NLR: A Cost-effective Nomogram to Guide Therapeutic Interventions in COVID-19

A meta-analysis on first-trimester blood count parameters-is the neutrophil-to-lymphocyte ratio a potentially novel method for first-trimester preeclampsia screening?

Objective

Meta-analysis focusing on the role of first-trimester neutrophil-to-lymphocyte ratio (NLR) in the prediction of preeclampsia.

Data sources

PubMed, Scopus, Web of Science, Cochrane Library, and Embase databases were queried from inception up to December 31, 2022.

Study eligibility criteria

The study included all types of original research that was conducted in humans and values of NLR were measured during the first trimester, among patients who later developed preeclampsia, compared to the values of control groups.

Study appraisal and synthesis methods

Two reviewers independently performed data abstraction and quality appraisal, and disagreements were resolved by consensus and, if necessary, by the opinion of a third reviewer. During the analysis, PRISMA and MOOSE guidelines were followed. All statistical analyses were made with R.

Results

For the research on the predictive role of NLR values in the first trimester for preeclampsia, a total of 6 studies were selected for analysis, covering 2,469 patients. The meta-analysis revealed a 95% confidence interval (CI) for the effect size of 0.641 to 1.523, with a prediction interval of 0.027 to 2.137.

Conclusion

Based on the analysis, NLR is a promising biochemical marker for future pieces of research that try to find new screening methods for first-trimester preeclampsia. We encourage other researchers to examine NLR's predictive value combined with other markers in preeclampsia screening, this way being able to find new and affordable protocols for first-trimester preeclampsia screening.

Systematic review registration

identifier CRD42023392663.

Predictive Performance Neutrophil-to-Lymphocyte Ratio of Acute Tonsillitis with Deep Neck Space Infection in Adult Patients

The aim of this study was to examine the neutrophil-to-lymphocyte ratio (NLR) in patients diagnosed with a deep neck infection (DNI) to identify helpful indicators for the initial differential diagnosis. This study was conducted as a single-center, retrospective cohort study that utilized data from the electronic medical records of patients who visited the emergency department in a tertiary university hospital between February 2018 and April 2022. The study enrolled patients aged ≥18 years who were diagnosed with tonsillitis with or without DNI during the study period. The NLR of patients without DNI was 6.1 ± 5.03, and the NLR of patients with acute tonsillitis with DNI was 8.0 ± 5.67, showing significant differences. The rate of admission in the general wards (GWs) and ICUs was significantly higher in patients with DNI, and the length of hospital stay was also significantly longer in patients with DNI. Older age, male, lower body temperature, C-reactive protein, and NLR were significant independent risk factors for DNI in patients with tonsillitis. The cutoff value for predicting DNI in patients with body temperature <37.5 was 3.09. The NLR of patients with tonsillitis, especially those with normal body temperature, can be used to predict their prognosis.

Nomogram-based prediction model for survival of COVID-19 patients: A clinical study

The study aim to construct an effective model for predicting the survival period of COVID-19 patients.

METHODS

Clinical data of 386 COVID-19 patients were collected from December 2022 to January 2023. The patients were randomly divided into training and validation cohorts in a 7:3 ratio. LASSO regression and multivariate Cox regression analyses were used to identify prognostic factors, and a nomogram was constructed. Nomogram was evaluated using decision curve analysis, receiver operating characteristic curve, consistency index (c-index), and calibration curve.

RESULTS

86 patients (22.3%) died. A new nomogram for predicting the survival was established based on age, resting oxygen saturation, Blood urea nitrogen (BUN), c-reactive protein-to-albumin ratio (CAR), and pneumonia visual score. The decision curve indicated high clinical applicability. The nomogram c-indexes in the training and validation cohorts were 0.846 and 0.81, respectively. The area under the curves (AUCs) for the 15-day and 30-day survival probabilities were 0.906 and 0.869 in the training cohort, and 0.851 and 0.843 in the validation cohort. The calibration curves demonstrated consistency between predicted and actual survival probabilities.

CONCLUSIONS

Our nomogram has the capacity to assist clinical practitioners in estimating the survival rate of COVID-19 patients, thereby facilitating more optimal management strategies and therapeutic interventions with substantial clinical applicability.

