Neutrophil/Lymphocyte Ratio (NLR) and Lymphocyte/Monocyte Ratio (LMR) - Risk of Death Inflammatory Biomarkers in Patients with COVID-19.

Aim: The aim of our retrospective study was search for new prognostic parameters, which can help quickly and cheaply identify patients with risk for severe course of SARS-CoV-2 infection. Materials and Methods: The following peripheral blood combination biomarkers were calculated: NLR (neutrophil/lymphocytes ratio), LMR (lymphocyte/monocyte ratio), PLR (platelet/lymphocyte ratio), dNLR (neutrophils/(white blood cells - neutrophils)), NLPR (neutrophil/(lymphocyte × platelet ratio)) in 374 patients who were admitted to the Temporary Hospital no 2 of Clinical Hospital in Bialystok (Poland) with COVID-19. The patients were divided into four groups depending on the severity of the course of COVID-19 using MEWS classification. Results: The NLR and dNLR were significantly increased with the severity of COVID-19, according to MEWS score. The AUC for the assessed parameters was higher in predicting death in patients with COVID-19: NLR (0.656, p=0.0018, cut-off=6.22), dNLR (0.615, p=0.02, cut-off=3.52) and LMR (0.609, p=0.03, cut-off=2.06). Multivariate COX regression analysis showed that NLR median above 5.56 (OR: 1.050, P=0.002), LMR median below 2.23 (OR: 1.021, P=0.011), and age >75 years old (OR: 1.072, P=0.000) had a significant association with high risk of death during COVID-19. Conclusion: Our results indicate that NLR, dNLR, and LMR calculated on admission to the hospital can quickly and easy identify patients with risk of a more severe course of COVID-19. Increase NLR and decrease LMR have a significant predictive value in COVID-19 patient's mortality and might be a potential biomarker for predicting death in COVID-19 patients.

Dynamic NLR and PLR in Predicting COVID-19 Severity: A Retrospective Cohort Study.

INTRODUCTION: The hyperinflammation phase of severe SARS-CoV-2 is characterised by complete blood count alterations. In this context, the neutrophil-to-lymphocyte ratio (NLR) and the platelet-to-lymphocyte ratio (PLR) can be used as prognostic factors. We studied NLR and PLR trends at different timepoints and computed optimal cutoffs to predict four outcomes: use of continuous positive airways pressure (CPAP), intensive care unit (ICU) admission, invasive ventilation and death. METHODS: We retrospectively included all adult patients with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pneumonia admitted from 23 January 2020 to 18 May 2021. Analyses included non-parametric tests to study the ability of NLR and PLR to distinguish the patients' outcomes at each timepoint. Receiver operating characteristic (ROC) curves were built for NLR and PLR at each timepoint (minus discharge) to identify cutoffs to distinguish severe and non-severe disease. Their statistical significance was assessed with the chi-square test. Collection of data under the SMACORE database was approved with protocol number 20200046877. RESULTS: We included 2169 patients. NLR and PLR were higher in severe coronavirus disease 2019 (COVID-19). Both ratios were able to distinguish the outcomes at each timepoint. For NLR, the areas under the receiver operating characteristic curve (AUROC) ranged between 0.59 and 0.81, and for PLR between 0.53 and 0.67. From each ROC curve we computed an optimal cutoff value. CONCLUSION: NLR and PLR cutoffs are able to distinguish severity grades and mortality at different timepoints during the course of disease, and, as such, they allow a tailored approach. Future prospects include validating our cutoffs in a prospective cohort and comparing their performance against other COVID-19 scores.

Hematological Parameters and Procalcitonin as Discriminants between Bacterial Pneumonia-Induced Sepsis and Viral Sepsis Secondary to COVID-19: A Retrospective Single-Center Analysis.

