Eosinophil: A Nonnegligible Predictor in COVID-19 Re-Positive Patients.

Although vaccine resources are being distributed worldwide, insufficient vaccine production remains a major obstacle to herd immunity. In such an environment, the cases of re-positive occurred frequently, and there is a big controversy regarding the cause of re-positive episodes and the infectivity of re-positive cases. In this case-control study, we tracked 39 patients diagnosed with COVID-19 from the Jiaodong Peninsula area of China, of which 7 patients tested re-positive. We compared the sex distribution, age, comorbidities, and clinical laboratory results between normal patients and re-positive patients, and analysed the correlation between the significantly different indicators and the re-positive. Re-positive patients displayed a lower level of serum creatinine (63.38 ± 4.94 U/L vs. 86.82 ± 16.98 U/L; P =0.014) and lower albumin (34.70 ± 5.46 g/L vs. 41.24 ± 5.44 g/L, P =0.039) at the time of initial diagnosis. In addition, two positive phases and the middle negative phase in re-positive patients with significantly different eosinophil counts (0.005 ± 0.005 × 109/L; 0.103 ± 0.033 × 109/L; 0.007 ± 0.115 × 109/L; Normal range: 0.02-0.52 × 109/L). The level of eosinophils in peripheral blood can be used as a marker to predict re-positive in patients who once had COVID-19.

Emerging Evidence for Pleiotropism of Eosinophils.

Eosinophils are complex granulocytes with the capacity to react upon diverse stimuli due to their numerous and variable surface receptors, which allows them to respond in very different manners. Traditionally believed to be only part of parasitic and allergic/asthmatic immune responses, as scientific studies arise, the paradigm about these cells is continuously changing, adding layers of complexity to their roles in homeostasis and disease. Developing principally in the bone marrow by the action of IL-5 and granulocyte macrophage colony-stimulating factor GM-CSF, eosinophils migrate from the blood to very different organs, performing multiple functions in tissue homeostasis as in the gastrointestinal tract, thymus, uterus, mammary glands, liver, and skeletal muscle. In organs such as the lungs and gastrointestinal tract, eosinophils are able to act as immune regulatory cells and also to perform direct actions against parasites, and bacteria, where novel mechanisms of immune defense as extracellular DNA traps are key factors. Besides, eosinophils, are of importance in an effective response against viral pathogens by their nuclease enzymatic activity and have been lately described as involved in severe acute respiratory syndrome coronavirus SARS-CoV-2 immunity. The pleiotropic role of eosinophils is sustained because eosinophils can be also detrimental to human physiology, for example, in diseases like allergies, asthma, and eosinophilic esophagitis, where exosomes can be significant pathophysiologic units. These eosinophilic pathologies, require specific treatments by eosinophils control, such as new monoclonal antibodies like mepolizumab, reslizumab, and benralizumab. In this review, we describe the roles of eosinophils as effectors and regulatory cells and their involvement in pathological disorders and treatment.

Neutrophil-to-lymphocyte ratio, platelets-to-lymphocyte ratio, and eosinophils correlation with high-resolution computer tomography severity score in COVID-19 patients.

Inflammation has an important role in the progression of various viral pneumonia, including COVID-19. Circulating biomarkers that can evaluate inflammation and immune status are potentially useful in diagnosing and prognosis of COVID-19 patients. Even more so when they are a part of the routine evaluation, chest CT could have even higher diagnostic accuracy than RT-PCT alone in a suggestive clinical context. This study aims to evaluate the correlation between inflammatory markers such as neutrophil-to-lymphocyte ratio (NLR), platelets-to-lymphocytes ratio (PLR), and eosinophils with the severity of CT lesions in patients with COVID-19. The second objective was to seek a statically significant cut-off value for NLR and PLR that could suggest COVID-19. Correlation of both NLR and PLR with already established inflammatory markers such as CRP, ESR, and those specific for COVID-19 (ferritin, D-dimers, and eosinophils) were also evaluated. One hundred forty-nine patients with confirmed COVID-19 disease and 149 age-matched control were evaluated through blood tests, and COVID-19 patients had thorax CT performed. Both NLR and PLR correlated positive chest CT scan severity. Both NLR and PLR correlated positive chest CT scan severity. When NLR value is below 5.04, CT score is lower than 3 with a probability of 94%, while when NLR is higher than 5.04, the probability of severe CT changes is only 50%. For eosinophils, a value of 0.35% corresponds to chest CT severity of 2 (Se = 0.88, Sp = 0.43, AUC = 0.661, 95% CI (0.544; 0.779), p = 0.021. NLR and PLR had significantly higher values in COVID-19 patients. In our study a NLR = 2.90 and PLR = 186 have a good specificity (0.89, p = 0.001, respectively 0.92, p<0.001). Higher levels in NLR, PLR should prompt the clinician to prescribe a thorax CT as it could reveal important lesions that could influence the patient's future management.