Use of the neutrophil-to-lymphocyte ratio and an oxygen requirement to predict disease severity in patients with COVID-19

We investigated the association between complete blood count, including neutrophil-to-lymphocyte ratio (NLR) in combination with patient characteristics, and coronavirus disease (COVID-19) outcomes to identify the best prognostic indicator. We analyzed data of patients with confirmed COVID-19 from the nationwide database of the Japan COVID-19 Task Force between February 2020 and November 2021. A composite outcome was defined as the most severe condition, including noninvasive positive-pressure ventilation, high-flow nasal cannula, invasive mechanical ventilation, extracorporeal membrane oxygenation, or death. Of 2425 patients in the analysis, 472 (19.5%) experienced a composite outcome. NLR was the best predictor of composite outcomes, with an area under the curve (AUC) of 0.81, and a sensitivity and specificity of 72.3% and 75.7%, respectively, using a cut-off value of 5.04. The combination of NLR and an oxygen requirement on admission had the highest AUC (0.88). This simple combination may help identify patients at risk of progression to severe disease.

Frontline workers: Mediators of mucosal immunity in community acquired pneumonia and COVID-19

The current COVID-19 pandemic has highlighted a need to further understand lung mucosal immunity to reduce the burden of community acquired pneumonia, including that caused by the SARS-CoV-2 virus. Local mucosal immunity provides the first line of defence against respiratory pathogens, however very little is known about the mechanisms involved, with a majority of literature on respiratory infections based on the examination of peripheral blood. The mortality for severe community acquired pneumonia has been rising annually, even prior to the current pandemic, highlighting a significant need to increase knowledge, understanding and research in this field. In this review we profile key mediators of lung mucosal immunity, the dysfunction that occurs in the diseased lung microenvironment including the imbalance of inflammatory mediators and dysbiosis of the local microbiome. A greater understanding of lung tissue-based immunity may lead to improved diagnostic and prognostic procedures and novel treatment strategies aimed at reducing the disease burden of community acquired pneumonia, avoiding the systemic manifestations of infection and excess morbidity and mortality.

Comparative analysis of neutrophil to lymphocyte ratio and derived neutrophil to lymphocyte ratio with respect to outcomes of in-hospital coronavirus disease 2019 patients: A retrospective study

Introduction and objectives

In patients with coronavirus disease 2019 (COVID-19), several abnormal hematological biomarkers have been reported. The current study aimed to find out the association of neutrophil to lymphocyte ratio (NLR) and derived NLR (dNLR) with COVID-19. The objective was to compare the accuracy of both of these markers in predicting the severity of the disease.

Materials and methods

The study was conducted in a single-center having patients with COVID-19 with a considerable hospital stay. NLR is easily calculated by dividing the absolute neutrophil count (ANC) with the absolute lymphocyte count (ALC) {ANC/ALC}, while dNLR is calculated by ANC divided by total leukocyte count minus ANC {ANC/(WBC-ANC)}. Medians and interquartile ranges (IQR) were represented by box plots. Multivariable logistic regression was performed obtaining an odds ratio (OR), 95% CI, and further adjusted to discover the independent predictors and risk factors associated with elevated NLR and dNLR.

Results

A total of 1,000 patients with COVID-19 were included. The baseline NLR and dNLR were 5.00 (2.91–10.46) and 4.00 (2.33–6.14), respectively. A cut-off value of 4.23 for NLR and 2.63 for dNLR were set by receiver operating characteristic (ROC) analysis. Significant associations of NLR were obtained by binary logistic regression for dependent outcome variables as ICU stay (p < 0.001), death (p < 0.001), and invasive ventilation (p < 0.001) while that of dNLR with ICU stay (p = 0.002), death (p < 0.001), and invasive ventilation (p = 0.002) on multivariate analysis when adjusted for age, gender, and a wave of pandemics. Moreover, the indices were found correlating with other inflammatory markers such as C-reactive protein (CRP), D-dimer, and procalcitonin (PCT).

Conclusion

Both markers are equally reliable and sensitive for predicting in-hospital outcomes of patients with COVID-19. Early detection and predictive analysis of these markers can allow physicians to risk assessment and prompt management of these patients.

COVID-19 is more dangerous for older people and its severity is increasing: a case-control study

Coronavirus disease 2019 (COVID-19) triggers important changes in routine blood tests. In this retrospective case-control study, biochemical, hematological and inflammatory biomarkers between March 10, 2020, and November 30, 2020 from 3969 COVID-19 patients (3746 in the non-intensive care unit (non-ICU) group and 223 in the ICU group) were analyzed by dividing into three groups as spring, summer and autumn. In the non-ICU group, lymphocyte to monocyte ratio was lower in autumn than the other two seasons and neutrophil to lymphocyte ratio was higher in autumn than the other two seasons. Also, monocyte and platelet were higher in spring than autumn; and eosinophil, hematocrit, hemoglobin, lymphocyte, and red blood cells decreased from spring to autumn. In the non-ICU group, alanine aminotransferase and gamma-glutamyltransferase gradually increased from spring to autumn, while albumin, alkaline phosphatase, calcium, total bilirubin and total protein gradually decreased. Additionally, C-reactive protein was higher in autumn than the other seasons, erythrocyte sedimentation rate was higher in autumn than summer. The changes in routine blood biomarkers in COVID-19 varied from the emergence of the disease until now. Also, the timely changes of blood biomarkers were mostly more negative, indicating that the disease progresses severely. The study was approved by the Erzincan Binali Yildirim University Non-interventional Clinical Trials Ethic Committee (approval No. 86041) on June 21, 2021.

