Associations between hematological parameters and disease severity in patients with SARS-CoV-2 infection

Machine learning algorithm approach to complete blood count can be used as early predictor of COVID-19 outcome

Although the SARS-CoV-2 infection has established risk groups, identifying biomarkers for disease outcomes is still crucial to stratify patient risk and enhance clinical management. Optimal efficacy of COVID-19 antiviral medications relies on early administration within the initial 5 d of symptoms, assisting high-risk patients in avoiding hospitalization and improving survival chances. The complete blood count (CBC) can be an efficient and affordable option to find biomarkers that predict the COVID-19 prognosis due to infection-induced alterations in various blood parameters. This study aimed to associate hematological parameters with different COVID-19 clinical forms and utilizes them as disease outcome predictors. We performed a CBC in blood samples from 297 individuals with COVID-19 from Belo Horizonte, Brazil. Statistical analysis, as well as ROC Curves and machine learning Decision Tree algorithms were used to identify correlations, and their accuracy, between blood parameters and disease severity. In the initial 4 d of infection, traditional hematological COVID-19 alterations, such as lymphopenia, were not yet apparent. However, the monocyte percentage and granulocyte-to-lymphocyte ratio (GLR) proved to be reliable predictors for hospitalization, even in cases where patients exhibited mild symptoms that later progressed to hospitalization. Thus, our findings demonstrate that COVID-19 patients with monocyte percentages lower than 7.7% and a GLR higher than 8.75 are assigned to the hospitalized group with a precision of 86%. This suggests that these variables can serve as important biomarkers in predicting disease outcomes and could be used to differentiate patients at hospital admission for managing therapeutic interventions, including early antiviral administration. Moreover, they are simple parameters that can be useful in minimally equipped health care units.

Pre-clinical acute oral toxicity and subacute neurotoxicity risk assessments on sprague dawley rats treated with single dose or repeated doses of flavonoid-enriched fraction extracted from Oroxylum indicum leaves

Oroxylum indicum possesses promising flavonoid secondary metabolites. However, translation of these compounds into clinical practice for neurological disease treatment is halted as the toxicity and safety profile of the plant extracts are yet to be determined. This study was conducted to assess the acute oral toxicity and subacute neurotoxicity that could be imposed by the flavonoid-enriched fraction (FEF) extracted from O. indicum leaves, by strictly following the procedures set in Organization for Economic Co-operation and Development (OECD) Guidelines No.420 and 424. It was found that at the highest dosage (2000 mg/kg b.wt), no death or toxicity-related behavioral changes were observed. No significant alteration in hematological and serum biochemical parameters beyond the standard laboratory range was observed. Detailed histopathological examination, as verified by clinical pathologist, revealed absence of detectable inflammation, changes in any macroscopic and microscopic tissue abnormalities in all vital organ of the treated rats. Moreover, neurological functional test of rats treated with repeated doses of FEF for 28 d also showed absence of neurological abnormality, suggesting negative long term side effects of this fraction on the animal. In conclusion, this study presented valuable pre-clinical safety validation of a high-quality herbal medicinal product, setting the foundation for its future application in clinical setting.

Association between Hematological Parameters and Severity of COVID-19 disease

Background

This study aimed to determine the relationships between hematological parameters- hemoglobin, Total Leucocyte Counts (TLC), platelet counts, Absolute Neutrophil Counts (ANC), Absolute Lymphocyte Counts (ALC), Neutrophil Lymphocyte Ratio (NLR), Systemic Immune Inflammatory Index (SII), Neutrophil Monocyte Ratio (NMR), Platelet Lymphocyte Ratio (PLR) and the severity of COVID-19 disease and their use in predicting severity of COVID-19 disease.

Methods and Material

This was a prospective, observational, single-center study of 573 symptomatic adult inpatients of COVID 19 admitted to our tertiary care center.

Statistical analysis used

The above-mentioned hematological parameter levels were noted and compared between the two categories of COVID-19 disease, namely non-severe and severe COVID-19 using logistic regression methods. Their cut-off values were detected using the ROC curve.

Results

The median TLC, ANC, NLR, SII, NMR, PLR were notably higher in patients with severe COVID-19 than in those with non-severe COVID-19. Logistic regression analysis showed that NMR (OR=1.029, p=0.006) and ALC (OR=0.999, p=0.002) were statistically significant independent predictors of COVID-19 severity.

Conclusions

The hematological parameters mentioned, can be used for predicting severe COVID-19 disease at admission. ALC and NMR levels could be used as hematological markers to predict severity of COVID-19 in adult patients with their cut off values being < 1105 cells/cubic millimeter and > 10.434 respectively.

