Role of hematological parameters in the stratification of COVID-19 disease severity

The external validity of machine learning-based prediction scores from hematological parameters of COVID-19: A study using hospital records from Brazil, Italy, and Western Europe

The unprecedented worldwide pandemic caused by COVID-19 has motivated several research groups to develop machine-learning based approaches that aim to automate the diagnosis or screening of COVID-19, in large-scale. The gold standard for COVID-19 detection, quantitative-Real-Time-Polymerase-Chain-Reaction (qRT-PCR), is expensive and time-consuming. Alternatively, haematology-based detections were fast and near-accurate, although those were less explored. The external-validity of the haematology-based COVID-19-predictions on diverse populations are yet to be fully investigated. Here we report external-validity of machine learning-based prediction scores from haematological parameters recorded in different hospitals of Brazil, Italy, and Western Europe (raw sample size, 195554). The XGBoost classifier performed consistently better (out of seven ML classifiers) on all the datasets. The working models include a set of either four or fourteen haematological parameters. The internal performances of the XGBoost models (AUC scores range from 84% to 97%) were superior to ML models reported in the literature for some of these datasets (AUC scores range from 84% to 87%). The meta-validation on the external performances revealed the reliability of the performance (AUC score 86%) along with good accuracy of the probabilistic prediction (Brier score 14%), particularly when the model was trained and tested on fourteen haematological parameters from the same country (Brazil). The external performance was reduced when the model was trained on datasets from Italy and tested on Brazil (AUC score 69%) and Western Europe (AUC score 65%); presumably affected by factors, like, ethnicity, phenotype, immunity, reference ranges, across the populations. The state-of-the-art in the present study is the development of a COVID-19 prediction tool that is reliable and parsimonious, using a fewer number of hematological features, in comparison to the earlier study with meta-validation, based on sufficient sample size (n = 195554). Thus, current models can be applied at other demographic locations, preferably, with prior training of the model on the same population. Availability: https://covipred.bits-hyderabad.ac.in/home; https://github.com/debashreebanerjee/CoviPred.

Dynamic Changes in Lymphocyte Populations and Their Relationship with Disease Severity and Outcome in COVID-19

Studies suggest that the dynamic changes in cellular response might correlate with disease severity and outcomes in SARS-CoV-2 patients. The study aimed to investigate the dynamic changes of lymphocyte subsets in patients with COVID-19. In this regard, 53 patients with COVID-19 were prospectively included, classified as mild, moderate, and severe. The peripheral lymphocyte profiles (LyT, LyB, and NK cells), as well as CD4+/CD8+, CD3+/CD19+, CD3+/NK and CD19+/NK ratios, and their dynamic changes during hospitalization and correlation with disease severity and outcome were assessed. We found significant differences in CD3+ lymphocytes between severity groups (p < 0.0001), with significantly decreased CD3+CD4+ and CD3+CD8+ in patients with severe disease (p < 0.0001 and p = 0.048, respectively). Lower CD3+/CD19+ and CD3+/NK ratios among patients with severe disease (p = 0.019 and p = 0.010, respectively) were found. The dynamic changes of lymphocyte subsets showed a significant reduction in NK cells (%) and a significant increase in CD3+CD4+ and CD3+CD8+ cells in patients with moderate and severe disease. The ROC analysis on the relationship between CD3+ cells and fatal outcome yielded an AUC of 0.723 (95% CI 0.583-0.837; p = 0.007), while after addition of age and SpO2, ferritin and NLR, the AUC significantly improved to 0.927 (95%CI 0.811-0.983), p < 0.001 with a sensitivity of 90.9% (95% CI 58.7-99.8%) and specificity of 85.7% (95% CI 69.7-95.2%). The absolute number of CD3+ lymphocytes might independently predict fatal outcomes in COVID-19 patients and T-lymphocyte subset evaluation in high-risk patients might be useful in estimating disease progression.

Unveiling Immunological and Hematological Markers in COVID-19: Insights from a Clinical Study

The COVID-19 pandemic has affected the global health system and economies largely. Therefore, knowledge about the clinical and laboratory profiles of patients with COVID-19 would help in the management and prognosis of the disease. The immunological and hematological indices have emerged as critical determinants for the severity of the disease and the prognosis; however, association with COVID-19 is clouded. The present study is aimed to characterize the immunological and hematological profiles of patients with COVID-19 in correlation with the disease severity. The study included 1,019 polymerase chain reaction (PCR)-confirmed patients with COVID-19 who were classified into serious and nonserious groups, considering severity criteria. Clinical laboratory investigations included hematological, biochemical, and immunological parameters regarding leukocyte counts, hemoglobin levels, and inflammatory markers. Our analysis of immunological and hematological differences between serious and nonserious patients with COVID-19 indicates that serious cases reflected elevated levels of pro-inflammatory markers such as lactate dehydrogenase, C-reactive protein (CRP), D-dimer, and ferritin, representing immune system dysregulation and systemic inflammation. Furthermore, in serious cases, discrepancies had also been noticed for many hematological parameters than nonserious ones, which also contained leukocyte count and hemoglobin level. Additionally, the CRP, D-dimer, blood urea nitrogen, alanine transaminase, and albumin levels could be independent predictors of COVID-19 severity by multivariate logistic regression analysis. Cutoff values for these biomarkers were defined by receiver operating characteristic curve analysis defining optimal parameters for the risk stratification and prognostication. The current investigation provides a comprehensive understanding of immunological and hematological correlation with COVID-19 severity, refining clinical decision-making and therapeutic interventions to improve patient outcomes.

Immunologic mediators profile in COVID-19 convalescence

SARS-CoV-2 caused the pandemic situation experienced since the beginning of 2020, and many countries faced the rapid spread and severe form of the disease. Mechanisms of interaction between the virus and the host were observed during acute phase, but few data are available when related to immunity dynamics in convalescents. We conducted a longitudinal study, with 51 healthy donors and 62 COVID-19 convalescent patients, which these had a 2-month follow-up after symptoms recovery. Venous blood sample was obtained from all participants to measure blood count, subpopulations of monocytes, lymphocytes, natural killer cells and dendritic cells. Serum was used to measure cytokines, chemokines, growth factors, anti-N IgG and anti-S IgG/IgM antibodies. Statistic was performed by Kruskal-Wallis test, and linear regression with days post symptoms and antibody titers. All analysis had confidence interval of 95%. Less than 35% of convalescents were anti-S IgM+, while more than 80% were IgG+ in D30. Anti-N IgG decreased along time, with loss of seroreactivity of 13%. Eosinophil count played a distinct role on both antibodies during all study, and the convalescence was orchestrated by higher neutrophil-to-lymphocyte ratio and IL-15, but initial stages were marked by increase in myeloid DCs, B1 lymphocytes, inflammatory and patrolling monocytes, G-CSF and IL-2. Later convalescence seemed to change to cytotoxicity mediated by T lymphocytes, plasmacytoid DCs, VEGF, IL-9 and CXCL10. Anti-S IgG antibodies showed the longest perseverance and may be a better option for diagnosis. The inflammatory pattern is yet present on initial stage of convalescence, but quickly shifts to a reparative dynamic. Meanwhile eosinophils seem to play a role on anti-N levels in convalescence, although may not be the major causative agent. We must highlight the importance of immunological markers on acute clinical outcomes, but their comprehension to potentialize adaptive system must be explored to improve immunizations and further preventive policies.