Procoagulant Microvesicles in COVID-19 Patients: Possible Modulators of Inflammation and Prothrombotic Tendency

Background

The hypercoagulability and thrombotic tendency in coronavirus disease 2019 (COVID-19) is multifactorial, driven mainly by inflammation, and endothelial dysfunction. Elevated levels of procoagulant microvesicles (MVs) and tissue factor–bearing microvesicles (TF-bearing MVs) have been observed in many diseases with thrombotic tendency. The current study aimed to measure the levels of procoagulant MVs and TF-bearing MVs in patients with COVID-19 and healthy controls and to correlate their levels with platelet counts, D-Dimer levels, and other proposed calculated inflammatory markers.

Materials and Methods

Forty ICU-admitted patients with COVID-19 and 37 healthy controls were recruited in the study. Levels of procoagulant MVs and TF-bearing MVs in the plasma of the study population were measured using enzyme linked immunosorbent assay.

Results

COVID-19 patients had significantly elevated levels of procoagulant MVs and TF-bearing MVs as compared with healthy controls (P<0.001). Procoagulant MVs significantly correlated with TF-bearing MVs, D-dimer levels, and platelet count, but not with calculated inflammatory markers (neutrophil/lymphocyte ratio, platelet/lymphocyte ratio, and platelet/neutrophil ratio).

Conclusion

Elevated levels of procoagulant MVs and TF-bearing MVs in patients with COVID-19 are suggested to be (i) early potential markers to predict the severity of COVID-19 (ii) a novel circulatory biomarker to evaluate the procoagulant activity and severity of COVID-19.

Comparison of Clinical and Diagnostic Features of Pediatric Oncology Patients With or Without COVID-19 Infection: A Retrospective Chart Review

There is a scarcity of data summarizing the clinical picture, laboratory, and imaging findings and outcome in children with malignancy and coronavirus disease 2019 (COVID-19) infection. This study characterizes a detailed comparison of pediatric oncology patients with and without COVID infection. A retrospective study was conducted at The Indus Hospital, Karachi, from March 2020 to June 2020. Clinical presentation, laboratory and imaging findings, disease severity, and outcome were compared between cohorts. The mean age of children with and without COVID was 8.0±4.9 and 7.4±4.1 years, respectively. Hematologic malignancy comprised the largest number of patients, followed by solid tumors. Lymphocytosis and low neutrophil-lymphocyte ratio was observed in the COVID positive group. Cardiac dysfunction (1.4% vs. 0%), acute respiratory distress syndrome (8% vs. 0%) and lower peripheral capillary oxygen saturation/fraction of inspired oxygen ratio (473 vs. 486) found to be associated with severe disease in COVID positive group (P<0.05). Overall mortality in children with COVID was 6.8% versus 2.7% in children without COVID. Pediatric patients with malignancy have different clinical features and laboratory parameters as compared with children without malignancy. Acute respiratory distress syndrome, absolute lymphocytosis and low neutrophil-lymphocyte ratio is associated with severe disease in children with malignancy and COVID infection. In contrast to adults, biochemical markers and complete blood count parameters do not help recognize COVID infection in pediatric patients with malignancy.

The Correlation between Neutrophil-to-Lymphocyte Ratio with C-reactive Protein and D-dimer Level among Indonesian COVID-19 Cases

BACKGROUND: Coronavirus disease-19 (COVID-19) pandemic has resulted high number of mortalities globally. Several inflammatory and coagulation biomarkers have been studied for predicting and differentiating severe COVID-19 such as C-reactive protein (CRP) and D-dimer. However, those markers may not readily available in developing countries. AIM: The aim of the study was to assess the utility of neutrophil-to-lymphocyte ratio (NLR), a widely available and inexpensive laboratory examination, as reliable inflammatory biomarkers for Indonesian COVID-19 patients; by analyzing the correlation of NLR level with CRP and D-dimer plasma level. METHODS: We conducted cross-sectional study in Professor Dr. R.D. Kandou Hospital, Manado involving RT-PCR confirmed and hospitalized COVID-19 patients. Lymphocyte count, NLR, CRP, and D-dimer were examined in severe and non-severe COVID-19 cases at hospital admission. Correlation test was done using Spearman correlation test. RESULTS: A total of 40 COVID-19 patients were included in the analysis, with 50% having mild disease and other half having severe disease. The NLR, CRP, and D-dimer were significantly higher in severe COVID-19 group. Significant correlation was found between NLR and CRP (p = 0.001 and r = 0.506) and also with D-dimer level (p = 0.000 and r = 0.570) in differentiating severity of COVID-19. CONCLUSION: NLR is correlated with CRP and D-dimer level; therefore, NLR may serve as reliable, cost-effective, and practical inflammatory biomarker for differentiating severe and non-severe COVID-19 cases.