Genetic background of hematological parameters in Holstein cattle based on genome-wide association and RNA sequencing analyses

Hematological parameters refer to the assessment of changes in the number and distribution of blood cells, including leukocytes (LES), erythrocytes (ERS), and platelets (PLS), which are essential for the early diagnosis of hematological system disorders and other systemic diseases in livestock. In this context, the primary objectives of this study were to investigate the genomic background of 19 hematological parameters in Holstein cattle, focusing on LES, ERS, and PLS blood components. Genetic and phenotypic (co)variances of hematological parameters were calculated based on the average information restricted maximum likelihood method and 1,610 genotyped individuals and 5,499 hematological parameter records from 4,543 cows. Furthermore, we assessed the genetic relationship between these hematological parameters and other economically important traits in dairy cattle breeding programs. We also carried out genome-wide association studies and candidate gene analyses. Blood samples from 21 primiparous cows were used to identify candidate genes further through RNA sequencing (RNA-seq) analyses. Hematological parameters generally exhibited low-to-moderate heritabilities ranging from 0.01 to 0.29, with genetic correlations between them ranging from -0.88 ± 0.09 (between mononuclear cell ratio and lymphocyte cell ratio) to 0.99 ± 0.01 (between white blood cell count and granulocyte cell count). Furthermore, low-to-moderate approximate genetic correlations between hematological parameters with one longevity, 4 fertility, and 5 health traits were observed. One hundred ninety-nine significant SNP located primarily on the Bos taurus autosomes (BTA) BTA4, BTA6, and BTA8 were associated with 16 hematological parameters. Based on the RNA-seq analyses, 6,687 genes were significantly downregulated and 4,119 genes were upregulated when comparing 2 groups of cows with high and low phenotypic values. By integrating genome-wide association studies (GWAS), RNA-seq, and previously published results, the main candidate genes associated with hematological parameters in Holstein cattle were ACRBP, ADAMTS3, CANT1, CCM2L, CNN3, CPLANE1, GPAT3, GRIP2, PLAGL2, RTL6, SOX4, WDFY3, and ZNF614. Hematological parameters are heritable and moderately to highly genetically correlated among themselves. The large number of candidate genes identified based on GWAS and RNA-seq indicate the polygenic nature and complex genetic determinism of hematological parameters in Holstein cattle.

Analysis of Risk Factors for Death in the Coronavirus Disease 2019 (COVID-19) Population: Data Analysis from a Large General Hospital in Anhui, China

During the coronavirus disease 2019 (COVID-19) pandemic, clinical prevention, early diagnosis, and hematological monitoring were challenging areas. This study aims to compare risk factors and hematological and biochemical data in non-survivor group patients with COVID-19 versus survivor group patients. A total of 204 patients with COVID-19 were selected as research subjects from December 2022 to January 2023. We analyzed the age, sex, time from onset to admission, and laboratory test indicators upon admission. The differences between surviving and deceased patients and mortality-related risk factors were examined. Among the 204 patients, 168 survived, whereas 36 died during hospitalization. Significant differences were observed between the two groups with COVID-19 across various factors, including age (p < 0.0001), WBC count (p < 0.0001), RBC count (p < 0.05), neutrophils (p < 0.0001), lymphocytes (p < 0.05), mean corpuscular hemoglobin concentration (MCHC) (p < 0.0001), RBC distribution width-standard deviation (RDW-SD) (p < 0.0001), RBC distribution width coefficient of variation (RDW-CV) (p < 0.0001), aspartate aminotransferase (AST) (p < 0.05), albumin (ALB) (p < 0.0001), creatinine (CR) (p < 0.0001), uric acid (UA) (p < 0.0001), blood urea nitrogen (BUN) (p < 0.0001), plasma thrombin time (TT) (p < 0.05), prothrombin time (PT) (p < 0.0001), and D-dimer (p < 0.0001). Multivariate logistic analysis revealed that older age, CR, UA, and ALB were independent factors associated with death (p < 0.05). Elderly patients with underlying diseases, abnormal routine blood test indices, and abnormal renal function and coagulation indices are at an increased worse prognosis and should be identified early. Age, UA, CR, and ALB can be used as predictors to assess the worse prognosis in the hospital.

Blood Count and Renal Functionality Assessments in the Emergency Section Disclose Morbidity and Mortality in Omicron COVID-19 Patients: A Retrospective Study

Background: SARS-CoV-2 is the coronavirus responsible for the COVID-19 pandemic. Even though we are no longer in a pandemic situation, people are still getting infected, some of them need hospitalization and a few of them die. Methods: We conducted a retrospective study including 445 patients who accessed the Emergency Section of Policlinico Umberto I, Rome, Italy, where they had routine blood exams. In this study, we focused on the complete blood count, serum creatinine and azotemia. The data were analyzed using ANOVA, Spearman correlation and ROC analyses. They were divided into four groups based on their clinical outcomes: (1) the emergency group (patients who had mild forms and were quickly discharged); (2) the hospital ward group (patients who were admitted to the emergency section and were then hospitalized in a COVID-19 ward); (3) the intensive care unit (ICU) group (patients who required intensive assistance after the admission in the emergency section); (4) the deceased group (patients who had a fatal outcome after admission to the emergency section). Results: We found significant changes for creatinine, azotemia, hematocrit, mean corpuscular hemoglobin concentration, basophils, monocytes, red blood cell distribution width, hemoglobin, hematocrit and red blood cell numbers using ANOVA according to their clinical outcomes, particularly for the deceased group. Also, we found linear correlations of clinical outcomes with eosinophils, hemoglobin, hematocrit, mean corpuscular hemoglobin concentration, lymphocyte, neutrophil, platelet and red blood cell number and red blood cell distribution width. Conclusions: This study discloses an early association between "classical" routine blood biomarkers and the severity of clinical outcomes in Omicron patients.