Comparative Study of the Effects of Clonidine and Tranexamic Acid on Intraoperative Bleeding in Rhinoplasty: A Clinical Trial

Introduction

The present study was conducted to compare the effects of clonidine and tranexamic acid on the volume of bleeding and quality of the surgical field in terms of bleeding in candidates who underwent rhinoplasty.

Methods

In this two-sided clinical trial, candidates eligible for rhinoplasty were randomly assigned to two treatment groups: tranexamic acid and clonidine. The first group received tranexamic acid at a dose of 700 µg/kg of body weight 2 hours before the surgical procedure, whereas the second group received clonidine orally at a dose of 2 mg/kg of body weight, 90 minutes before surgery. Subsequently, the volume of bleeding was calculated based on the amount of blood collected via suction and in blood-soaked gauze, which was previously weighed.

Results

Among the 92 patients who underwent rhinoplasty, 82% were women. The mean age and standard deviation (SD) of individuals who underwent rhinoplasty were 29.22 ± 8.50 years. There were no significant differences between the two treatment groups in terms of age, gender, and body mass index. The volume of blood collected via suction during rhinoplasty, categorized into surgery duration <63 minutes and ≤63 minutes, showed a significant difference between the 2 treatment groups.

Conclusion

The use of tranexamic acid, compared with clonidine, resulted in lesser intraoperative bleeding and better surgical field quality. Considering the superior effectiveness of tranexamic acid in reducing intraoperative bleeding, it is recommended to use tranexamic acid instead of clonidine in rhinoplasty.

Dynamic Assessment of Hematological Parameters as Predictive Biomarkers for Disease Severity and Prognosis in COVID-19 Patients: A Longitudinal Study

BACKGROUND

The coronavirus disease 2019 (COVID-19) pandemic, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has led to substantial morbidity and mortality worldwide. Hematological abnormalities are common in COVID-19 patients and play a significant role in disease pathogenesis and prognosis.

OBJECTIVE

This study aimed to longitudinally monitor hematological parameters in COVID-19 patients and investigate their predictive value for disease severity and prognosis.

METHODS

A prospective longitudinal design was employed to enroll 121 adult patients diagnosed with COVID-19 based on positive SARS-CoV-2 reverse transcription-polymerase chain reaction (RT-PCR) test results. Baseline demographic and clinical data were collected, and hematological parameters, including complete blood count (CBC) indices, inflammatory markers, and coagulation profiles, were measured at predefined time points during hospitalization or outpatient visits. Follow-up assessments were conducted longitudinally to monitor the disease progression and clinical outcomes.

RESULTS

This study revealed dynamic changes in hematological parameters over the course of COVID-19. Hemoglobin levels showed a decrease from baseline (mean ± SD: 12.5 ± 1.8 g/dL) to the peak of illness (10.2 ± 2.0 g/dL), indicating the development of anemia during the acute phase of infection. White blood cell counts demonstrated an initial increase (8.9 ± 3.2 × 10^9/L) followed by a decline (5.4 ± 1.9 × 10^9/L) as the disease progressed, suggesting an early inflammatory response followed by immune suppression. The platelet counts fluctuated, with a decrease observed during the acute phase (190 ± 50 × 10^9/L) and subsequent recovery during convalescence (240 ± 60 × 10^9/L). Inflammatory markers, such as C-reactive protein and interleukin-6, were elevated, peaking at 120 and 150 pg/mL, respectively, indicating systemic inflammation. Coagulation profiles showed abnormalities suggestive of COVID-19-associated coagulopathy, including elevated D-dimer levels (mean ± SD: 3.5 ± 1.2 µg/mL) and prolonged prothrombin time (15.8 ± 2.5 seconds). Longitudinal analysis of hematological parameters revealed associations between disease severity and clinical outcomes, with certain abnormalities correlating with an increased risk of complications and a poor prognosis.

CONCLUSION

This study highlights the importance of monitoring hematological parameters in COVID-19 patients for risk stratification, prognostication, and guiding therapeutic interventions.

The role of platelet large cell ratio in determining mortality in COVID-19 patients

Inflammatory mechanisms have been implicated and have been subject to research in the clinical course of COVID-19 patients. In this study, platelet large cell ratio (P-LCR) has been examined as a novel prognostic and inflammatory parameter. A total of 1992 COVID-19-positive patients admitted to COVID-19 unit of Infectious Diseases were included. In order to identify a potential relationship between P-LCR and mortality, surviving patients were compared with subjects who died as a result of the disease. Although P-LCR levels showed a steady increase in all COVID-19 patients after admission, they were significantly higher in those who eventually died (P < .001), indicating a positive correlation between mortality and P-LCR. The P-LCR levels of patients followed up in the intensive care unit were statistically significantly higher than those followed up in the ward (P < .001). P-LCR levels of patients intubated in intensive care unit were statistically significantly higher than those who were not intubated (P < .001). Also, P-LCR levels were subdivided into 3 categories as normal, low, and elevated. Elevated P-LCR was found to be positively correlated with leukocyte count, neutrophil count, D-dimer, troponin, ferritin, and C-Reactive Protein (CRP) and showed negative correlation with fibrinogen, lymphocyte count, and platelet count. As P-LCR was correlated with the severity of inflammation in all COVID-19 patients, it was significantly higher in those patients who died. Elevated P-LCR was considered to be associated with the risk of severe disease and death. This inexpensive, readily available test may be incorporated into our clinical practice as a novel marker of poor prognosis in addition to other valuable laboratory parameters.

Long-Term Risk of Reduced Cognitive Performance and Associated Factors in Discharged Older Adults with COVID-19: A Longitudinal Prospective Study

BACKGROUND

Increasing numbers of reports have suggested a deterioration in cognitive performance after recovery from coronavirus disease 2019 (COVID-19), however insufficient information is available regarding long-term brain health and risk factors related to reduced cognitive performance in advanced age. We investigated the prevalence of reduced cognitive performance and its associated factors among older adults after COVID-19.

METHODS

This prospective observational study enrolled older individuals (aged ≥65 years) hospitalized for COVID-19. Discharged patients were contacted after an average of 15 months and a brief battery was administered during telephone interviews to assess their mental status.

RESULTS

Among the 174 patients, 77 (44.3%) showed reduced cognitive performance at follow-up. Multivariate analysis revealed that female sex, education level, and increased Deyo/Charlson Comorbidity Index score, which is an objective indicator of chronic disease burden, were independent risk factors for long-term cognitive performance. Depression and anxiety symptoms, assessed using the Patient Health Questionnaire-2 and Generalized Anxiety Disorder 2-item questionnaire at the end of the study, were not associated with reduced cognitive performance.

CONCLUSION

Our findings provide key insights into discharged older adults with COVID-19 at risk of long-term cognitive impairment, and help to ascertain the factors associated with this problem.

Hematological Indices in COVID-19 Patients with Rhinosinusitis Mucormycosis

Introduction

Rhinosinusitis mucormycosis (RM) is an invasive opportunistic fungal infection, especially among COVID-19 patients. The current study aimed to assess the peripheral blood hematological disorders of COVID-19 patients-associated RM.