C-reactive protein and neutrophil-lymphocyte ratio as predictors of mortality in coronavirus disease 2019

OBJECTIVE

This study investigates whether C-reactive protein, platelet-lymphocyte ratio, and neutrophil-lymphocyte ratio could be useful to predict mortality in COVID-19.

METHODS

Data of 635 patients with COVID-19 followed up in Sinop Ataturk State Hospital from February to May 2020 were evaluated retrospectively. Diagnosis of COVID-19 was made according to the interim guidance of the World Health Organization. Patients were grouped into two groups based on mortality as survived and non-survived patients. Age, gender, neutrophil-lymphocyte ratio, platelet-lymphocyte ratio, and C-reactive protein of the groups were investigated and compared.

RESULTS

The mean age of the participants was 55.8±22.3 years. Among the patients, 584 survived and 51 patients died. Age was significantly different between the groups, 54.2±22.3 in the survived group and 75.6±11.1 in the dead group (p=0.000). In addition, neutrophil, C-reactive protein, and neutrophil-lymphocyte ratio values were significantly higher in the dead group (p=0.000). platelet-lymphocyte ratio was slightly higher in the dead group, but this difference was not significant (p=0.42). The area under the curve values for age, lymphocyte, platelet, C-reactive protein, and neutrophil-lymphocyte ratio are 0.797, 0.424, 0.485, 0.778, and 0.729, respectively.

CONCLUSIONS

Our results showed that neutrophil-lymphocyte ratio and C-reactive protein are significantly higher in patients leading to death and could be effective biomarkers in predicting COVID-19 fatality. Furthermore, C-reactive protein could be used as an independent biomarker to predict death in patients with COVID-19, regardless of gender and age (p=0.000).

Prospective Analysis Between Neutrophil-to-Lymphocyte Ratio on Admission and Development of Delirium Among Older Hospitalized Patients With COVID-19

Objective: To examine any prospective association between neutrophil-to-lymphocyte ratio (NLR) at hospital admission and subsequent delirium in older COVID-19 hospitalized patients comparing by sex and age groups. Methods: The sample consisted of 1,785 COVID-19 adult inpatients (minimum sample size required of 635 participants) admitted to a public general hospital in Madrid (Spain) between March 16th and April 15th, 2020. Variables were obtained from electronic health records. Binary logistic regression models were performed between baseline NLR and delirium adjusting for age, sex, medical comorbidity, current illness severity, serious mental illness history and use of chloroquine and dexamethasone. An NLR cut-off was identified, and stratified analyses were performed by age and sex. Also, another biomarker was tested as an exposure (the systemic immune-inflammation index -SII). Results: 55.3% of the patients were men, with a mean age of 66.8 years. Roughly 13% of the patients had delirium during hospitalization. NLR on admission predicted subsequent delirium development (adjusted OR = 1.02, 95 percent CI: 1.00-1.04, p = 0.024). Patients between 69 and 80 years with NLR values > 6.3 presented a twofold increased risk for delirium (p = 0.004). There were no sex differences in the association between baseline NLR and delirium (p > 0.05) nor SII predicted delirium development (p = 0.341). Conclusion: NLR is a good predictor of delirium during hospitalization, especially among older adults, independently of medical comorbidity, illness severity, and other covariates. Routine blood tests on admission might provide valuable information to guide the decision-making process to be followed with these especially vulnerable patients.

MPR and NLR as Prognostic Markers in ICU-Admitted Patients with COVID-19 in Jazan, Saudi Arabia

Objective

The aims of the current study were to evaluate the importance of MPR and NLR as prognostic markers in ICU-admitted COVID-19 patients and to investigate the impact of COVID-19 on hematological and coagulation parameters in patients from Jazan region of Saudi Arabia.

Methods

This retrospective study was conducted between October 2020 and January 2021 at King Fahad Central Hospital, Jazan region. Medical files, which included the results of complete blood count (CBC), calculated mean platelet volume to platelet count ratio (MPR) and neutrophils-to-lymphocytes ratio (NLR) parameters, coagulation profile and D-dimer test, of 96 (64 male and 32 female) COVID-19-infected patients admitted to the intensive care unit were reviewed. Associations between the test results and COVID-19 infection outcomes (discharged [DC] or passed away [PA]) were measured.