Hematological parameters and their predictive value for assessing disease severity in laboratory-confirmed COVID-19 patients: a retrospective study

BACKGROUND

The coronavirus disease 19 (COVID-19) infection has spread globally and caused a substantial amount of mortality and morbidity. Early detection of severe infections will improve care and reduce deaths. The use of hematological parameters in predicting COVID-19 disease severity, patient outcomes, and early risk stratification is limited. Therefore, the study was aimed at determining hematological parameters and their predictive value for assessing disease severity in laboratory-confirmed COVID-19 patients in Northwest Ethiopia.

METHODS

A retrospective cross-sectional study was conducted at the University of Gondar comprehensive specialized hospital and Tibebe Ghion comprehensive specialized referral hospital on 253 patients diagnosed with COVID-19 and admitted between March 2021 and February 2022. Data were extracted, and entered into Epi-data 4.2.0.0, and analyzed using SPSS version 25 software. Hematological parameters were provided as the median and interquartile range (IQR). Categorical variables were represented by their frequency, and the χ2 test was applied to compare observed results with expected results. The receiver-operating curve (ROC) was used to establish the predictive value of hematological parameters for COVID-19 severity. A p-value < 0.05 was considered statistically significant.

RESULTS

On a total of 253 patients, there were 43.87% severe cases, with a mortality rate of 26.9%. The ROC analysis showed the optimal cutoff values for hematological parameters were ANC (3370), lymphocyte (680), NLR (9.34), PLR (290.77), platelets (332,000), and WBCs (4390.65). The area under the curve (AUC) values for NLR (0.679) and ANC (0.631) were high, with the highest sensitivity and specificity, and could potentially be used to predict COVID-19 severity.

CONCLUSION

This study proved that high NLR and high ANC have prognostic value for assessing disease severity in COVID-19. Thus, assessing and considering these hematological parameters when triaging COVID-19 patients may prevent complications and improve the patient's outcome.

The association between mean platelet volume and poor outcome in patients with COVID-19: Systematic review, meta-analysis, and meta-regression

INTRODUCTION

This study aims to assess the association between mean platelet volume (MPV) and poor outcome in patients with COVID-19.

METHODS

We performed a comprehensive literature search using the PubMed, Embase and Scopus databases with keywords "2019-nCoV" OR "SARS-CoV-2" OR "COVID-19" AND "mean platelet volume" OR "MPV" on 8 July 2021. The primary outcome was composite poor outcome, defined as severe COVID-19 or mortality. The pooled effect estimate was reported as mean differences in terms of MPV between the group with and without outcome.

RESULTS

There were 17 studies which consist of 4549 patients with COVID-19 were included in this study. The incidence of poor outcome was 25% (20%-30%). Mean MPV was found to be higher in the poor outcome group in compare to no poor outcome group (10.3 ± 1.9 fL vs 9.9 ± 1.7 fL). The mean MPV difference between both group was 0.47 fL [95% CI 0.27, 0.67], p < 0.001; I2: 62.91%, p < 0.001). In the sub-group analysis, patients with severe COVID-19 had higher MPV (mean difference 0.54 fL [95% CI 0.28, 0.80], p < 0.001; I2: 54.84%, p = 0.014). Furthermore, MPV was also higher in the mortality group (mean difference 0.54 fL [95% CI 0.29, 0.80], p = 0.020; I2: 71.11%, p = 0.004). Meta-regression analysis showed that the association between MPV and poor outcome was not affected by age (p = 0.789), gender (p = 0.167), platelets (p = 0.056), white blood cells (p = 0.639), and lymphocytes (p = 0.733).

CONCLUSION

This meta-analysis indicated that increased MPV was associated with severity and mortality in patients with COVID-19. Further research is needed to determine the optimum cut-off point.

Blood Biomarkers from the Emergency Department Disclose Severe Omicron COVID-19-Associated Outcomes

Background: Since its outbreak, Coronavirus disease 2019 (COVID-19), a life-threatening respiratory illness, has rapidly become a public health emergency with a devastating social impact. Lately, the Omicron strain is considered the main variant of concern. Routine blood biomarkers are, indeed, essential for stratifying patients at risk of severe outcomes, and a huge amount of data is available in the literature, mainly for the previous variants. However, only a few studies are available on early routine biochemical blood biomarkers for Omicron-afflicted patients. Thus, the aim and novelty of this study were to identify routine blood biomarkers detected at the emergency room for the early prediction of severe morbidity and/or mortality. Methods: 449 COVID-19 patients from Sapienza University Hospital of Rome were divided into four groups: (1) the emergency group (patients with mild forms who were quickly discharged); (2) the hospital ward group (patients that after the admission in the emergency department were hospitalized in a COVID-19 ward); (3) the intensive care unit (ICU) group (patients that after the admission in the emergency department required intensive assistance); (4) the deceased group (patients that after the admission in the emergency department had a fatal outcome). Results: ANOVA and ROC data showed that high-sensitivity troponin-T (TnT), fibrinogen, glycemia, C-reactive protein, lactate dehydrogenase, albumin, D-dimer myoglobin, and ferritin for both men and women may predict lethal outcomes already at the level of the emergency department. Conclusions: Compared to previous Delta COVID-19 parallel emergency patterns of prediction, Omicron-induced changes in TnT may be considered other early predictors of severe outcomes.

