95% CI 7.73 to 14.06; P = .005).

CONCLUSIONS

Higher values of NLR were associated with severity and all-cause mortality in hospitalised COVID-19 patients.

Complete blood count alterations in COVID-19 patients: A narrative review

Coronavirus disease 2019 (COVID-19) pandemic represents a scientific and social crisis. One of the main unmet needs for coronavirus disease 2019 is its unpredictable clinical course, which can rapidly change in an irreversible outcome. COVID-19 patients can be classified into mild, moderate, and severe. Several haematological parameters, such as platelets, white blood cell total count, lymphocytes, neutrophils, (together with neutrophil-lymphocyte and platelet-lymphocyte ratio), and haemoglobin were described to be associated with COVID-19 infection and severity. The purpose of these review is to describe the current state of the art about complete blood count alterations during COVID-19 infection, and to summarize the crucial role of some haematological parameters during the course of the disease. Decreased platelet, lymphocyte, haemoglobin, eosinophil, and basophil count, increased neutrophil count and neutrophil-lymphocyte and platelet-lymphocyte ratio have been associated with COVID-19 infection and a worse clinical outcome. Our study adds some novelty about the identification of effective biomarkers of progressive disease, and might be helpful for diagnosis, prevention of complications, and effective therapy.

Clinical significance of prognostic nutrition index in hospitalized patients with COVID-19: Results from single-center experience with systematic review and meta-analysis

BACKGROUND

We aimed to ascertain risk indicators of in-hospital mortality and severity as well as to provide a comprehensive systematic review and meta-analysis to investigate the prognostic significance of the prognostic nutrition index (PNI) as a predictor of adverse outcomes in hospitalized coronavirus disease 2019 (COVID-19) patients.

METHODS

In this cross-sectional study, we studied patients with COVID-19 who were referred to our hospital from February 16 to November 1, 2020. Patients with either a real-time reverse-transcriptase polymerase chain reaction test that was positive for COVID-19 or high clinical suspicion based on the World Health Organization (WHO) interim guidance were enrolled. A parallel systematic review/meta-analysis (in PubMed, Embase, and Web of Science) was performed.

RESULTS

A total of 504 hospitalized COVID-19 patients were included in this study, among which 101 (20.04%) patients died during hospitalization, and 372 (73.81%) patients were categorized as severe cases. At a multivariable level, lower PNI, higher lactate dehydrogenase (LDH), and higher D-dimer levels were independent risk indicators of in-hospital mortality. Additionally, patients with a history of diabetes, lower PNI, and higher LDH levels had a higher tendency to develop severe disease. The meta-analysis indicated the PNI as an independent predictor of in-hospital mortality (odds ratio [OR] = 0.80; P < .001) and disease severity (OR = 0.78; P = .009).

CONCLUSION

Our results emphasized the predictive value of the PNI in the prognosis of patients with COVID-19, necessitating the implementation of a risk stratification index based on PNI values in hospitalized patients with COVID-19.

High-density lipoprotein cholesterol: A marker of COVID-19 infection severity?

BACKGROUND AND AIMS

To systematically address all the relevant evidence of the association between high-density lipoprotein cholesterol (HDL-C) and COVID-19 infection.

METHODS

We searched PubMed, PubMed Central and medRxiv databases (up to May 2021) for studies related to HDL-C and COVID-19 infection. A qualitative synthesis of published prospective and retrospective studies for the role of low HDL-C levels on COVID-19 infection severity was performed.

RESULTS

Thirty-three studies (6 prospective, 27 retrospective) including 11,918 COVID-19 patients were eligible for the systematic review. Twelve studies compared HDL-C levels on admission in COVID-19 patients with healthy controls. In these 12 studies, COVID-19 patients had significantly lower HDL-C levels on admission compared with that of healthy controls. Twenty-eight studies observed the HDL-C levels among COVID-19 diagnosed patients, to establish the role of low HDL-C values in the prognosis of the infection. Twenty-four studies showed a correlation between low HDL-C levels with disease severity, while only 4 studies showed no association.

CONCLUSIONS

Low HDL-C levels should be added in the list of the others well-known risk factors for COVID-19 severity.

Evaluation of hematological parameters and inflammatory markers in children with COVID-19

Background

The aim of this study was to evaluate hematological parameters in children with COVID-19 and determine the effects of inflammatory biomarkers on the assessment of hospitalization.

Methods

This retrospective single-center study was performed on 633 children with COVID-19 between March 2020 and January 2021. The study population was separated into two groups: inpatients (n = 83) and outpatients (n = 550). Univariate and multivariate logistic regression was applied to identify risk factors for hospitalization.

Results

Lymphopenia (n = 228, 36%) was found mainly to be a hematological abnormality in all cases. Compared with outpatients, inpatients had significantly higher white blood cell (WBC) (p = 0.005), lymphocyte (p < 0.001), and platelet counts (p = 0.036), and significantly higher red cell distribution width (p = 0.001), C-reactive protein (CRP) (p = 0.003), procalcitonin (p = 0.001), d-dimer (p < 0.001), and lymphocyte to monocyte ratio values (p = 0.004). On the other hand, they had significantly lower values of hemoglobin (p < 0.001), neutrophil to lymphocyte ratio (p = 0.024), platelet lymphocyte ratio (p = 0.001), derivated neutrophil to lymphocyte ratio (p = 0.037), and mean platelet volume to lymphocyte ratio (p < 0.001). ROC analysis showed that WBC, CRP, and procalcitonin cutoff values were the best discriminated between inpatients and outpatients. The results for the areas under the curve of WBC, CRP, and procalcitonin used to assess patients’ hospitalization were 0.595 (95% CI 0.519–0.670, p = 0.005), 0.599 (95% CI 0.527–0.672, p = 0.003), and 0.599 (95% CI 0.525–0.673, p = 0.004), respectively.

Conclusion

We suggest that high WBC and procalcitonin levels can be used as independent predictors of hospitalization in children with COVID-19.