Results

The results of the current study demonstrate overall significant differences in CBC parameters between PA group as compared to DC group (P < 0.05). The PA group had a significantly elevated MPR (10.15±12.16 vs 4.04±1.5; P < 0.01) and NLR (18.29±19.82 vs 7.35±9.68; P < 0.01) as compared to the DC group, suggesting an association between these parameters and mortality. Odds ratios analysis also showed that adjustment for demographic variables and comorbidities did not weaken the observed association.

Conclusion

Elevated MPR and NLR are associated with poor prognosis in COVID-19 patients and could be useful as therapy management indicators.

Prognostic value of neutrophil-to-lymphocyte ratio in COVID-19 compared with Influenza and respiratory syncytial virus infection

A high neutrophil to lymphocyte ratio (NLR) is considered an unfavorable prognostic factor in various diseases, including COVID-19. The prognostic value of NLR in other respiratory viral infections, such as Influenza, has not hitherto been extensively studied. We aimed to compare the prognostic value of NLR in COVID-19, Influenza and Respiratory Syncytial Virus infection (RSV). A retrospective cohort of COVID-19, Influenza and RSV patients admitted to the Tel Aviv Medical Center from January 2010 to October 2020 was analyzed. Laboratory, demographic, and clinical parameters were collected. Two way analyses of variance (ANOVA) was used to compare the association between NLR values and poor outcomes among the three groups. ROC curve analyses for each virus was applied to test the discrimination ability of NLR. 722 COVID-19, 2213 influenza and 482 RSV patients were included. Above the age of 50, NLR at admission was significantly lower among COVID-19 patients (P < 0.001). NLR was associated with poor clinical outcome only in the COVID-19 group. ROC curve analysis was performed; the area under curve of poor outcomes for COVID-19 was 0.68, compared with 0.57 and 0.58 for Influenza and RSV respectively. In the COVID-19 group, multivariate logistic regression identified a high NLR (defined as a value above 6.82) to be a prognostic factor for poor clinical outcome, after adjusting for age, sex and Charlson comorbidity score (odds ratio of 2.9, P < 0.001). NLR at admission is lower and has more prognostic value in COVID-19 patients, when compared to Influenza and RSV.

Early Prediction of Severe COVID-19 in Patients by a Novel Immune-Related Predictive Model

During the progression of coronavirus disease 2019 (COVID-19), immune response and inflammation reactions are dynamic events that develop rapidly and are associated with the severity of disease. Here, we aimed to develop a predictive model based on the immune and inflammatory response to discriminate patients with severe COVID-19. COVID-19 patients were enrolled, and their demographic and immune inflammatory reaction indicators were collected and analyzed. Logistic regression analysis was performed to identify the independent predictors, which were further used to construct a predictive model. The predictive performance of the model was evaluated by receiver operating characteristic curve, and optimal diagnostic threshold was calculated; these were further validated by 5-fold cross-validation and external validation. We screened three key indicators, including neutrophils, eosinophils, and IgA, for predicting severe COVID-19 and obtained a combined neutrophil, eosinophil, and IgA ratio (NEAR) model (NEU [10⁹/liter] - 150×EOS [10⁹/liter] + 3×IgA [g/liter]). NEAR achieved an area under the curve (AUC) of 0.961, and when a threshold of 9 was applied, the sensitivity and specificity of the predicting model were 100% and 88.89%, respectively. Thus, NEAR is an effective index for predicting the severity of COVID-19 and can be used as a powerful tool for clinicians to make better clinical decisions. IMPORTANCE The immune inflammatory response changes rapidly with the progression of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and is responsible for clearance of the virus and further recovery from the infection. However, the intensified immune and inflammatory response in the development of the disease may lead to more serious and fatal consequences, which indicates that immune indicators have the potential to predict serious cases. Here, we identified both eosinophils and serum IgA as prognostic markers of COVID-19, which sheds light on new research directions and is worthy of further research in the scientific research field as well as clinical application. In this study, the combination of NEU count, EOS count, and IgA level was included in a new predictive model of the severity of COVID-19, which can be used as a powerful tool for better clinical decision-making.

Research on Influencing Factors and Classification of Patients With Mild and Severe COVID-19 Symptoms

Objective

To analyze the epidemiological history, clinical symptoms, laboratory testing parameters of patients with mild and severe COVID-19 infection, and provide a reference for timely judgment of changes in the patients’ conditions and the formulation of epidemic prevention and control strategies.

Methods

A retrospective study was conducted in this research, a total of 90 patients with COVID-19 infection who received treatment from January 21 to March 31, 2020 in the Ninth People’s Hospital of Dongguan City were selected as study subject. We analyzed the clinical characteristics of laboratory-confirmed patients with COVID-19, used the oversampling method (SMOTE) to solve the imbalance of categories, and established Lasso-logistic regression and random forest models.