Associations of the neutrophil/lymphocyte ratio, monocyte/ lymphocyte ratio, and platelet/lymphocyte ratio with COVID-19 disease severity in patients with neurological symptoms: A cross-sectional monocentric study

Objectives

Data are limited regarding the relationship of neutrophil/lymphocyte ratio (NLR), monocyte/lymphocyte ratio (MLR), and platelet/ lymphocyte ratio (PLR) with neurological symptoms (NS) in COVID-19 patients. This study is the first to assess the utility of the NLR, MLR, and PLR for predicting COVID-19 severity in infected patients with NS.

Materials and Methods

Consecutive 192 PCR-positive COVID-19 patients with NS were included in this cross-sectional and prospective study. The patients were classified into the non-severe and severe groups. We analyzed routinely complete blood count in these groups in terms of COVID-19 disease severity.

Results

Advanced age, a higher body mass index, and comorbidities were significantly more common in the severe group (P < 0.001). Among the NS, anosmia (P = 0.001) and memory loss (P = 0.041) were significantly more common in the non-severe group. In the severe group, the lymphocytes and monocyte counts and the hemoglobin level were significantly lower, while the neutrophil count, NLR, and PLR were significantly higher (all P < 0.001). In the multivariate model, advanced age and a higher neutrophil count were independently associated with severe disease (both P < 0.001) but the NLR and PLR were not (both P > 0.05).

Conclusion

We found positive associations of COVID-19 severity with the NLR and PLR in infected patients with NS. Further research is required to shed more light on the role of neurological involvement in disease prognosis and outcomes.

Clinical utility of haematological inflammatory biomarkers in predicting 30-day mortality in hospitalised adult patients with COVID-19

Coronavirus disease 2019 (COVID-19) is a multisystem disease affecting respiratory, cardiovascular, gastrointestinal, neurological, immunological and haematological systems. The most important indices that have been studied are platelet (PLT) indices in addition to the PLT count and red blood cell distribution width (RDW). This retrospective study included 95 patients with COVID-19 and was conducted at the Hospital Isolation, Scientific and Medical Research Centre and Clinical Pathology Department at Zagazig University Hospitals, Egypt over 6 months from March to August 2021. All patients on admission had a full blood count, which included white blood cell (WBC) count, haemoglobin, RDW, PLT count and its indices in addition to PLT-to-WBC ratio (PWR) and PLT-to-lymphocyte ratio (PLR), which were calculated for all the study patients. There were significant linear correlations for higher levels of the PLR, PWR and RDW and mortality rate (p = 0.03, p < 0.001 and p < 0.001 respectively). Moreover, on multivariable analysis the RDW, PLT count and PWR levels were independent prognostic predictors for mortality with a hazard ratio [HR] of 1.25 (95% confidence interval [CI] 1.09-1.44, p = 0.002), 1.00 (95% CI 0.99-1.00, p = 0.03) and 2.3 (95% CI 1.21-4.48, p = 0.01) respectively. The RDW and PLT indices are accessible predictors that can be valuable prognostic factors for survival assessment and risk stratification of COVID-19.

Hematologic analysis of hospitalized patients and outpatients infected with SARS-CoV-2 and possible use as a prognostic biomarker

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is a global health problem; this has caused thousands of deaths around the world. This infection induces hematologic alterations, and it is necessary to recognize predictive biomarkers to address the need for hospitalization or the severity of the disease. This study aimed to analyze different parameters in outpatients and hospitalized patients infected with SARS-CoV-2 and determine whether hematic biometry can be used for prognosis rapidly. We analyzed 689 patients, of whom 355 were outpatients (162 women and 193 men) and 334 required hospitalization (197 men and 137 women). The average age of the hospitalized patients was 46 years (men, 49 years; women, 52 years), whereas the average age of the outpatients was 49 years (men, 51 years; women, 44 years). Hematologic parameters were analyzed and compared between the outpatients and hospitalized patients. The patients were divided into groups by age and sex. We found that in the hospitalized patients, the erythrocyte, hematocrit, and hemoglobin levels decreased, whereas the outpatients did not experience changes in the erythroid series. In leukocytes, these increased significantly, as they did in neutrophils; however, lymphocytopenia was observed. In the outpatients, we observed normal levels of neutrophils and lymphopenia. We can conclude that hematic biometry can be used as a biomarker, and the relation between neutrophils and lymphocytes is indicated for understanding the development and prognosis of the disease.

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.

Assessment of the Level of Protein C in Hospitalized Iraqi Patients with COVID-19 and its Correlation with Hematological and Inflammatory Markers

BACKGROUND: COVID-19 coagulopathy manifests by elevation of certain marker of active coagulation as fibrinogen and this increment associated with increased markers of inflammations. AIM: To measure protein C (PC) level in hospitalized patients with COVID-19 and to find a possible correlation with hematological and inflammatory markers. PATIENTS AND METHODS: Seventy-five hospitalized Iraqi adult patients with COVID-19 were included in a descriptive cross-sectional research. PC, D-dimer, and erythrocyte sedimentation rate (ESR) blood samples were collected, and further information was received from patient’s records. Statistical analysis was conducted using SPSS version 23 and Microsoft Office Excel 2019. RESULTS: Mean age of 75 patients included in the study was 60.13 ± 14.65 years. Sixty-two (62.7%) of patients exhibited neutrophilia, whereas 41 had lymphopenia (54.7%). High ratio of neutrophil/lymphocyte (N/L) was seen in 66 (88.0%), eosinopenia was seen in 46 (61.3%), high lactate dehydrogenase level was seen 68 (90.7%), serum ferritin was high in 66 (88.0%), and high level of C-reactive protein was seen in 68 (90.7%), increased ESR was seen in 69 (92.0%) and high level of D-dimer was seen in 56 (74.7%), while low level of PC was seen in 12 (16.0%) patients. PC had significant negative correlation with prothrombin and partial thromboplastin time but no significant correlation with hematological and inflammatory parameters. CONCLUSION: COVID-19 coagulopathy is common in majority of patients which include significant changes in WBCs counts, inflammatory markers, PC, and D-dimer levels. Such changes may have a great impact on morbidity and mortality and thus need to be monitored throughout treatment and convalescence.