Materials and Methods

During ten month, in two COVID-19 centers in Mashhad, Iran, from June 2021 to March 2022, eighty-three patients suspected of COVID-19 with rhinosinusitis or rhino-orbital mucormycosis participated in this study. The hematological indices of these patients were measured by independent sample T-test or Mann-Whitney test for quantitative data, and the qualitative variables were analyzed using Chi-square or Fisher's exact test in SPSS version 20 at a significance level of 0.05.

Results

Of the COVID-19 patients, 40 (48.2%) were affected by RM, and leukocytosis due to neutrophilia was observed in 30% of them. Leukocyte counts were normal in 10 (25%) patients, but 1 (2.5%) and 3 (7.5%) had leukopenia and lymphopenia, respectively. Leukocytosis plus lymphopenia was observed in 7 (17.5%) patients. Also, the synchronicity of leukopenia and lymphopenia was seen in 5 (12.5%) patients. Leukopenia, lymphopenia, and neutropenia have occurred concurrently in 2 (5%) patients. The complete blood count (CBC) showed that RBCs, hemoglobin (Hb), hematocrit (HCT), MCH, MCHC, platelet (PLT), and lymphocytes decreased while neutrophils increased.

Conclusion

Among the hematological parameters, leukocytosis due to neutrophilia and reduction in Hb, HCT, and PLT are more dominant factors in COVID-19 patients-associated RM.

Characteristics of hematological parameters on admission in COVID-19 Omicron variant infected in Chinese population: a large-scale retrospective study

BACKGROUND

The Omicron variant of SARS-CoV-2, currently the most prevalent strain, has rapidly spread in Jingzhou, China, due to changes in the country's epidemic prevention policy, resulting in an unprecedented increase in cases. Previous studies reported hematological parameters' predictive value in COVID-19 severity and prognosis, but their relevance for early diagnosis in patients infected by the Omicron variant, particularly in high-risk pneumonia cases, remains unclear. Our study aimed to evaluate these parameters as early warning indicators for Omicron-infected patients in fever clinics and those with pulmonary infections (PI).

METHODS

A total of 2,021 COVID-19 patients admitted to the fever clinic and infectious disease department of Jingzhou Hospital Affiliated to Yangtze University from November 1, 2022, to December 31, 2022, were retrospectively recruited. Demographic and hematological parameters were obtained from the electronic medical records of eligible patients. These hematological parameters were analyzed by receiver operating characteristic (ROC) curves to determine whether they can be used for early diagnosis of COVID-19 patients in fever clinics and the presence of PI in COVID-19 patients.

RESULTS

Statistical differences in hematological parameters were observed between COVID-19 patients with fever and PI and control groups (P < 0.01). The ROC curve further demonstrated that lymphocyte (LYM) counts, neutrophil (NEU) counts, monocyte-to-lymphocyte ratios (MLR), platelet-to-lymphocyte ratios (PLR), white blood cell counts (WBC), and mean corpuscular hemoglobin concentration (MCHC) were the top 6 indicators in diagnosing Omicron infection with fever, with area under the curve (AUC) values of 0.738, 0.718, 0.713, 0.702, 0.700, and 0.687, respectively (P < 0.01). Furthermore, the mean platelet volume (MPV) with an AUC of 0.764, red blood cell count (RBC) with 0.753, hematocrit (HCT) with 0.698, MLR with 0.694, mean corpuscular hemoglobin (MCH) with 0.676, and systemic inflammation response indexes (SIRI) with 0.673 were the top 6 indicators for the diagnosis of COVID-19 patients with PI (P < 0.01).

CONCLUSIONS

LYM, NEU, MLR, PLR, WBC, and MCHC can serve as potential prescreening indicators for Omicron infection in fever clinics. Additionally, MPV, RBC, HCT, MLR, MCH, and SIRI can predict the presence of PI in COVID-19 patients infected by the Omicron variant.

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.

Prognostic value of neutrophil and lymphocyte counts and neutrophil/lymphocyte ratio for predicting death in patients hospitalized for COVID-19

COVID-19 primarily affects the respiratory system and can cause changes in other systems. Early identification of patients with a higher potential for complications is critical to provide the best possible treatment to reduce the disease's lethality. This study aimed to analyze the behavior of hematologic biomarkers in predicting mortality in patients hospitalized with COVID-19. This retrospective cohort study used data from the medical records of patients hospitalized with COVID-19 between March and August 2020 in two referral hospitals for treatment of the disease in the city of Cuiabá (in the state of Mato Grosso, Brazil). Clinical and laboratory characteristics related to cardiovascular involvement and death during hospitalization were evaluated. Neutrophils, lymphocytes, and monocytes, as well as the neutrophil-to-lymphocyte ratio (NLR) and the monocyte-to-lymphocyte ratio (MRL), were used as potential biomarkers of death. A total of 199 patients were included (male: 113; mean age: 51.4 years). Leukocyte, neutrophil, and lymphocyte counts showed a statistically significant association with death, as did NLR and MRL. Satisfactory accuracy in predicting death was observed for leukocyte, neutrophil, lymphocyte, NLR, and MLR counts. The hematologic biomarkers studied may be useful for prognosticating hospitalized patients for the possibility of death from COVID-19.

Evaluation of circulating insulin-like growth factor-1, heart-type fatty acid-binding protein, and endotrophin levels as prognostic markers of COVID-19 infection severity

BACKGROUND

Coronavirus Disease 2019 (COVID-19) is a worldwide pandemic challenge spreading enormously within a few months. COVID-19 is characterized by the over-activation of the immune system causing cytokine storm. Insulin-like growth factor-1 (IGF-1) pathway can regulate the immune response via interaction with various implicated cytokines. Heart-type fatty acid-binding protein (H-FABP) has been shown to promote inflammation. Given the fact that coronavirus infections induce cytokines secretion leading to inflammatory lung injury, it has been suggested that H-FABP levels are affected by COVID-19 severity. Moreover, endotrophin (ETP), the cleavage product of collagen VI, may be an indicator of an overactive repair process and fibrosis, considering that viral infection may predispose or exacerbate existing respiratory conditions, including pulmonary fibrosis. This study aims to assess the prognostic capacity of circulating IGF-1, HFABP, and ETP, levels for COVID-19 severity progression in Egyptian patients.

METHODS

The study cohort included 107 viral RNA-positive patients and an equivalent number of control individuals with no clinical signs of infection. Clinical assessments included profiling of CBC; serum iron; liver and kidney functions; inflammatory markers. Circulating levels of IGF-1; H-FABP, and ETP were estimated using the corresponding ELISA kits.

RESULTS

No statistical difference in the body mass index was detected between the healthy and control groups, while the mean age of infected patients was significantly higher (P = 0.0162) than the control. Patients generally showed elevated levels of inflammatory markers including CRP and ESR concomitant with elevated serum ferritin; D dimer and procalcitonin levels, besides the COVID-19 characteristic lymphopenia and hypoxemia were also frequent. Logistic regression analysis revealed that oxygen saturation; serum IGF-1, and H-FABP can significantly predict the infection progression (P < 0.001 each). Both serum IGF-1 and H-FABP as well as O₂ saturation showed remarkable prognostic potentials in terms of large AUC values, high sensitivity/specificity values, and wide confidence interval. The calculated threshold for severity prognosis was 25.5 ng/mL; 19.5 ng/mL, 94.5, % and for IGF-1, H-FABP, and O₂ saturation; respectively. The calculated thresholds of serum IGF-1; H-FABP, and O₂ saturation showed positive and negative value ranges of 79-91% and 72-97%; respectively, with 66-95%, 83-94% sensitivity, and specificity; respectively.