Results

Among the 90 confirmed COVID-19 cases, 79 were mild and 11 were severe. The average age of the patients was 36.1 years old, including 49 males and 41 females. The average age of severe patients is significantly older than that of mild patients (53.2 years old vs 33.7 years old). The average time from illness onset to hospital admission was 4.1 days and the average actual hospital stay was 18.7 days, both of these time actors were longer for severe patients than for mild patients. Forty-eight of the 90 patients (53.3%) had family cluster infections, which was similar among mild and severe patients. Comorbidities of underlying diseases were more common in severe patients, including hypertension, diabetes and other diseases. The most common symptom was cough [45 (50%)], followed by fever [43 (47.8%)], headache [7 (7.8%)], vomiting [3 (3.3%)], diarrhea [3 (3.3%)], and dyspnea [1 (1.1%)]. The laboratory findings of patients also included leukopenia [13(14.4%)] and lymphopenia (17.8%). Severe patients had a low level of creatine kinase (median 40.9) and a high level of D-dimer. The median NLR of severe patients was 2.82, which was higher than that of mild patients. Logistic regression showed that age, phosphocreatine kinase, procalcitonin, the lymphocyte count of the patient on admission, cough, fatigue, and pharynx dryness were independent predictors of COVID-19 severity. The classification of random forest was predicted and the importance of each variable was displayed. The variable importance of random forest indicates that age, D-dimer, NLR (neutrophil to lymphocyte ratio) and other top-ranked variables are risk factors.

Conclusion

The clinical symptoms of COVID-19 patients are non-specific and complicated. Age and the time from onset to admission are important factors that determine the severity of the patient’s condition. Patients with mild illness should be closely monitored to identify those who may become severe. Variables such as age and creatine phosphate kinase selected by logistic regression can be used as important indicators to assess the disease severity of COVID-19 patients. The importance of variables in the random forest further complements the variable feature information.

Evaluation of CBC Parameters in Relation to PCR Test Results in Diagnosing Pediatric COVID-19 Disease

Objective This study aimed to investigate whether complete blood count parameters have predictive properties in diagnosing coronavirus disease 2019 (COVID-19) in regard to positive polymerase chain reaction (PCR) test in children with a prediagnosis of COVID-19, and whether these parameters are related to the severity of clinical findings in children with COVID-19.

Methods This retrospective cross-sectional study included children who were hospitalized with a possible diagnosis of COVID-19 and had undergone PCR testing in the COVID-19 children's clinic. Probable case definition was made according to the COVID-19 diagnostic and therapeutic guidelines of the Ministry of Health of the Republic of Turkey.

Results A total of 133 patients were included in the study, of which 46 (34.6%) were negative for the PCR test and 87 (65.4%) were positive for the PCR test. white blood cell (WBC), neutrophil, lymphocyte, and platelet levels were significantly lower in the PCR positive group than in the PCR negative group. The platelet to mean platelet volume ratio (PLT/MPV) was significantly lower in the PCR positive group than the PCR negative group, whereas the platelet distribution width (PDW) of the PCR positive patient group was significantly higher than the PCR negative group. For the multivariable model with PDW and neutrophil to lymphocyte ratio/age factors included, F1 score was 0.864, area under the receiver operating characteristics was 0.804, and area under the precision-recall curve was 0.873. The decision tree had a 72.9% cross-validation accuracy value.

Conclusion WBC, neutrophils, lymphocytes, platelets, PLT/MPV, and PDW parameters could be used in conjunction with clinical symptoms and findings to predict the PCR test result.

A new haematocytometric index: Predicting severity and mortality risk value in COVID-19 patients

INTRODUCTION

Coronavirus disease 2019 (COVID-19) caused by SARS-CoV-2 virus, is a major public health concern spanning from healthy carriers to patients with life-threatening conditions. Although most of COVID-19 patients have mild-to-moderate clinical symptoms, some patients have severe pneumonia leading to death. Therefore, the early prediction of disease prognosis and severity is crucial in COVID-19 patients. The main objective of this study is to evaluate the haemocytometric parameters and identify severity score associated with SARS-CoV-2 infection.

METHODS

Clinical and laboratory records were retrospectively reviewed from 97 cases of COVID-19 admitted to hospitals in Istanbul, Turkey. The patient groups were subdivided into three major groups: Group 1 (Non-critical): 59 patients, Group 2 (Critical-Survivors): 23 patients and Group 3 (Critical-Non-survivors):15 patients. These data was tested for correlation, including with derived haemocytometric parameters. The blood analyses were performed the Sysmex XN-series automated hematology analyser using standard laboratory protocols. All statistical testing was undertaken using Analyse-it software.