Mean Platelet Volume as a Predictor of COVID-19 Severity: A Prospective Cohort Study in the Highlands of Peru

Introduction: Although 80% of symptomatic individuals with COVID-19 develop mild forms, it is the severe (15%) and critical (5%) forms that have the greatest impact in the hospital setting. Recognizing markers that can predict severe forms is essential, especially in high-altitude populations. Methods: We conducted a prospective cohort study at 3200 masl (meters above sea level) in a city in Peru to determine if MPV (mean platelet volume) level is a predictor of COVID-19 severity. Patients with mild/moderate disease were enrolled and followed for 21 days or until the development of severe disease (primary outcome). A bivariate analysis was used to identify variables associated with severe disease. A ROC analysis determined the best MPV (mean platelet count) cut-off to predict COVID-19 severity, and then, a multiple regression analysis was performed. Results: 64 patients were enrolled. The median age was 48.5 years (IQT 39–64.5) and the proportion of women was 51.6%, the most frequent symptoms were chest pain (73%), fever (71%), and dyspnea (67%). The median time to develop a severe form from the onset of symptoms was 11 days (IQT 10.5–13). The most common radiographic phase on CT scan (computed tomography) was progressive (60.38%). We observed that an MPV of more than 10.15 fL in the first week of disease predicted severity regardless of age and sex at high altitudes. Conclusions: MPV in the first week of the disease may predict severity in patients diagnosed with COVID-19 at high altitudes; however, we need prospective studies with a larger population and at a different altitude, levels to confirm these findings.

Sex-Dependent Performance of the Neutrophil-to-Lymphocyte, Monocyte-to-Lymphocyte, Platelet-to-Lymphocyte and Mean Platelet Volume-to-Platelet Ratios in Discriminating COVID-19 Severity

Background

The neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), lymphocyte-to-monocyte ratio (LMR), and mean platelet volume-to-platelet ratio (MPR) are combined hematology tests that predict COVID-19 severity, although with different cut-off values. Because sex significantly impacts immune responses and the course of COVID-19, the ratios could be biased by sex.

Purpose

This study aims to evaluate sex-dependent differences in the contribution of NLR, PLR, MLR, and MPR to COVID-19 severity and mortality upon hospital admission using a sample of pneumonia patients with SARS-CoV-2 infection.

Methods

This single-center observational cross-sectional study included 3,280 confirmed COVID-19 cases (CDC 2019-Novel Coronavirus real-time RT-PCR Diagnostic) from Quito (Ecuador). The receiver operating characteristic (ROC) curve analysis was conducted to identify optimal cut-offs of the above parameters when discriminating severe COVID-19 pneumonia and mortality risks after segregation by sex. Severe COVID-19 pneumonia was defined as having PaO₂ < 60 mmHg and SpO₂ < 94%, whereas non-severe COVID-19 pneumonia was defined as having PaO₂ ≥ 60 mmHg and SpO₂ ≥ 94%.

Results

The mortality rate of COVID-19 among men was double that in women. Severe COVID-19 pneumonia and non-surviving patients had a higher level of NLR, MLR, PLR, and MPR. The medians of NLR, MLR, and MPR in men were significantly higher, but PLR was not different between men and women. In men, these ratios had lower cut-offs than in women (NLR: 2.42 vs. 3.31, MLR: 0.24 vs. 0.35, and PLR: 83.9 vs. 151.9). The sensitivity of NLR, MLR, and PLR to predict pneumonia severity was better in men (69–77%), whereas their specificity was enhanced in women compared to men (70–76% vs. 23–48%).

Conclusion

These ratios may represent widely available biomarkers in COVID-19 since they were significant predictors for disease severity and mortality although with different performances in men and women.

Soluble Angiotensin-Converting Enzyme 2 as a Prognostic Biomarker for Disease Progression in Patients Infected with SARS-CoV-2

Predicting disease severity in patients infected with SARS-CoV-2 is difficult. Soluble angiotensin-converting enzyme 2 (sACE2) arises from the shedding of membrane ACE2 (mACE2), which is a receptor for SARS-CoV-2 spike protein. We evaluated the predictive value of sACE2 compared with known biomarkers of inflammation and tissue damage (CRP, GDF-15, IL-6, and sFlt-1) in 850 patients with and without SARS-CoV-2 with different clinical outcomes. For univariate analyses, median differences between biomarker levels were calculated for the following patient groups (classified by clinical outcome): RT-PCR-confirmed SARS-CoV-2 positive (Groups 1−4); RT-PCR-confirmed SARS-CoV-2 negative following previous SARS-CoV-2 infection (Groups 5 and 6); and ‘SARS-CoV-2 unexposed’ patients (Group 7). Median levels of CRP, GDF-15, IL-6, and sFlt-1 were significantly higher in hospitalized patients with SARS-CoV-2 compared with discharged patients (all p < 0.001), whereas levels of sACE2 were significantly lower (p < 0.001). ROC curve analysis of sACE2 provided cut-offs for predicting hospital admission (≤0.05 ng/mL (positive predictive value: 89.1%) and ≥0.42 ng/mL (negative predictive value: 84.0%)). These findings support further investigation of sACE2, as a single biomarker or as part of a panel, to predict hospitalization risk and disease severity in patients with SARS-CoV-2 infection.