Bacterial and viral sepsis induce alterations of all hematological parameters and procalcitonin is used as a biomarker of infection and disease severity. Our aim was to study the hematological patterns associated with pulmonary sepsis triggered by bacteria and Severe Acute Respiratory Syndrome-Coronavirus-type-2 (SARS-CoV-2) and to identify the discriminants between them. We performed a retrospective, observational study including 124 patients with bacterial sepsis and 138 patients with viral sepsis. Discriminative ability of hematological parameters and procalcitonin between sepsis types was tested using receiver operating characteristic (ROC) analysis. Sensitivity (Sn%), specificity (Sp%), positive and negative likelihood ratios were calculated for the identified cut-off values. Patients with bacterial sepsis were older than patients with viral sepsis (p < 0.001), with no differences regarding gender. Subsequently to ROC analysis, procalcitonin had excellent discriminative ability for bacterial sepsis diagnosis with an area under the curve (AUC) of 0.92 (cut-off value of >1.49 ng/mL; Sn = 76.6%, Sp = 94.2%), followed by RDW% with an AUC = 0.87 (cut-off value >14.8%; Sn = 80.7%, Sp = 85.5%). Leukocytes, monocytes and neutrophils had good discriminative ability with AUCs between 0.76-0.78 (p < 0.001), while other hematological parameters had fair or no discriminative ability. Lastly, procalcitonin value was strongly correlated with disease severity in both types of sepsis (p < 0.001). Procalcitonin and RDW% had the best discriminative ability between bacterial and viral sepsis, followed by leukocytes, monocytes and neutrophils. Procalcitonin is a marker of disease severity regardless of sepsis type.

Serial Changes in Blood-Cell-Count-Derived and CRP-Derived Inflammatory Indices of COVID-19 Patients.

The aim of the study was to investigate the serial changes in inflammatory indices derived from blood cell counts and C-reactive protein (CRP) levels in COVID-19 patients with good and poor outcomes. We retrospectively analyzed the serial changes in the inflammatory indices in 169 COVID-19 patients. Comparative analyses were performed on the first and last days of a hospital stay or death and serially from day 1 to day 30 from the symptom onset. On admission, non-survivors had higher CRP to lymphocytes ratio (CLR) and multi-inflammatory index (MII) values than survivors, while at the time of discharge/death, the largest differences were found for the neutrophil to lymphocyte ratio (NLR), systemic inflammation response index (SIRI), and MII. A significant decrease in NLR, CLR, and MII by the time of discharge was documented in the survivors, and a significant increase in NLR was documented in the non-survivors. The NLR was the only one that remained significant from days 7-30 of disease in intergroup comparisons. The correlation between the indices and the outcome was observed starting from days 13-15. The changes in the index values over time proved to be more helpful in predicting COVID-19 outcomes than those measured on admission. The values of the inflammatory indices could reliably predict the outcome no earlier than days 13-15 of the disease.

Clinical Significance and Diagnostic Utility of NLR, LMR, PLR and SII in the Course of COVID-19: A Literature Review.

Nowadays, society is increasingly struggling with infectious diseases that are characterized by severe course and even death. Recently, the whole world has faced the greatest epidemiological threat, which is COVID-19 caused by SARS CoV-2 virus. SARS CoV-2 infection is often accompanied by severe inflammation, which can lead to the development of different complications. Consequently, clinicians need easily interpreted and effective markers of inflammation that can predict the efficacy of the treatment and patient prognosis. Inflammation is associated with changes in many biochemical and hematological parameters, including leukocyte counts and their populations. In COVID-19, changes in leukocytes count populations such as neutrophils, lymphocytes or monocytes are observed. The numerous research confirm that indicators like neutrophil-to-lymphocyte ratio (NLR), lymphocyte-to-monocyte ratio (LMR), platelets-to-lymphocyte ratio (PLR) and systemic inflammatory index (SII) may prove effective in assessment patient prognosis and choosing optimal therapy. Therefore, in this review, we would like to summarize the latest knowledge about the diagnostic utility of systemic inflammatory ratios - NLR, LMR, PLR and SII in patients with COVID-19. We focused on the papers evaluating the diagnostic utility of inflammatory ratios using ROC curve published in the recent 3 years. Identification of biomarkers associated with inflammation would help the selection of patients with severe course of COVID-19 and high risk of death.