CONCLUSION

The calculated cut-off values of serum IGF-1 and H-FABP represent a promising non-invasive prognostic tool that would facilitate the risk stratification in COVID-19 patients, and control the morbidity/mortality associated with progressive infection.

Hematological findings in COVID-19 and their correlation with severity of Disease

Objective

To evaluate the efficacy of hematological parameters to predict severity of COVID-19 patients.

Method

This was a cross-sectional comparative study conducted at Central Park Teaching Hospital, Lahore in COVID ward and COVID ICU between April 23, 2021 to June 23, 2021. Patients of all ages and both genders with positive PCR admitted in the COVID ward and ICU during this time span of two months were included in the study. Data was collected retrospectively.

Results

This study included 50 patients with male to female ratio of 1.38:1. Though males are more affected by COVID-19 but the difference is not statistically significant. The mean age of the study population was 56.21 and the patients in the severe disease group have higher age. It was observed that in severe/critical group the mean values of total leukocyte count 21.76×103 μI (p-value= 0.002), absolute neutrophil count 71.37% (p-value=0.045), neutrophil lymphocyte ratio (NLR) 12.80 (p-value=0.00) and PT 11.9 seconds (p-value=0.034) and the difference was statistically significant. While in severe/critical group, the mean values of hemoglobin 12.03g/dl (p-value=0.075), lymphocyte count 28.41% (p-value=0.8), platelet count 226×103 μI (p-value=0.67) and APTT 30.7 (p-value=0.081) and the difference was not significantly different between groups.

Conclusion

It can be concluded from the study that total leucocyte count, absolute neutrophil count and neutrophil lymphocyte ratio can predict in-hospital mortality and morbidity in COVID-19 patients.

On-admission and dynamic trend of laboratory profiles as prognostic biomarkers in COVID-19 inpatients

This large-scale study aimed to investigate the trend of laboratory tests of patients with COVID-19. Hospitalized confirmed and probable COVID-19 patients in three general hospitals were examined from March 20, 2020, to June 18, 2021. The confirmed and probable COVID-19 patients with known outcomes and valid laboratory results were included. The least absolute shrinkage and selection operator (LASSO) and Cox regression were used to select admittance prognostic features. Parallel Pairwise Comparison of mortality versus survival was used to examine the trend of markers. In the final cohort, 11,944 patients were enrolled, with an in-hospital mortality rate of 21.8%, mean age of 59.4 ± 18.0, and a male-to-female ratio of 1.3. Abnormal admittance level of white blood cells, neutrophils, lymphocytes, mean cellular volume, urea, creatinine, bilirubin, creatine kinase-myoglobin binding, lactate dehydrogenase (LDH), Troponin, c-reactive protein (CRP), potassium, and creatinine phosphokinase reduced the survival of COVID-19 inpatients. Moreover, the trend analysis showed lymphocytes, platelet, urea, CRP, alanine transaminase (ALT), and LDH have a dissimilar trend in non-survivors compared to survived patients. This study proposed a novel approach to find serial laboratory markers. Serial examination of platelet count, creatinine, CRP, LDH, and ALT can guide healthcare professionals in finding patients at risk of deterioration.

Age, comorbidities, c-reactive protein and procalcitonin as predictors of severity in confirmed COVID-19 patients in the Philippines

Background

The Coronavirus Disease 2019 (COVID-19) pandemic has been affecting people globally, and the Philippines is one of the countries greatly struck by the virus. The continued rise of new positive cases has drawn attention to the urgent need for healthcare management to cope with this challenge. Severity prediction could help improve medical decision-making and optimise the patient's treatment plan with a good clinical outcome. This study aimed to identify the determinants of COVID-19 disease severity.

Methods

Demographic characteristics and laboratory findings were collected from electronic medical records and paper forms of all confirmed COVID-19 cases reported by the University of Perpetual Help DALTA Medical Center between the September 1, 2020 and the October 31, 2021. We performed statistical analyses and interpretation of data to compare severe and non-severe groups.

Results

5,396 confirmed cases were examined. Most of the severe cases were elderly, male, had blood type A, and with comorbidities. Cycle threshold (Ct) values were lower in the severe group. Most patients had higher-than-normal levels of all blood parameters except platelet, white blood cell (WBC), neutrophil, and lymphocyte counts. Age, sex, ABO blood groups, comorbidities, open reading frame 1 ab (ORF1ab) and nucleocapsid (N) gene Ct values, ferritin, C-reactive protein (CRP), procalcitonin (PCT), D-dimer, white blood cell (WBC) count, neutrophil count, and lymphocyte count were significantly associated with disease severity. In multivariate analysis, age groups >60 and 30-59 years, presence of comorbidities, CRP level >5 ng/mL, and PCT >0.05 ng/mL were identified as disease severity predictors.

Conclusions

Based on our results, age, comorbidities, CRP, and PCT level may be utilised as primary assessment factors for possible hospital admission and close monitoring upon testing. Early detection of these risk factors may provide strategic interventions that help reduce mortality, hospital admissions, and more expensive and extensive treatments.

Immune Dynamics Involved in Acute and Convalescent COVID-19 Patients

COVID-19 is a viral disease that has caused millions of deaths around the world since 2020. Many strategies have been developed to manage patients in critical conditions; however, comprehension of the immune system is a key factor in viral clearance, tissue repairment, and adaptive immunity stimulus. Participation of immunity has been identified as a major factor, along with biomarkers, prediction of clinical outcomes, and antibody production after infection. Immune cells have been proposed not only as a hallmark of severity, but also as a predictor of clinical outcomes, while dynamics of inflammatory molecules can also induce worse consequences for acute patients. For convalescent patients, mild disease was related to higher antibody production, although the factors related to the specific antibodies based on a diversity of antigens were not clear. COVID-19 was explored over time; however, the study of immunological predictors of outcomes is still lacking discussion, especially in convalescent patients. Here, we propose a review using previously published studies to identify immunological markers of COVID-19 outcomes and their relation to antibody production to further contribute to the clinical and laboratorial management of patients.

The Role of Hemogram-derived Ratios in COVID-19 Severity Stratification in a Primary Healthcare Facility

Background

Coronavirus disease 2019 (COVID-19) can cause a wide clinical spectrum, ranging from asymptomatic to severe disease with a high mortality rate. In view of the current pandemic and the increasing influx of patients into healthcare facilities, there is a need to identify simple and reliable tools for stratifying patients.

Objective

Study aimed to analyze whether hemogram-derived ratios (HDRs) can be used to identify patients with a risk of developing a severe clinical form and admission to hospital.

Methods

This cross-sectional and observational study included 500 patients with a confirmed diagnosis of COVID-19. Data on clinical features and laboratory parameters were collected from medical records and 13 HDRs were calculated and analyzed. Descriptive and inferential statistics were included in the analysis.