COVID-19 diagnosis by routine blood tests using machine learning.

Physicians taking care of patients with COVID-19 have described different changes in routine blood parameters. However, these changes hinder them from performing COVID-19 diagnoses. We constructed a machine learning model for COVID-19 diagnosis that was based and cross-validated on the routine blood tests of 5333 patients with various bacterial and viral infections, and 160 COVID-19-positive patients. We selected the operational ROC point at a sensitivity of 81.9% and a specificity of 97.9%. The cross-validated AUC was 0.97. The five most useful routine blood parameters for COVID-19 diagnosis according to the feature importance scoring of the XGBoost algorithm were: MCHC, eosinophil count, albumin, INR, and prothrombin activity percentage. t-SNE visualization showed that the blood parameters of the patients with a severe COVID-19 course are more like the parameters of a bacterial than a viral infection. The reported diagnostic accuracy is at least comparable and probably complementary to RT-PCR and chest CT studies. Patients with fever, cough, myalgia, and other symptoms can now have initial routine blood tests assessed by our diagnostic tool. All patients with a positive COVID-19 prediction would then undergo standard RT-PCR studies to confirm the diagnosis. We believe that our results represent a significant contribution to improvements in COVID-19 diagnosis.

Host-dependent molecular factors mediating SARS-CoV-2 infection to gain clinical insights for developing effective targeted therapy.

Coronavirus disease 2019 (COVID-19), a recent viral pandemic that first began in December 2019, in Hunan wildlife market, Wuhan, China. The infection is caused by a coronavirus, SARS-CoV-2 and clinically characterized by common symptoms including fever, dry cough, loss of taste/smell, myalgia and pneumonia in severe cases. With overwhelming spikes in infection and death, its pathogenesis yet remains elusive. Since the infection spread rapidly, its healthcare demands are overwhelming with uncontrollable emergencies. Although laboratory testing and analysis are developing at an enormous pace, the high momentum of severe cases demand more rapid strategies for initial screening and patient stratification. Several molecular biomarkers like C-reactive protein, interleukin-6 (IL6), eosinophils and cytokines, and artificial intelligence (AI) based screening approaches have been developed by various studies to assist this vast medical demand. This review is an attempt to collate the outcomes of such studies, thus highlighting the utility of AI in rapid screening of molecular markers along with chest X-rays and other COVID-19 symptoms to enable faster diagnosis and patient stratification. By doing so, we also found that molecular markers such as C-reactive protein, IL-6 eosinophils, etc. showed significant differences between severe and non-severe cases of COVID-19 patients. CT findings in the lungs also showed different patterns like lung consolidation significantly higher in patients with poor recovery and lung lesions and fibrosis being higher in patients with good recovery. Thus, from these evidences we perceive that an initial rapid screening using integrated AI approach could be a way forward in efficient patient stratification.

Clinical Characteristics and Eosinophils in Young SARS-CoV-2-Positive Chinese Travelers Returning to Shanghai.