Comparison of inflammation markers in different severities of COVID-19 disease

Objectives: We retrospectively analyzed COVID-19 patients for clinical and hematologic features and tried to define the most appropriate markers to diagnose and predict the severity. Methods: This is a retrospective cross-sectional study. All 4443 patients included were diagnosed with reverse trancription-polymerase chain reaction between January 1 and December 30, 2020. We classified patients according to their mode of treatment: outpatient, inpatient in the ward, or inpatients in the intensive care unit (ICU). Results: The mean age of 2283 (51.4%) women and 2160 (48.6%) men included in the study was determined to be 39.77±17.30. Of the 4443 patients, 3985 (89.7%) were outpatients, 330 (7.4%) were inpatients, and 128 (2.9%) patients were treated in the ICU. The mean hospital stay was 8.36±4.55 days for the survivors in the ward group and 2.67±1.53 days for those who died (p=0.031). The mean hospitalization time of the survivors in the ICU group was 19.97±12.09 days, and the mean hospitalization time of the deceased was 13.10±9.99 days (p=0.001). Age, ferritin, D-dimer, glucose, ALT, AST, urea, creatinine, CRP, HgA1c, IMG, IMG%, and RDW-SD showed a gradual and significant increase in outpa-tient, ward, and ICU groups (p<0.001). Na, K, Neu, Neu%, MCV, RDW-CV, MPV, NLR, PLR, and NMR increased gradually from the outpatient group to the service and ICU groups, whereas Ca, RBC, Hgb, and Hct values decreased significantly (p<0.001). WBC, lymph%, and RDW were highest in the ICU group. Conclusion: Advanced age and being male are important risk factors for hospitalization. Indexes such as NLR, PLR, LCR, NMR, and LMR can be used to predict the severity of the disease. © 2022, Kare Publishing. All rights reserved.

Evaluation and comparison of utility of neutrophil-to-lymphocyte ratio (NLR) as a diagnostic marker in covid-19 infection

Introduction: The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which was first described during a pneumonia outbreak in Wuhan, has attracted tremendous attention in a short period of time as the death toll and the number of confirmed cases is growing unceasingly. Although molecular testing is the gold standard method of SARS-CoV-2 detection, the existence of the false-negative results presents a major limitation to this method. Material(s) and Method(s): Our present study aimed to determine the relationship between NLR and COVID-19 patients underwent treatment. The study was an analytical observational with a cross-sectional approach from May 2021 to January 2022 at the SMMH Medical College, Saharanpur, Uttar Pradesh. Result(s): COVID-19 infection is caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). Diabetes mellitus and heart disease comorbid have high morbidity and mortality. Increased Neutrophils to Lymphocyte Ratio (NLR) assist in early screening of disease severity, especially patients admitted in the Intensive Care Unit (ICU). There was a correlation between NLR in COVID-19 patients who were severely ill and admitted in the ICU with p=0.012. Conclusion(s): Increased NLR of COVID-19 patients occurs due to infiltration of the innate and adaptive immune system in infected tissue, resulting in decreased circulating lymphocytes. This subsequently increases NLR in COVID-19 patients. This study found a moderate positive correlation between NLR in COVID-19 patients who were severely ill. Copyright © 2022 Ubiquity Press. All rights reserved.

Hemograms and serial hemogram-derived ratios in survivors and non-survivors of COVID-19 in Campinas, Brazil.