RESULTS

97 patients with COVID-19 disease and 935 sequential complete blood count (CBC-Diff) measurements (days 0-30) were included in the final analyses. Multivariate analysis demonstrated that red cell distribution width (RDW) (>13.7), neutrophil to lymphocyte ratio (NLR) (4.4), Hemoglobin (Hgb) (<11.4 gr/dL) and monocyte to neutrophil ratio (MNR) (0.084) had the highest area under curve (AUC) values, respectively in discrimination critical patients than non-critical patients. In determining Group 3, MNR (<0.095), NLR (>5.2), Plateletcount (PLT) (>142 x103/L) and RDW (>14) were important haemocytometric parameters, and the mortality risk value created by their combination had the highest AUC value (AUC = 0.911, 95% CI, 0886-0.931). Trend analysis of CBC-Diff parameters over 30 days of hospitalization, NLR on day 2, MNR on day 4, RDW on day 6 and PLT on day 7 of admission were found to be the best time related parameters in discrimination non-critical (mild-moderate) patient group from critical (severe and non-survivor) patient group.

CONCLUSION

NLR is a strong predictor for the prognosis for severe COVID-19 patients when the cut-off chosen was 4.4, the combined mortality risk factor COVID-19 disease generated from RDW-CV, NLR, MNR and PLT is best as a mortality haematocytometric index.

Prognostic value of serum lactate dehydrogenase in hospitalized patients with Covid-19

Background: Biochemical markers in COVID-19 remain to be defined. We analyzed the usefulness of LDH and ferritin in predicting outcome.

Methods: This retrospective study analyzed ferritin and LDH concentrations obtained during the first 11 days of hospitalization in COVID-19 patients. We compared the change in ferritin and LDH concentrations obtained on each day of hospital admission with respect to baseline values between patients with favorable and unfavorable outcomes. We used receiver operating curve analysis to determine cutoffs for predicting outcomes.

Results: We analyzed 387 patients. For determinations done on the 9th day, increases in LDH concentrations > 14.6% over the baseline yielded 80% positive predictive value, and a lack of increase yielded 96% negative predictive value for unfavorable outcomes. The change in ferritin concentration yielded lower predictive values.

Conclusion: The percentage of change in LDH with respect to the baseline on the 9th day of hospitalization can predict outcome..

The use of neutrophil-to-lymphocyte ratio (NLR) as a marker for COVID-19 infection in Saudi Arabia: A case-control retrospective multicenter study

Objectives:

To assess the neutrophil-to-lymphocyte ratio (NLR) diagnostic and prognostic value in the context of Coronavirus disease-2019 (COVID-19) infection in Saudi Arabia.

Methods:

A case-control study in which 701 confirmed COVID-19 patients (of which 41 were intensive care unit [ICU]-admitted) and 250 control subjects were enrolled. The study was conducted retrospectively in October on patients admitted to 3 separate hospitals in Saudi Arabia namely: King Abdullah Bin Abdulaziz University Hospital (Riyadh), Ohud Hospital (Madinah), and Nojood Medical Center (Madinah) between May and September 2020. Neutrophil-to-lymphocyte ratio was calculated based on absolute neutrophil and lymphocyte count. Institutional ethical approval was obtained prior to the study.

Results:

Patients (median age 35 years), of which 54.8% were females, were younger than the control cohort (median age 48 years). Patients had significantly higher NLR compared to the control group. Intensive care unit admitted patients had significantly higher platelet, WBC and neutrophil counts. The ICU patients’ NLR was almost twice as of the non-intensive patients. The NLR value of 5.5 was found to be of high specificity (96.4%) and positive predictive value (91.4%) in diagnosing COVID-19. Furthermore, it had a very good sensitivity (86.4%) in predicting severe forms of disease, such as, ICU admission.

Conclusion:

Neutrophil-to-lymphocyte ratio is an important tool in determining the COVID-19 clinical status. This study further confirms the prognostic value of NLR in detecting severe infection, and those patients with high NLR should be closely monitored and managed.