Results

Of the 500 patients, 43.8% had a severe form of the disease. Lymphocytopenia, monocytopenia, higher C-reactive protein (CRP), and erythrocyte sedimentation rate (ESR) were found in severe patients (p < 0.05). Significantly higher neutrophil-to-lymphocyte ratio (NLR), derived NLR (dNLR), neutrophil-to-platelet ratio (NPR), neutrophil-to-lymphocyte-to-platelet ratio (NLPR) and CRP-to-lymphocyte ratio (CRP/Ly) values were found in severe patients (p < 0.001). In addition, they have statistically significant prognostic potential (p < 0.001). The area under the curve (AUC) for CRP/Ly, dNLR, NLPR, NLR, and NPR were 0.693, 0.619, 0.619, 0.616, and 0.603, respectively. The sensitivity and specificity were 65.7% and 65.6% for CRP/Ly, 51.6% and 70.8 for dNLR, 61.6% and 57.3% for NLPR, 40.6% and 80.4% for NLR, and 48.8% and 69.1% for NPR.

Conclusion

The results of the study suggest that NLR, dNLR, CRP/Ly, NPR, and NLPR can be considered as potentially useful markers for stratifying patients with a severe form of the disease. HDRs derived from routine blood tests results should be included in common laboratory practice since they are readily available, easy to calculate, and inexpensive.

Reduced IFN-γ levels along with changes in hematologic and immunologic parameters are key to COVID-19 severity in Bangladeshi patients

The manifestation of coronavirus disease 2019 (COVID-19) severity and mortality has been associated with dysregulation of the immune response, often influenced by racial disparities and conferred by changes in hematologic and immunologic parameters. These biological and hematologic parameters as well as cytokine profiles were investigated in a cohort of 61 COVID-19-positive patients (categorized into mild, moderate, and severe groups) from Bangladesh using standard analytical methods. The data reported that the interleukin (IL)-4 and IL-6 levels were significantly increased, whereas the levels of interferon (IFN)-γ were significantly reduced in patients with severe COVID-19 (p < 0.05) compared with those in patients with mild and/or moderate COVID-19. The extent of erythrocyte sedimentation rate (ESR); neutrophil count; and levels of ferritin, C-reactive protein (CRP), and D-dimer (p < 0.05) were found to be significantly increased, whereas the white blood cell (WBC), lymphocyte, eosinophil, and platelet counts (p < 0.05) were observed to be significantly reduced in patients with severe COVID-19 compared with those in the patients in other 2 groups. Our study exhibited a significantly higher IL-6-to-lymphocyte ratio in patients with severe COVID-19 than in those with mild and moderate COVID-19. The calculated neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), lymphocyte-to-monocyte ratio (LMR), and ferritin-to-ESR ratio were significantly increased in patients with severe COVID-19. The increase in the IL-4 and IL-6 levels along with CRP and D-dimer levels may envisage a hyperinflammatory environment and immune dysregulation, which contribute to prolonged viral persistence, leading to severe disease. However, the reduced level of IFN-γ can be attributed to a less fatality toll in Bangladesh compared with that in the rest of the world.

Laboratory Characteristics on SARS-CoV-2 Infection among Patients with Diabetes Mellitus: A Single-Center Retrospective Study

BACKGROUND

Diabetic patients have been severely affected by COVID-19 infection. It has been reported that the disease is more progressive leading to venous and arterial thromboembolism, due to multiple factors. This study was conducted to determine the hematologic parameters including D-dimer in diabetic patients with COVID-19 infection in association with disease severity and treatment.

METHOD

This retrospective cohort study was conducted at King Fahad Medical City, Saudi Arabia, after obtaining IRB approval, by collecting data regarding all laboratory parameters, disease severity, and anticoagulant treatment of COVID-19 diabetic patients (n = 159) from medical records from March to December 2020.

RESULT

Mean value of white blood cells, neutrophils, monocytes, eosinophils, lymphocyte monocyte ratio, C-reactive protein, serum ferritin, and LDH levels was elevated in severe cases than in mild cases with statistical significant increase in HbA1c (0.047), serum fibrinogen (0.007), C-reactive protein (0.005), serum ferritin (0.034), and serum LDH (0.015). Mortality was observed in 14 (8.8%) patients mostly with severe COVID-19 with diabetes. In our study, treatment with low molecular weight heparin was not significantly related to severity. A logistic regression analysis indicated an association of some laboratory parameters with severity and mortality of the disease.

CONCLUSION

The routine blood parameters if detected early will enable physicians to identify severe cases of COVID-19 patients with Diabetes for prompt treatment and save considerable time and resources.

Significance of hematologic abnormalities in COVID-19 severity among infected patients in Lagos, Nigeria

BACKGROUND

There have been suggestions that hematologic abnormalities in COVID-19 are linked with the progression and severity of diseases and mortality. Lymphopenia, sepsis, and thrombocytopenia were highly reported in patients with COVID-19. This study investigated the significance of hematologic abnormalities in patients with COVID-19 in Lagos, Nigeria, and its potential as a diagnostic tool for COVID-19 severity.

RESULTS

This was a retrospective observational study with a total of 340 patients with COVID-19 (236 patients included in the analysis). These patients were categorized into two groups, comprising 71 patients with severe COVID-19 (SCP) and 165 patients with non-severe COVID-19 (NSCP). The majority were males in both categories (SCP 74.6% and NSCP 63.6%). The mean ± SD ages for SCP and NSCP were 52.28 ± 16.87 and 42.44 ± 17.18 years, respectively. The SCP (52.1%) and NSCP (20.0%) had underlying health conditions. The SCP exhibited significantly higher neutrophil counts (P < 0.05) and significantly lower mean hemoglobin, red blood cell (RBC), packed cell volume (PCV), and lymphocyte values (P < 0.05). Anemia and lymphocytopenia were more prominent in the SCP group than in the NSCP group (P < 0.05). Hemoglobin, RBC, PCV, and lymphocytes were inversely correlated with age-group in the SCP, while only lymphocytes and platelets were inversely correlated with age-group in the NSCP. The highest area under the ROC curve (AUC) for neutrophils was 0.739 with a sensitivity of 62.0% and specificity of 80.0%, while white blood cells had an AUC of 0.722 with a sensitivity of 73.2% and specificity of 61.2%. The AUC for neutrophil-lymphocyte ratio (NLR) was 0.766 with a sensitivity of 63.3% and specificity of 83.5%, while that for the platelet-lymphocyte ratio (PLR) was 0.695 with a sensitivity and specificity of 61.7% and 77.8%.

CONCLUSIONS

COVID-19 affected the levels of hemoglobin, RBC, PCV, and lymphocytes in the blood, and the differences were significant between the SCP and NSCP. The significant changes in neutrophil and lymphocyte counts may be useful in the prognosis and management of COVID-19 severity in hospital settings. Furthermore, NLR and PLR may be used in the prognosis and management of severe COVID-19 infection, as well as provide an objective basis for early identification and management in low-resource settings.

Clinical laboratory parameters and comorbidities associated with severity of coronavirus disease 2019 (COVID-19) in Kurdistan Region of Iraq

Background

The pandemic coronavirus disease (COVID-19) dramatically spread worldwide. Considering several laboratory parameters and comorbidities may facilitate the assessment of disease severity. Early recognition of disease progression associated with severe cases of COVID-19 is essential for timely patient triaging. Our study investigated the characteristics and role of laboratory results and comorbidities in the progression and severity of COVID-19 cases.