Role of red blood cell distribution width, as a prognostic indicator in COVID-19: A systematic review and meta-analysis

The red blood cell distribution width (RDW), an indicator of anisocytosis has emerged as a potential tool for risk stratification of critically ill patients with sepsis. Prognostic predictors are of paramount interest for prompt intervention and optimal utilization of the healthcare system in this ongoing context of the Coronavirus Disease 2019 (COVID-19) pandemic. The current systematic review and meta-analysis aims to explore the utility of RDW in the prognosis of COVID-19 patients. A comprehensive screening of electronic databases was performed up to 30th April 2021 after enrolling in PROSPERO (CRD42020206685). Observational studies or interventional studies, evaluating the impact of RDW in COVID-19 outcomes (mortality and severity) are included in this meta-analysis.Our search retrieved 25 studies, with a total of 18,392 and 3,446 COVID-19 patients for mortality and disease severity outcomes. Deceased and critically ill patients had higher RDW levels on admission in comparison to survivors and non-severe patients (SMD = 0.46; 95%CI 0.31-0.71; I2  = 88% and SMD = 0.46; 95%CI 0.26-0.67; I2  = 60%, respectively). In a sub-group analysis of 2,980 patients, RDW > 14.5 has been associated with increased risk of mortality (OR = 2.73; 95%CI 1.96-3.82; I2  = 56%). However, the evidences is of low quality. A higher level of RDW on admission in COVID-19 patients is associated with increased morbidity and mortality. However, further studies regarding the cut-off value of RDW are the need of the hour.

Does Neutrophil-to-lymphocyte Ratio at Admission Predict Severity and Mortality in COVID-19 Patients? A Systematic Review and Meta-analysis

Background

Coronavirus disease-2019 (COVID-2019) pandemic continues to be a significant public health problem. Severe COVID-19 cases have a poor prognosis and extremely high mortality. Prognostic factor evidence can help healthcare providers understand the likely prognosis and identify subgroups likely to develop severe disease with increased mortality risk so that timely treatments can be initiated. This meta-analysis has been performed to evaluate the neutrophil-to-lymphocyte ratio (NLR) at admission as a prognostic factor to predict severe coronavirus disease and mortality.

Materials and methods

A literature search was conducted through April 30, 2021, to retrieve all published studies, including gray literature and preprints, investigating the association between NLR and severity or mortality in COVID-19 patients. Screening of studies and data extraction have been done by two authors independently. The methodological quality of the included studies was assessed by the Quality in Prognosis Studies (QUIPS) tool.

Results

Twenty-four studies involving 4,080 patients reported the prognostic value of NLR for severe COVID-19. The pooled sensitivity (SEN), specificity (SPE), and area under the curve were 0.75 (95% CI 0.69–0.80), 0.74 (95% CI 0.70–0.78), and 0.81 (95% CI 0.77–0.84). Fifteen studies involving 4,071 patients reported the prognostic value of NLR for mortality in COVID-19. The pooled sensitivity (SEN), specificity (SPE), and area under curve were 0.80 (95% CI 0.72–0.86), 0.78 (95% CI 0.69–0.85), and 0.86 (95% CI 0.83–0.89).

Conclusion

The prognostic value of NLR at admission for severity and mortality in patients with COVID-19 is good. Evaluating the NLR at admission can assist treating clinicians to identify early the cases likely to worsen. This would help to conduct early triage, identify potentially high-risk cases, and start optimal monitoring and management, thus reducing the overall mortality of COVID-19.

Trial registry

This meta-analysis was prospectively registered on PROSPERO database (Registration Number: CRD42021247801).

How to cite this article

Sarkar PG, Pant P, Kumar J, Kumar A. Does Neutrophil-to-lymphocyte Ratio at Admission Predict Severity and Mortality in COVID-19 Patients? A Systematic Review and Meta-analysis. Indian J Crit Care Med 2022;26(3):361–375.