Prevalence of SARS-CoV-2 Specific Antibodies in Asymptomatic Hemodialysis Patients

Background: Since the outbreak of the new coronavirus pandemic, the importance of carrying out an infection check to prevent acquisition and transmission among end-stage renal disease patients (ESRD) under maintenance hemodialysis (MHD) has become a major concern in the health care system. Applying serology screening tests could enlighten the view with regards to disease prevalence in dialysis wards.Methods: We subjected 328 end-stage renal disease patients to maintenance hemodialysis. After dividing patients into suspicious and non-suspicious groups for COVID-19 infection based on their clinical manifestation, they were investigated for SARS-CoV-2 specific IgM and IgG screening against nucleoprotein (NP), spike protein (SP), and receptor-binding domain (RBD), utilizing our recently developed ELISA tests.Results: We found that approximately 10.1% of asymptomatically tested cases were antibody positive. Although IgG positivity showed a higher prevalence than IgM across all three virus antigen subunits, there were no significant differences among mentioned immunoglobulins of the studied groups. The most prevalent antibody was from the IgG subtype against virus nucleoprotein (NP), while the lowest prevalence was attributed to receptor-binding domain (RBD) IgM.Conclusion: High seropositive rate among asymptomatic end-stage renal disease patients, as a sample of high-risk population, reflected the importance of considering SARS-CoV-2 specific antibody screening for disease containment.

Risk factors for mortality in hospitalized patients with COVID-19 from three hospitals in Peru: a retrospective cohort study

BACKGROUND

Peru was one of the countries with the highest COVID-19 mortality worldwide during the first stage of the pandemic. It is then relevant to evaluate the risk factors for mortality in patients hospitalized for COVID-19 in three hospitals in Peru in 2020, from March to May, 2020.  Methods: We carried out a retrospective cohort study. The population consisted of patients from three Peruvian hospitals hospitalized for a diagnosis of COVID-19 during the March-May 2020 period. Independent sociodemographic variables, medical history, symptoms, vital functions, laboratory parameters and medical treatment were evaluated. In-hospital mortality was assessed as the outcome. We performed Cox regression models (crude and adjusted) to evaluate risk factors for in-hospital mortality. Hazard ratios (HR) with their respective 95% confidence intervals (95% CI) were calculated.  Results: We analyzed 493 hospitalized adults; 72.8% (n=359) were male and the mean age was 63.3 ± 14.4 years. COVID-19 symptoms appeared on average 7.9 ± 4.0 days before admission to the hospital, and the mean oxygen saturation on admission was 82.6 ± 13.8. While 67.6% (n=333) required intensive care unit admission, only 3.3% (n=16) were admitted to this unit, and 60.2% (n=297) of the sample died. In the adjusted regression analysis, it was found that being 60 years old or older (HR=1.57; 95% CI: 1.14-2.15), having two or more comorbidities (HR=1.53; 95% CI: 1.10-2.14), oxygen saturation between 85-80% (HR=2.52; 95% CI: 1.58-4.02), less than 80% (HR=4.59; 95% CI: 3.01-7.00), and being in the middle (HR=1.65; 95% CI: 1.15-2.39) and higher tertile (HR=2.18; 95% CI: 1.51-3.15) of the neutrophil-to-lymphocyte ratio, increased the risk of mortality.  Conclusions: The risk factors found agree with what has been described in the literature and allow the identification of vulnerable groups in whom monitoring and early identification of symptoms should be prioritized in order to reduce mortality.

Hematological and Inflammatory Parameters to Predict the Prognosis in COVID-19

We aimed to evaluate the predictive ability of hematological and inflammatory parameters for mortality in COVID-19 patients. This was a retrospective study of hospitalized COVID-19 patients over 18 years old between March 2020 and May 2020. Patients were diagnosed to have COVID-19 based either on chest computed tomography findings or reverse transcriptase-polymerase chain reaction test. Age, gender, chronic medical conditions, and laboratory values including hemogram parameters (white blood cell, neutrophil, lymphocyte, and platelet counts), neutrophil to lymphocyte ratio, D-dimer, ferritin, fibrinogen, C-reactive protein, procalcitonin, prothrombin time, activated partial thromboplastin time and the international normalized ratio were recorded. Overall, we included 302 patients. Of these, 148 patients were male; the male to female ratio was 0.961. The mean age of the entire study cohort was 57.1 ± 17.6 years. The most common chronic medical condition was hypertension (38.1%). Half of the patients received low molecular weight heparin. During the study period, 25 patients (8.2%) died. White blood cell count and neutrophil count were significantly higher, whereas lymphocyte count was significantly lower in the deceased patients. The median neutrophil to lymphocyte ratio was 11.6 in the deceased patients, it was significantly higher than the surviving patients (p < 0.001). The values of C-reactive protein, procalcitonin, D-dimer, and ferritin were significantly higher among the deceased patients. Prothrombin time, activated partial thromboplastin time and the international normalized ratio were significantly longer in the deceased group compared with the surviving group. Logistic regression analysis showed age > 65 years, neutrophil to lymphocyte ratio, activated partial thromboplastin time, and hypertension as the independent predictors of mortality. The rate of abnormal inflammatory and hematologic-coagulation parameters increased with the COVID-19 severity. Age > 65 years, hypertension, activated partial thromboplastin time and neutrophil to lymphocyte ratio were the independent predictors of mortality.