Methods

The study was conducted from early-June to mid-August 2020. Blood samples and clinical data were taken from 322 patients diagnosed with COVID-19 at Qala Hospital, Kalar, Kurdistan Region of Iraq. Biological markers used in this study include complete blood count (CBC), D-dimer, erythrocyte sedimentation rate (ESR), serum ferritin, blood sugar, C-reactive protein (CRP) and SpO2.

Results

The sample included 154 males (47.8%) and 168 females (52.2%). Most females were in the mild and moderate symptom groups, while males developed more severe symptoms. Regarding comorbidities, diabetes mellitus was considered the greatest risk factor for increasing the severity of COVID-19 symptoms. As for biological parameters, WBC, granulocytes, ESR, Ferritin, CRP and D-Dimer were elevated significantly corresponding to the severity of the disease, while lymphocytes and SpO2 showed the opposite pattern. Higher RBC was significantly associated with COVID-19 severity, especially in females.

Conclusion

Gender, age and diabetes mellitus are important prognostic risk factors associated with severity and mortality of COVID-19. Relative to non-severe COVID-19, severe cases are characterized by an increase of most biological markers. These markers could be used to recognize severe cases and to monitor the clinical course of COVID-19.

Application of machine learning models based on decision trees in classifying the factors affecting mortality of COVID-19 patients in Hamadan, Iran

BACKGROUND

Due to the high mortality of COVID-19 patients, the use of a high-precision classification model of patient's mortality that is also interpretable, could help reduce mortality and take appropriate action urgently. In this study, the random forest method was used to select the effective features in COVID-19 mortality and the classification was performed using logistic model tree (LMT), classification and regression tree (CART), C4.5, and C5.0 tree based on important features.

METHODS

In this retrospective study, the data of 2470 COVID-19 patients admitted to hospitals in Hamadan, west Iran, were used, of which 75.02% recovered and 24.98% died. To classify, at first among the 25 demographic, clinical, and laboratory findings, features with a relative importance more than 6% were selected by random forest. Then LMT, C4.5, C5.0, and CART trees were developed and the accuracy of classification performance was evaluated with recall, accuracy, and F1-score criteria for training, test, and total datasets. At last, the best tree was developed and the receiver operating characteristic curve and area under the curve (AUC) value were reported.

RESULTS

The results of this study showed that among demographic and clinical features gender and age, and among laboratory findings blood urea nitrogen, partial thromboplastin time, serum glutamic-oxaloacetic transaminase, and erythrocyte sedimentation rate had more than 6% relative importance. Developing the trees using the above features revealed that the CART with the values of F1-score, Accuracy, and Recall, 0.8681, 0.7824, and 0.955, respectively, for the test dataset and 0.8667, 0.7834, and 0.9385, respectively, for the total dataset had the best performance. The AUC value obtained for the CART was 79.5%.

CONCLUSIONS

Finding a highly accurate and qualified model for interpreting the classification of a response that is considered clinically consequential is critical at all stages, including treatment and immediate decision making. In this study, the CART with its high accuracy for diagnosing and classifying mortality of COVID-19 patients as well as prioritizing important demographic, clinical, and laboratory findings in an interpretable format, risk factors for prognosis of COVID-19 patients mortality identify and enable immediate and appropriate decisions for health professionals and physicians.

Hematological profile of COVID-19 patients in Ramanagar district, Karnataka - A cross sectional study

Introduction and Aim: Coronavirus disease 2019 (COVID-19) is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) which rapidly evolved into a pandemic infecting humans all over the world. Whether hematologic and immunologic responses play a crucial role in progression of COVID-19 is still not clear. Increasing scientific evidence has shown that abnormalities in routine hematological tests, have the potential to diagnose SARS-CoV-2 infection in an economical way. Major laboratory changes indicating systemic inflammation and multi-organ impairment including hematopoietic system leading to lymphocytopenia, neutrophilia, eosinopenia, mild thrombocytopenia and ratios derived from these hematological parameters indicated severe disease and/or fatal outcomes. The aim was to study the hematological profile of Covid-19 patients admitted at a tertiary care hospital at Ramanagar district.   Materials and Methods: This retrospective study included 260 confirmed cases of Covid-19 diagnosed at a tertiary health care centre. Demographic, clinical, laboratory, treatment, and outcome data were extracted from the institutional electronic medical records after obtaining permission from the concerned authorities. From CBC test results obtained neutrophil lymphocyte ratio was derived.   Results: The present study revealed that majority of Covid positive patients   presented with lymphopenia. While a  significant association was observed between N/L ratio and disease severity, no significant association was seen between platelet count and severity of the disease.   Conclusion: Since the results of the present study features lymphopenia among large proportion of patients and elevated N/L ratio among critically ill patients these markers could be utilized as useful prognostic indicators during the initial assessment of disease severity and thus appropriate management can be planned for such patients before the condition of the patient deteriorates.

Epidemiology, Clinico-Pathological Characteristics, and Comorbidities of SARS-CoV-2-Infected Pakistani Patients

SARS-CoV-2 is a causative agent for COVID-19 disease, initially reported from Wuhan, China. The infected patients experienced mild to severe symptoms, resulting in several fatalities due to a weak understanding of its pathogenesis, which is the same even to date. This cross-sectional study has been designed on 452 symptomatic mild-to-moderate and severe/critical patients to understand the epidemiology and clinical characteristics of COVID-19 patients with their comorbidities and response to treatment. The mean age of the studied patients was 58 ± 14.42 years, and the overall male to female ratio was 61.7 to 38.2%, respectively. In total, 27.3% of the patients had a history of exposure, and 11.9% had a travel history, while for 60% of patients, the source of infection was unknown. The most prevalent signs and symptoms in ICU patients were dry cough, myalgia, shortness of breath, gastrointestinal discomfort, and abnormal chest X-ray (p < 0.001), along with a high percentage of hypertension (p = 0.007) and chronic obstructive pulmonary disease (p = 0.029) as leading comorbidities. The complete blood count indicators were significantly disturbed in severe patients, while the coagulation profile and D-dimer values were significantly higher in mild-to-moderate (non-ICU) patients (p < 0.001). The serum creatinine (1.22 μmol L^-1; p = 0.016) and lactate dehydrogenase (619 μmol L^-1; p < 0.001) indicators were significantly high in non-ICU patients, while raised values of total bilirubin (0.91 μmol L^-1; p = 0.054), C-reactive protein (84.68 mg L^-1; p = 0.001), and ferritin (996.81 mg L^-1; p < 0.001) were found in ICU patients. The drug dexamethasone was the leading prescribed and administrated medicine to COVID-19 patients, followed by remdesivir, meropenem, heparin, and tocilizumab, respectively. A characteristic pattern of ground glass opacities, consolidation, and interlobular septal thickening was prominent in severely infected patients. These findings could be used for future research, control, and prevention of SARS-CoV-2-infected patients.

Hematological findings in adult patients with SARS CoV‐2 infection at Tygerberg Hospital Cape Town South Africa

Background

Coronavirus disease 2019 (COVID‐19) is associated with hematological abnormalities of variable severity. The full blood count (FBC) and leukocyte differential count (DIFF) could facilitate the prediction of disease severity and outcome in COVID‐19. This study aimed to assess the hematological parameters in early severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) infection and their correlation with disease outcome.