Introduction: The hemogram and hemogram-derivative ratios (HDRs) are becoming markers of the severity and mortality of COVID-19. We evaluated the hemograms and serial weekly HDRs [neutrophil-lymphocyte ratio (NLR), monocyte-lymphocyte ratio (MLR), platelet-lymphocyte ratio (PLR), neutrophil-platelet ratio (NPR) and systemic immune-inflammatory index (SII)] in the survivors and non-survivors of COVID-19. Methods: We retrospectively reviewed the medical notes and serial hemograms of real-time reverse-transcription polymerase chain reaction (RT-PCR)-confirmed COVID-19 adults hospitalized from April 2020 to March 2021 from the time of diagnosis to the 3rd week of diagnosis. Results: Of the 320 adults, 257 (80.3%) were survivors and had a lower mean age than the non-survivors (57.73 vs. 64.65 years, p < 0.001). At diagnosis, the non-survivors had lower lymphocyte (p = 0.002) and basophil (p = 0.049) counts and the hematocrit showed a p-value (Is this what you meant???) of 0.021); higher NLR (p < 0.001), PLR (p = 0.047), NPR (p = 0.022) and SII (p = 0.022). Using general linear models, the survivors and non-survivors showed significant variations with weekly lymphocyte count (p < 0.001), neutrophil count (p = 0.005), NLR (p = 0.009), MLR (p = 0.010) and PLR (p = 0.035). All HDRs remained higher in the non-survivors in the 2nd week and 3rd week of diagnosis and the HDRs were higher in the intubated patients than in the non-intubated patients. The NLR and SII were more efficient predictors of mortality in COVID-19 patients. Conclusions: This study shows that serial lymphocyte and neutrophil counts, NLR, PLR, MLR, NPR and SII could serve as good and easily accessible markers of severity and predictors of outcomes in COVID-19 patients and should be used for the monitoring of treatment response.

Evaluation of prognostic markers in patients infected with SARS-CoV-2

Prognostic markers are the biomarkers used to measure the disease progression and patient outcome regardless of treatment in coronavirus disease 2019 (COVID-19). This study aimed to analyze laboratory parameters as prognostic markers for the early identification of disease severity. In this study, 165 patients attending Sukraraj Tropical and Infectious Disease Hospital with COVID-19 were enrolled and divided into severe and non-severe groups. The demographic data, underlying co-morbidities, and laboratory findings were analyzed and compared between severe and non-severe cases. The correlation between the disease criticality and laboratory parameters was analyzed. Cut-off values of parameters for severe patients were speculated through the receiver operating characteristics (ROC) curve, and regression analysis was performed to determine the risk factors. Patients with severe COVID-19 infection had significantly higher absolute neutrophil count, neutrophil-lymphocyte ratio (NLR), platelet-lymphocyte ratio (PLR), ferritin, positive carbohydrate reactive protein (CRP), glucose, urea, creatinine, and aspartate aminotransferase, while lower absolute lymphocyte count, absolute eosinophil count (AEC), and red blood cell count in comparison to non-severe infection. ROC analysis gave a cut-off value (sensitivity, specificity) of age, AEC, NLR, PLR, and ferritin as 47.5 years (70.2, 64.7%), 335 cells/mm(3) (74, 67%) 3.3 (68.4, 63.7%), 129 (77.2, 51%), and 241 ng/mL (74.0%, 65.0%) respectively. Risk factor analysis showed higher age, low AEC, high ferritin, and positive CRP as independent risk factors associated with severe COVID-19 infection. Hematological and inflammatory markers, including novel NLR and PLR, should be assessed to aid clinicians in the early identification of severe cases, prioritization of cases, and effective management to decrease the mortality of COVID-19 patients.

Platelet to Lymphocyte Ratio and Neutrophil to Lymphocyte Ratio as a Severity Marker in Moderate to Severe COVID-19 Patients

The world is facing COVID-19 pandemic which has created havoc amongst the mankind. It has created huge burden on health care facilities. The COVID-19 disease is caused by a newly emerged mutant of corona virus that is SARS-CoV-2. The virus is highly contagious and infects through respiratory route. It invades the respiratory tract mainly lungs causing coronavirus pneumonia. Patients usually present with fever, non-productive cough, breathlessness, myalgia, fatigue. In severe cases, disease can rapidly progress to ARDS (Acute Respiratory Distress Syndrome), septic shock, MODS (Multi-Organ Dysfunction Syndrome). Death may occur due to the complications. Furthermore, early diagnosis of severe cases and early interventions help in decreasing the burden on intensive healthcare facilities. HRCT scans are being used to assess the disease severity and CT score were calculated which was graded as mild, moderate and severe with score 0-8, 9-15 and 16-25 respectively. But this is highly expensive for general population of a developing country like India. Interleukins, D-dimer, ferritin, pro-calcitonin tests have also been used to assess the severity but again they pose a financial constraint for the population. So we needed a basic investigation which could let us assess the severity of disease and prognosis of the patient early for effective and early management of the patient. This might help provide better intensive care management for the patients at early stage and decrease the morbidity and mortality in COVID-19 patients. We have tried to unfold the CBC as prognostic marker for COVID-19 patients.