Background: The COVID-19 outbreak, which was first reported in Wuhan, China, in December 2019, began to spread throughout the world, and now involves over 200 countries. Methods: A total of 37 overseas young and middle-aged people, who tested as SARS-CoV-2 positive upon their return to Shanghai, were enrolled for an analysis of their clinical symptoms, blood routine indexes, and lung CT images. Results: The clinical symptoms were characterized by fever (51.4%), dry cough (13.5%), expectoration (27.0%), hypodynamia (21.6%), pharyngalia (10.8%), pharynoxerosis (8.1%), rhinobyon (13.5%), rhinorrhea (8.1%), muscular soreness (16.2%), and diarrhea (2.7%). In 16.2% of cases, no symptoms were reported. Fever was the most common symptom (51.40%). The pneumonic changes referred to the latticed ground glass imaging and similar white lung imaging accompanied by consolidated shadows. The rate of pneumonia was high (81.10%). We found that the exclusive percent of eosinophils was abnormally low. By analyzing the correlation of eosinophils, fever, and pneumonia, we found that the percentage of eosinophils was low in the COVID-19 patients afflicted with fever or pneumonia (P < 0.01). Additionally, pneumonia and fever were negatively correlated with the percentage of eosinophils and eosinophils/neutrophils ratio (P < 0.01, respectively), but not associated with pneumonia severity (P > 0.05). Fever was not correlated with pneumonia (P > 0.05). Conclusion: A low percentage of eosinophils may be considered as a biomarker of pneumonia of COVID-19, but not as a biomarker of pneumonia severity.

Haematological characteristics and risk factors in the classification and prognosis evaluation of COVID-19: a retrospective cohort study.

BACKGROUND: COVID-19 is an ongoing global pandemic. Changes in haematological characteristics in patients with COVID-19 are emerging as important features of the disease. We aimed to explore the haematological characteristics and related risk factors in patients with COVID-19. METHODS: This retrospective cohort study included patients with COVID-19 admitted to three designated sites of Wuhan Union Hospital (Wuhan, China). Demographic, clinical, laboratory, treatment, and outcome data were extracted from electronic medical records and compared between patients with moderate, severe, and critical disease (defined according to the diagnosis and treatment protocol for novel coronavirus pneumonia, trial version 7, published by the National Health Commission of China). We assessed the risk factors associated with critical illness and poor prognosis. Dynamic haematological and coagulation parameters were investigated with a linear mixed model, and coagulopathy screening with sepsis-induced coagulopathy and International Society of Thrombosis and Hemostasis overt disseminated intravascular coagulation scoring systems was applied. FINDINGS: Of 466 patients admitted to hospital from Jan 23 to Feb 23, 2020, 380 patients with COVID-19 were included in our study. The incidence of thrombocytopenia (platelet count <100 × 109 cells per L) in patients with critical disease (42 [49%] of 86) was significantly higher than in those with severe (20 [14%] of 145) or moderate (nine [6%] of 149) disease (p<0·0001). The numbers of lymphocytes and eosinophils were significantly lower in patients with critical disease than those with severe or moderate disease (p<0·0001), and prothrombin time, D-dimer, and fibrin degradation products significantly increased with increasing disease severity (p<0·0001). In multivariate analyses, death was associated with increased neutrophil to lymphocyte ratio (≥9·13; odds ratio [OR] 5·39 [95% CI 1·70-17·13], p=0·0042), thrombocytopenia (platelet count <100 × 109 per L; OR 8·33 [2·56-27·15], p=0·00045), prolonged prothrombin time (>16 s; OR 4·94 [1·50-16·25], p=0·0094), and increased D-dimer (>2 mg/L; OR 4·41 [1·06-18·30], p=0·041). Thrombotic and haemorrhagic events were common complications in patients who died (19 [35%] of 55). Sepsis-induced coagulopathy and International Society of Thrombosis and Hemostasis overt disseminated intravascular coagulation scores (assessed in 12 patients who survived and eight patients who died) increased over time in patients who died. The onset of sepsis-induced coagulopathy was typically before overt disseminated intravascular coagulation. INTERPRETATION: Rapid blood tests, including platelet count, prothrombin time, D-dimer, and neutrophil to lymphocyte ratio can help clinicians to assess severity and prognosis of patients with COVID-19. The sepsis-induced coagulopathy scoring system can be used for early assessment and management of patients with critical disease. FUNDING: National Key Research and Development Program of China.