Methods

A retrospective cross‐sectional descriptive study was performed. Adults with a FBC and positive SARS‐CoV‐2 polymerase chain reaction results between March 1, and June 31, 2020 were reviewed. Basic hematological parameters (FBC, DIFF) and human immunodeficiency virus (HIV) status were recorded. Outcome measures were admission to a general ward or intensive care unit (ICU), recovery or death.

Results

Six hundred and eighty‐five cases median age 51 years, were analyzed. Forty‐four percent were males and fourteen percent were HIV‐positive with no association between death and/or ICU admission (p = 0.522 and p = 0.830, respectively). Leucocytosis was predictive of ICU admission (odds ratio [OR]: 2.4, confidence interval [CI]: 1.77–3.8186) and neutrophilia, of both mortality (OR: 1.5, CI: 1.0440–2.0899) and ICU admission (OR: 4, CI: 2.5933–6.475). Median lymphocyte count was decreased and d‐dimer raised, showing no significant association with outcome. Raised neutrophil‐to‐lymphocyte‐ratio (NLR) was associated with increased odds of mortality (OR: 2.5, CI: 1.3556–3.2503) and ICU admission (OR: 4.8, CI: 2.4307–9.5430) as was monocyte‐to‐lymphocyte‐ratio (MLR) (OR: 2, CI: 1.3132–2.9064) and (OR: 2.3, CI: 1.0608–1.9935), respectively. Hospital admission and older age were significantly associated with mortality (p = 0.0008 and p < 0.0001), respectively.

Conclusion

Evidence‐based interpretation of routine laboratory parameters, readily available in resource‐constrained settings, may identify patients at increased risk of mortality. The FBC, DIFF, NLR, and MLR should form part of the early COVID‐19 investigation.

Even patients with mild COVID-19 symptoms after SARS-CoV-2 infection show prolonged altered red blood cell morphology and rheological parameters

Infection with the novel severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) and the associated coronavirus disease-19 (COVID-19) might affect red blood cells (RBC); possibly altering oxygen supply. However, investigations of cell morphology and RBC rheological parameters during a mild disease course are lacking and thus, the aim of the study. Fifty individuals with mild COVID-19 disease process were tested after the acute phase of SARS-CoV-2 infection (37males/13 females), and the data were compared to n = 42 healthy controls (30 males/12 females). Analysis of venous blood samples, taken at rest, revealed a higher percentage of permanently elongated RBC and membrane extensions in COVID-19 patients. Haematological parameters and haemoglobin concentration, MCH and MCV in particular, were highly altered in COVID-19. RBC deformability and deformability under an osmotic gradient were significantly reduced in COVID-19 patients. Higher RBC-NOS activation was not capable to at least in part counteract these reductions. Impaired RBC deformability might also be related to morphological changes and/or increased oxidative state. RBC aggregation index remained unaffected. However, higher shear rates were necessary to balance the aggregation-disaggregation in COVID-19 patients which might be, among others, related to morphological changes. The data suggest prolonged modifications of the RBC system even during a mild COVID-19 disease course.

Machine learning approaches in Covid-19 severity risk prediction in Morocco

The purpose of this study is to develop and test machine learning-based models for COVID-19 severity prediction. COVID-19 test samples from 337 COVID-19 positive patients at Cheikh Zaid Hospital were grouped according to the severity of their illness. Ours is the first study to estimate illness severity by combining biological and non-biological data from patients with COVID-19. Moreover the use of ML for therapeutic purposes in Morocco is currently restricted, and ours is the first study to investigate the severity of COVID-19. When data analysis approaches were used to uncover patterns and essential characteristics in the data, C-reactive protein, platelets, and D-dimers were determined to be the most associated to COVID-19 severity prediction. In this research, many data reduction algorithms were used, and Machine Learning models were trained to predict the severity of sickness using patient data. A new feature engineering method based on topological data analysis called Uniform Manifold Approximation and Projection (UMAP) shown that it achieves better results. It has 100% accuracy, specificity, sensitivity, and ROC curve in conducting a prognostic prediction using different machine learning classifiers such as X_GBoost, AdaBoost, Random Forest, and ExtraTrees. The proposed approach aims to assist hospitals and medical facilities in determining who should be seen first and who has a higher priority for admission to the hospital.

Synergistic Effect of Static Compliance and D-dimers to Predict Outcome of Patients with COVID-19-ARDS: A Prospective Multicenter Study

The synergic combination of D-dimer (as proxy of thrombotic/vascular injury) and static compliance (as proxy of parenchymal injury) in predicting mortality in COVID-19-ARDS has not been systematically evaluated. The objective is to determine whether the combination of elevated D-dimer and low static compliance can predict mortality in patients with COVID-19-ARDS. A “training sample” (March–June 2020) and a “testing sample” (September 2020–January 2021) of adult patients invasively ventilated for COVID-19-ARDS were collected in nine hospitals. D-dimer and compliance in the first 24 h were recorded. Study outcome was all-cause mortality at 28-days. Cut-offs for D-dimer and compliance were identified by receiver operating characteristic curve analysis. Mutually exclusive groups were selected using classification tree analysis with chi-square automatic interaction detection. Time to death in the resulting groups was estimated with Cox regression adjusted for SOFA, sex, age, PaO₂/FiO₂ ratio, and sample (training/testing). “Training” and “testing” samples amounted to 347 and 296 patients, respectively. Three groups were identified: D-dimer ≤ 1880 ng/mL (LD); D-dimer > 1880 ng/mL and compliance > 41 mL/cmH₂O (LD-HC); D-dimer > 1880 ng/mL and compliance ≤ 41 mL/cmH₂O (HD-LC). 28-days mortality progressively increased in the three groups (from 24% to 35% and 57% (training) and from 27% to 39% and 60% (testing), respectively; p < 0.01). Adjusted mortality was significantly higher in HD-LC group compared with LD (HR = 0.479, p < 0.001) and HD-HC (HR = 0.542, p < 0.01); no difference was found between LD and HD-HC. In conclusion, combination of high D-dimer and low static compliance identifies a clinical phenotype with high mortality in COVID-19-ARDS.

Neutrophil Maturation, Reactivity and Granularity Research Parameters to Characterize and Differentiate Convalescent Patients from Active SARS-CoV-2 Infection

Studying the dynamics changes of neutrophils during innate immune response in coronavirus 2019 (COVID-19) can help understand the pathogenesis of this disease. The aim of the study was to assess the usefulness of new neutrophil activation parameters: Immature Granulocyte (IG), Neutrophil Reactivity Intensity (NEUT-RI), Neutrophil Granularity Intensity (NEUT-GI), and data relating to granularity, activity, and neutrophil volume (NE-WX, NE-WY, NE-WZ) available in hematology analyzers to distinguish convalescent patients from patients with active SARS-CoV-2 infection and healthy controls (HC). The study group consisted of 79 patients with a confirmed positive RT-PCR test for SARS-CoV2 infection, 71 convalescent patients, and 20 HC. We observed leukopenia with neutrophilia in patients with active infection compared to convalescents and HC. The IG median absolute count was higher in convalescent patients than in COVID-19 and HC (respectively, 0.08 vs. 0.03 vs. 0.02, p < 0.0001). The value of the NEUT-RI parameter was the highest in HC and the lowest in convalescents (48.3 vs. 43.7, p < 0.0001). We observed the highest proportion of NE-WX, NE-WY, and NE-WZ parameters in HC, without differences between the COVID-19 and convalescent groups. New neutrophil parameters can be useful tools to assess neutrophils’ activity and functionalities in the immune response during infection and recovery from COVID-19 disease.