Early Routine Biomarkers of SARS-CoV-2 Morbidity and Mortality: Outcomes from an Emergency Section

Background. COVID-19 is a severe acute respiratory disease caused by SARS-CoV-2, a virus belonging to the Coronaviridae family. This disease has spread rapidly around the world and soon became an international public health emergency leading to an unpredicted pressure on the hospital emergency units. Early routine blood biomarkers could be key predicting factors of COVID-19 morbidity and mortality as suggested for C-reactive protein (CRP), IL-6, prothrombin and D-dimer. This study aims to identify other early routine blood biomarkers for COVID-19 severity prediction disclosed directly into the emergency section. Methods. Our research was conducted on 156 COVID-19 patients hospitalized at the Sapienza University Hospital “Policlinico Umberto I” of Rome, Italy, between March 2020 and April 2020 during the paroxysm’s initial phase of the pandemic. In this retrospective study, patients were divided into three groups according to their outcome: (1) emergency group (patients who entered the emergency room and were discharged shortly after because they did not show severe symptoms); (2) intensive care unit (ICU) group (patients who attended the ICU after admission to the emergency unit); (3) the deceased group (patients with a fatal outcome who attended the emergency and, afterward, the ICU units). Routine laboratory tests from medical records were collected when patients were admitted to the emergency unit. We focused on Aspartate transaminase (AST), Alanine transaminase (ALT), Lactate dehydrogenase (LDH), Creatine kinase (CK), Myoglobin (MGB), Ferritin, CRP, and D-dimer. Results. As expected, ANOVA data show an age morbidity increase in both ICU and deceased groups compared with the emergency group. A main effect of morbidity was revealed by ANOVA for all the analyzed parameters with an elevation between the emergency group and the deceased group. Furthermore, a significant increase in LDH, Ferritin, CRP, and D-dimer was also observed between the ICU group and the emergency group and between the deceased group and ICU group. Receiver operating characteristic (ROC) analyses confirmed and extended these findings. Conclusions. This study suggests that the contemporaneous presence of high levels of LDH, Ferritin, and as expected, CRP, and D-dimer could be considered as potential predictors of COVID-19 severity and death.

Gender Differences Associated with Hyper-Inflammatory Conditions in COVID-19 Patients

COVID-19 has been associated with various hyper-inflammatory conditions (HICs) such as macrophage activation, hematological dysfunction, cytokinaemia, coagulopathy, and liver inflammation. However, it is not clear if the differences in the disease severity and mortality shown by male and female COVID-19 patients are associated with these HICs. Here, we review the literature and present supporting laboratory data on the gender differences associated with various HICs in COVID-19 patients. We measured plasma/serum levels of various HIC specific clinical markers in severe male (N=132) and severe female (N=78) COVID-19 patients. The result revealed that all clinical markers were highly elevated above the normal in both male and female COVID-19 patients. However, a comparison of AUROC (area under the receiving operative characteristics) of specific clinical markers revealed that elevation in serum ferritin (marker for macrophage activation), and neutrophil to lymphocyte (N/L) ration (marker for hematological dysfunction) was much higher in male compared to the female COVD-19 patients. Further, univariate regression analyses revealed that male COVID-19 patients had two times higher risks than female patients for developing macrophage activation (OR 2.36, P=0.004)), hematological dysfunctions (OR 2.23, P=0.01), coagulopathy (OR 2.10, P=0.01), and cytokinaemia (OR 2.31, P=0.01). Similar results were obtained in bivariate analyses. Survival curve analysis showed that male COVID-19 patients had relatively short survival duration than female COVID-19 patients (hazard ratio 2.0, 95% CI 1.3-3.7, P=0.01). The above findings suggest that the high mortality rate in male COVID-19 patients compared to the female could be due to higher prevalence and severity of various HICs.

Role of platelet-to-lymphocyte count ratio (PLR), as a prognostic indicator in COVID-19: A systematic review and meta-analysis

Prognostic predictors are of paramount interest for prompt intervention and optimal utilization of the healthcare system in the ongoing context of the COVID-19 pandemic. The platelet-to-lymphocyte count ratio (PLR), has emerged as a potential tool for risk stratification of critically ill patients with sepsis. The current systematic review explores the utility of PLR as a prognostic predictor of COVID-19 patients. We screened the electronic databases until May 15, 2021 after enrolling in PROSPERO (CRD42021220269). Studies evaluating the association between PLR on admission and outcomes in terms of mortality and severity among COVID-19 patients were included. We retrieved 32 studies, with a total of 2768 and 3262 COVID-19 patients for mortality and disease severity outcomes. Deceased and critically ill patients had higher PLR levels on admission in comparison to survivors and non-severe patients (mean differences [MD] = 66.10; 95% confidence interval [CI]: 47.75-84.44; p < 0.00001 and MD = 86.74; 95% CI: 67.7-105.7; p < 0.00001, respectively). A higher level of PLR on admission in COVID-19 patients is associated with increased morbidity and mortality. However, the evidence is of low quality and further studies regarding the cut-off value of PLR are the need of the hour.

Value of the Neutrophil-Lymphocyte Ratio in Predicting COVID-19 Severity: A Meta-analysis

Background

Coronavirus disease 2019 (COVID-19) is highly contagious and continues to spread rapidly. However, there are no simple and timely laboratory techniques to determine the severity of COVID-19. In this meta-analysis, we assessed the potential of the neutrophil-lymphocyte ratio (NLR) as an indicator of severe versus nonsevere COVID-19 cases.

Methods

A search for studies on the NLR in severe and nonsevere COVID-19 cases published from January 1, 2020, to July 1, 2021, was conducted on the PubMed, EMBASE, and Cochrane Library databases. The pooled sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, diagnostic odds ratio (DOR), and area under the curve (AUC) analyses were done on Stata 14.0 and Meta-disc 1.4 to assess the performance of the NLR.