Systemic Inflammatory Biomarkers and Chest CT Findings as Predictors of Acute Limb Ischemia Risk, Intensive Care Unit Admission, and Mortality in COVID-19 Patients.

BACKGROUND: Numerous tools, including inflammatory biomarkers and lung injury severity scores, have been evaluated as predictors of thromboembolic events and the requirement for intensive therapy in COVID-19 patients. This study aims to verify the predictive role of inflammatory biomarkers [monocyte to lymphocyte ratio (MLR), neutrophil to lymphocyte ratio (NLR), platelet to lymphocyte ratio (PLR), systemic inflammatory index (SII), Systemic Inflammation Response Index (SIRI), and Aggregate Index of Systemic Inflammation (AISI)] and the CT Severity Score in acute limb ischemia (ALI) risk, intensive unit care (ICU) admission, and mortality in COVID-19 patients.; Methods: The present study was designed as an observational, analytical, retrospective cohort study and included all patients older than 18 years of age with a diagnosis of COVID-19 infection, confirmed through real time-polymerase chain reaction (RT-PCR), and admitted to the County Emergency Clinical Hospital of Targu-Mureș, Romania, and Modular Intensive Care Unit of UMFST "George Emil Palade" of Targu Mures, Romania between January 2020 and December 2021. RESULTS: Non-Survivors and "ALI" patients were associated with higher incidence of cardiovascular disease [atrial fibrillation (AF) p = 0.0006 and p = 0.0001; peripheral arterial disease (PAD) p = 0.006 and p < 0.0001], and higher pulmonary parenchyma involvement (p < 0.0001). Multivariate analysis showed a high baseline value for MLR, NLR, PLR, SII, SIRI, AISI, and the CT Severity Score independent predictor of adverse outcomes for all recruited patients (all p < 0.0001). Moreover, the presence of AF and PAD was an independent predictor of ALI risk and mortality. CONCLUSIONS: According to our findings, higher MLR, NLR, PLR, SII, SIRI, AISI, and CT Severity Score values at admission strongly predict ALI risk, ICU admission, and mortality. Moreover, patients with AF and PAD had highly predicted ALI risk and mortality but no ICU admission.

Neutrophil-to-Lymphocyte Ratio and Platelet-to-Lymphocyte Ratio Can Predict the Severity in COVID-19 Patients from Ethiopia: A Retrospective Study.

Background: Coronaviruses are a broad family of pathogens that can cause mild to severe respiratory illnesses. Due to a strong inflammatory response and a weak immunological response, viral pneumonia inflammation, like Coronavirus Disease 2019 (COVID-19), displays an unbalanced immune response. Therefore, circulating biomarkers of inflammation and the immune system can serve as reliable predictors of a patient's prognosis for COVID-19. Hematological ratios are reliable markers of inflammation that are frequently utilized in pneumonia, primarily in viral infections with low cost in developing countries. Purpose: To examine the neutrophil-to-lymphocyte ratio (NLR), lymphocyte-to-monocyte ratio (LMR), and platelet-to-lymphocyte ratio (PLR) in predicting the severity of COVID-19 patients. Methods: An institutional-based retrospective study was done on 105 hospitalized COVID-19 patients at the University of Gondar comprehensive specialized referral hospital, Northwest Ethiopia. The laboratory evaluations that were gathered, evaluated, and reported on included the total leucocyte count (TLC), absolute neutrophil count (ANC), absolute lymphocyte count (ALC), absolute monocyte count (AMC), NLR, LMR, and PLR. The Kruskal-Wallis test and Wilcoxon matched-pairs signed test were used to see whether there were any differences between the continuous variables. Receiver operating curve (ROC) analysis was used to determine the appropriate cut-off values for NLR, PLR, and LMR. P-value <0.05 was considered a statistically significant association. Results: ANC, NLR, and PLR were highest in the critical group (p = 0.001), while this group had the least ALC and LMR (p = 0.001). We calculated the optimal cut-off values of the hematological ratios; NLR (8.4), LMR (1.4), and PLR (18.0). NLR had the highest specificity and sensitivity, at 83.8% and 80.4%, respectively. Conclusion: Our research showed that NLR and PLR were good indicators of severity in COVID-19. However, our findings indicate that MLR is not a reliable predictor.