Hematological profiles of COVID-19 patients at the Ratlam district, Madhya Pradesh State, India

It is of interest to compare the hematological profile (using Complete blood count) of COVID patients admitted in ICU, private ward, and isolation ward with varying severity. This data will help predict the severity of infection at peripheries and rural areas.  Detailed history and CBC was performed for all the cases. Different ratios and indexes such as systemic inflammatory index (SII), Neutrophil lymphocyte ratio (NLR), platelet lymphocyte ratio (PLR) were assessed. A total of 862 cases with a mean age of 49.9 ±17.4 years were enrolled. Hemoglobin level, lymphocyte (count per liter and percentage) were significantly lower in patients admitted in ICU as compared to patients admitted in the isolation ward and private ward (p <0.05). However, TLC, neutrophils, platelet count were higher in patients admitted to ICU (p <0.05). The Various ratios such as SII, NLR, and PLR showed significantly higher value in cases admitted in ICU (p <0.05). The TLC, neutrophil count, neutrophil percentage, SII, NLR, and PLR were significant predictors of severe disease (admission in ICU) with high diagnostic accuracy. We show that complete blood count method is a simple, readily available, rapid, and inexpensive tool that can be utilized for diagnosis and can predicting the severity of COVID 19 where RTPCR or trained staff is not available. Thus, NLR (%), SII, PLR, and TLC can predict severe illness with high accuracy.

Dynamic profile and clinical implications of hematological and immunological parameters in COVID-19 patients. A retrospective study

BACKGROUND

Ever since the World Health Organization (WHO) announced the SARS-CoV-2 or nCOVID-19 infection (a pandemic), continuous spread of the virus has been observed which has continuously seen to affect and kill multitudes of individuals all over the world. An understanding of the pathophysiology of this disease is necessary for an effective treatment. Laboratory investigations play an important role in the diagnosis as well as treatment of this infectious disease. Hematological parameters demonstrate alterations during the progression of nCOVID-19 infection. Of these, many are indicative of extremely poor clinical outcome. Hematological findings like leukopenia, lymphopenia, thrombocytopenia and coagulation-related abnormalities are the most common manifestations. The aim of this study was to assess the dynamic profile and clinical implications of hematological and immunological parameters among nCOVID-19 infections.

MATERIALS AND METHODS

This retrospective study was designed after categorizing patients suffering from COVID-19 into three groups: (a) Group I; (b) Group II and (c) Group III or severe critical patients. Hematological and immunological parameters of neutrophilic and white blood cell counts, d-dimer levels, hemoglobin levels, immunoglobulin G (IgG) and M (IgM) levels and interleukin-6 (IL-6) levels were assessed. Statistical analysis using Kruskal-Wallis test was used.

RESULTS

Normal white blood cell and neutrophil count among COVID-19 patients was seen. However, median values in Group II (P < 0.01) and Group III (P < 0.0001) were found to show significantly higher values when compared to Group I. A significant (P < 0.01) decrease in lymphocytic counts was found among severe and critical patients. Hemoglobin level was found to demonstrate higher decrease (P < 0.01) among severe and critical patients. Platelet count was found in normal range in all COVID-19 patients. Routine coagulation tests revealed increased fibrinogen (P < 0.01) and d-dimer levels (P < 0.0001) in severe and critical patients. Normal proportions of total CD3+ and CD4 + T lymphocytes were observed in COVID-19. However, CD8 + T lymphocytes proportion was found to be decreased (P-value < 0.05). Immunoglobulin G levels among Groups II and III patients were found to be lower when compared with Group I (P < 0.001). No statistical significance was observed between the groups in IgM levels. Plasma IL-6 levels were found to show progressive rise among Groups II and III patients (P < 0.05).

CONCLUSION

Analysis of hematological and immunological parameters profiles in COVID-19 patients may help in deciphering the clinical progression of patients suffering from COVID-19 disease. Thus, regular monitoring of the hospitalized patients may help in planning the management of these cases.

Neutrophils and COVID-19: Active Participants and Rational Therapeutic Targets

Whilst the majority of individuals infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative pathogen of COVID-19, experience mild to moderate symptoms, approximately 20% develop severe respiratory complications that may progress to acute respiratory distress syndrome, pulmonary failure and death. To date, single cell and high-throughput systems based analyses of the peripheral and pulmonary immune responses to SARS-CoV-2 suggest that a hyperactive and dysregulated immune response underpins the development of severe disease, with a prominent role assigned to neutrophils. Characterised in part by robust generation of neutrophil extracellular traps (NETs), the presence of immature, immunosuppressive and activated neutrophil subsets in the circulation, and neutrophilic infiltrates in the lung, a granulocytic signature is emerging as a defining feature of severe COVID-19. Furthermore, an assessment of the number, maturity status and/or function of circulating neutrophils at the time of hospital admission has shown promise as a prognostic tool for the early identification of patients at risk of clinical deterioration. Here, by summarising the results of studies that have examined the peripheral and pulmonary immune response to SARS-CoV-2, we provide a comprehensive overview of the changes that occur in the composition, phenotype and function of the neutrophil pool in COVID-19 patients of differing disease severities and discuss potential mediators of SARS-CoV-2-induced neutrophil dysfunction. With few specific treatments currently approved for COVID-19, we conclude the review by discussing whether neutrophils represent a potential therapeutic target for the treatment of patients with severe COVID-19.

Analysis of laboratory blood parameter results for patients diagnosed with COVID-19, from all ethnic group populations: A single centre study

Introduction

Although factors such as age, sex, diabetes, obesity and changes in certain laboratory investigations are important prognostic factors in COVID‐19 infection, these may not apply to all ethnic/racial groups. We hypothesized differences in routine biochemistry and haematology indices in Caucasian and a combined group of Black, Asian and Minority Ethnic (BAME) patients who tested positive for COVID‐19 who died, compared to survivors.

Methods

We tested our hypothesis in 445 patients (229 Caucasian, 216 BAME) admitted to secondary care with proven COVID‐19 infection, in whom standard routine laboratory indices were collected on admission.

Results

After 28 weeks, 190 (42.7%) had died within 28 days of COVID diagnosis (97 Caucasians [42.4%], 93 BAMEs [43.1%], P = .923). A general linear model analysis found the ethnicity interaction with mortality to be significant for fibrinogen, ferritin and HbA₁c (after controlling for age). In a multivariate analysis, a neutrophil/lymphocyte ratio > 7.4 and a urea/albumin ratio > 0.28 increased the odds of death for both the Caucasian and the BAME group. Additional factors increasing the odds ratio in the BAME group included age >60 years and being diabetic.

Conclusion

Neutrophil/lymphocyte ratio and urea/albumin ratio are simple metrics that predict death to aid clinicians in determining the prognosis of COVID‐19 and help provide early intensive intervention to reduce mortality. In the BAME groups, intensive monitoring even at younger age and those with diabetes may also help reduce COVID‐19 associated mortality.