Results

Thirty studies, including 5570 patients, were analyzed. Of these, 1603 and 3967 patients had severe and nonsevere COVID-19, respectively. The overall sensitivity and specificity were 0.82 (95% confidence interval (CI), 0.77-0.87) and 0.77 (95% CI, 0.70-0.83), respectively; positive and negative correlation ratios were 3.6 (95% CI, 2.7-4.7) and 0.23 (95% CI, 0.17-0.30), respectively; DOR was 16 (95% CI, 10-24), and the AUC was 0.87 (95% CI, 0.84-0.90).

Conclusion

The NLR could accurately determine the severity of COVID-19 and can be used to identify patients with severe disease to guide clinical decision-making.

Red Blood Cell Distribution Width, Disease Severity, and Mortality in Hospitalized Patients with SARS-CoV-2 Infection: A Systematic Review and Meta-Analysis

The identification of biomarkers predicting disease severity and outcomes is the focus of intense research in patients with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2 infection). Ideally, such biomarkers should be easily derivable from routine tests. We conducted a systematic review and meta-analysis of the predictive role of the red blood cell distribution width (RDW), a routine hematological test, in patients with SARS-CoV-2 infection. We searched the electronic databases PubMed, Web of Science and Scopus, from January 2020 to November 2020, for studies reporting data on the RDW and coronavirus disease 2019 (COVID-19) severity, defined as severe illness or admission to the intensive care unit (ICU), and mortality. Eleven studies in 4901 COVID-19 patients were selected for the meta-analysis. Pooled results showed that the RDW values were significantly higher in patients with severe disease and non-survivors (standard mean difference, SMD = 0.56, 95% CI 0.31 to 0.81, p < 0.001). Heterogeneity between studies was extreme (I² = 80.6%; p < 0.001). In sensitivity analysis, the effect size was not modified when each study was in turn removed (effect size range, between 0.47 and 0.63). The Begg’s (p = 0.53) and Egger’s tests (p = 0.52) showed no evidence of publication bias. No significant correlations were observed between SMD and age, gender, whole blood count, end point, study geographic area, or design. Our meta-analysis showed that higher RDW values are significantly associated with COVID-19 severity and mortality. This routine parameter might assist with early risk stratification in patients with SARS-CoV-2 infection.

Significance of MPV, RDW and PDW with the Severity and Mortality of COVID-19 and Effects of Acetylsalicylic Acid Use

We aimed to investigate association between mean platelet volume (MVP), platelet distribution width (PDW) and red cell distribution width (RDW) and mortality in patients with COVID-19 and find out in which patients the use of acetylsalicylic acid (ASA) affects the prognosis due to the effect of MPV on thromboxan A2. A total of 5142 patients were divided into those followed in the intensive care unit (ICU) and those followed in the ward. Patient medical records were examined retrospectively. ROC analysis showed that the area under curve (AUC) values were 0.714, 0.750, 0.843 for MPV, RDW and D-Dimer, the cutoff value was 10.45fl, 43.65fl, 500.2 ng/mL respectively. (all P < .001). Survival analysis showed that patients with MPV >10.45 f/l and D-Dimer >500.2 ng/mL, treatment with ASA had lower in-hospital and 180-day mortality than patients without ASA in ICU patients (HR = 0.773; 95% CI = 0.595-0.992; P = .048, HR = 0.763; 95% CI = 0.590-0.987; P = .036). Administration of low-dose ASA in addition to anti-coagulant according to MPV and D-dimer levels reduces mortality.

Associations between hematological parameters and disease severity in patients with SARS-CoV-2 infection

Background

The emergence and rapid spread of the deadly novel coronavirus disease caused by severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) is a swiftly evolving public health crisis worldwide. SARS‐CoV‐2 infection is characterized by the development and progression of inflammatory responses. Hematological parameters, such as white blood cells (WBCs) and their subpopulations, red cell distribution width, platelet count, mean platelet volume, plateletcrit, and derived markers such as neutrophil‐to‐lymphocyte ratio (NLR), platelet‐to‐lymphocyte ratio (PLR), and lymphocyte‐to‐monocyte ratio, are established biomarkers of inflammatory responses. We aimed to investigate associations between hematological parameters and disease severity in patients with SARS‐CoV‐2 infection.

Methods

We retrospectively analyzed data from 68 patients with confirmed SARS‐CoV‐2 infection. Twenty‐two patients had mild illness, and 46 had moderate or severe illness at the time of admission. Univariate and multivariate regression analyses were used to identify correlates of disease severity. The areas under receiver operating characteristic curves were calculated to estimate and compare the predictive values of different diagnostic markers.

Results

Mean lymphocyte and monocyte counts were lower while WBC counts, neutrophil counts, NLR, and PLR were higher in patients with severe disease compared with those with mild disease (all P < .01). Univariate analysis revealed that older age, high WBC counts, high neutrophil counts, high NLR, high PLR, low monocyte counts, and low lymphocyte counts were independent correlates of severe illness. Multivariate analysis identified high NLR as the only independent correlate of severe illness. Receiver operating characteristic curve analysis showed that NLR had the highest area under curve of all hematological parameters.

Conclusion

Among hematological parameters, the NLR showed superior prediction of disease severity in patients with SARS‐CoV‐2 infection. Thus, the NLR could be a valuable parameter to complement conventional measures for identification of patients at high risk for severe disease.