Artificial intelligence model on chest imaging to diagnose COVID-19 and other pneumonias: A systematic review and meta-analysis.

Objectives: When diagnosing Coronavirus disease 2019(COVID-19), radiologists cannot make an accurate judgments because the image characteristics of COVID-19 and other pneumonia are similar. As machine learning advances, artificial intelligence(AI) models show promise in diagnosing COVID-19 and other pneumonias. We performed a systematic review and meta-analysis to assess the diagnostic accuracy and methodological quality of the models. Methods: We searched PubMed, Cochrane Library, Web of Science, and Embase, preprints from medRxiv and bioRxiv to locate studies published before December 2021, with no language restrictions. And a quality assessment (QUADAS-2), Radiomics Quality Score (RQS) tools and CLAIM checklist were used to assess the quality of each study. We used random-effects models to calculate pooled sensitivity and specificity, I2 values to assess heterogeneity, and Deeks' test to assess publication bias. Results: We screened 32 studies from the 2001 retrieved articles for inclusion in the meta-analysis. We included 6737 participants in the test or validation group. The meta-analysis revealed that AI models based on chest imaging distinguishes COVID-19 from other pneumonias: pooled area under the curve (AUC) 0.96 (95 % CI, 0.94-0.98), sensitivity 0.92 (95 % CI, 0.88-0.94), pooled specificity 0.91 (95 % CI, 0.87-0.93). The average RQS score of 13 studies using radiomics was 7.8, accounting for 22 % of the total score. The 19 studies using deep learning methods had an average CLAIM score of 20, slightly less than half (48.24 %) the ideal score of 42.00. Conclusions: The AI model for chest imaging could well diagnose COVID-19 and other pneumonias. However, it has not been implemented as a clinical decision-making tool. Future researchers should pay more attention to the quality of research methodology and further improve the generalizability of the developed predictive models.

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

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

Platelet-to-Lymphocyte Ratio (PLR) Is Not a Predicting Marker of Severity but of Mortality in COVID-19 Patients Admitted to the Emergency Department: A Retrospective Multicenter Study.

(1) Introduction: In the present study, we investigate the prognostic value of platelet-to-lymphocyte ratio (PLR) as a marker of severity and mortality in COVID-19 infection. (2) Methods: Between 1 March and 30 April 2020, we conducted a multicenter, retrospective cohort study of patients with moderate to severe coronavirus 19 (COVID-19), all of whom were hospitalized after being admitted to the emergency department (ED). (3) Results: A total of 1035 patients were included in our study. Neither lymphocytes, platelets or PLR were associated with disease severity. Lymphocyte count was significantly lower and PLR values were significantly higher in the group of patients who died, and both were associated with mortality in the univariate analysis (OR: 0.524, 95% CI: (0.336-0.815), p = 0.004) and (OR: 1.001, 95% CI: (1.000-1.001), p = 0.042), respectively. However, the only biological parameter significantly associated with mortality in the multivariate analysis was platelet count (OR: 0.996, 95% CI: (0.996-1.000), p = 0.027). The best PLR value for predicting mortality in COVID-19 was 356.6 (OR: 3.793, 95% CI: (1.946-7.394), p < 0.001). (4) Conclusion: A high PLR value is however associated with excess mortality.

Cardiovascular complications and predictors of mortality in hospitalized patients with COVID-19: a cross-sectional study from the Indian subcontinent.

BACKGROUND: COVID-19 has spread rapidly across the world, producing significant morbidity and mortality. We investigated the cardiovascular complications and association of laboratory parameters with severity and mortality predictors in COVID-19 hospitalized patients. METHODS: Between May 2020 and June 2021, 730 COVID-19 patients were included in this retrospective observational study in the Coastal Karnataka region of South India. Acute coronary syndrome (ACS), myocarditis, arrhythmias, and all-cause mortality were reported as cardiovascular consequences. Neutrophil/lymphocyte ratio (NLR), platelet/lymphocyte ratio (PLR), serum creatinine, D-dimer, troponin T, N-terminal pro-brain natriuretic peptide (NT-ProBNP), serum ferritin, and serum lactate dehydrogenase (LDH) were among the laboratory parameters measured. RESULTS: Most common electrocardiogram (ECG) changes were prolonged QTc interval (45.6%) followed by ST-T changes (40.7%) and sinus tachycardia (24.2%). 9.2% patients presented with ACS, with 38.8% having ST-elevation myocardial infarction (STEMI) and 61.2% having non-ST elevation myocardial infarction (NSTEMI). In non-survivors, NLR (p < 0.001) and PLR (p = 0.001) were significantly higher. Multivariable regression analysis showed that age (OR:1.019, 95% CI 1.003-1.034; p = 0.017), acute kidney injury (OR:3.562, 95% CI 1.737-7.301; p = 0.001), white blood cell count (WBC) (OR = 1.100, 95% CI 1.035-1.169; p = 0.002), platelet count (OR = 0.994, 95% CI 0.990-0.997; p = 0.001), PLR (OR = 1.002, 95% CI 1.000-1.004; p = 0.023) and severe COVID-19 (OR = 9.012, 95% CI 3.844-21.129; p = 0.001) were independent predictors of mortality in COVID-19 patients. CONCLUSIONS: Age, WBC count, neutrophil%, NLR, PLR, creatinine, D-dimer, ferritin, LDH, tachycardia, and lymphocytes% strongly correlated with the severity of the disease. Age, acute kidney injury, elevated WBC count, a greater PLR, low platelet count, and COVID-19 severity were independent predictors of mortality.

Hematological abnormalities in immunosuppressed patients with COVID-19: Evidence from a single center. A cross sectional study.

BACKGROUND: Changes in hematological parameters in patients with COVID-19 are emerging as important features of the disease in the general population. In the present study we aimed to explore the hematological characteristics and its prevalence proportion ratio in patients with immunosuppression with COVID-19. AIM: To explore the differences between immunosuppressed and non-immunosuppressed patients, with and without COVID-19 from a hematological perspective. METHODS: This cross-sectional study reports on the baseline complete blood count in patients attending the HHA Hospital, in Chile. The study reports descriptive characteristics of the population, including sex, age, ethnicity, corticoids and biological therapy scheme and a complete report of blood test results. A total of 476 patients were enrolled in this study from October of 2020 to April 2021. RESULTS: Findings revels a significant increment (p value ≤ 0.001) on the median of total neutrophils and leucocytes, and in platelet-lymphocyte ratio (PLR), neutrophil- lymphocyte ratio (NLR) and monocyte-lymphocyte ratio (MLR) in immunosuppressed patients with COVID-19 (IS(+)) and immunocompetent patients with COVID-19 (IC(+)) compared with their respective controls. By contrast, a significant reduction on the median of lymphocytes, and eosinophiles was observed in IS(+) individuals compared with its controls. Also, the red blood cell count, hemoglobin, hematocrit, and mean corpuscular hemoglobin concentration were significantly reduced in IS(+) patients, whereas red blood cell, distribution width and mean corpuscular volume, were significantly higher in patients with COVID-19. CONCLUSION: Rapid blood tests, including, neutrophil, lymphocytes count and PLR, NLR can be used for early assessment and management of patients with immunosuppression.

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.