Distinguishing between COVID-19 and influenza during the early stages by measurement of peripheral blood parameters

Characterization and trajectories of hematological parameters prior to severe COVID-19 based on a large-scale prospective health checkup cohort in western China: a longitudinal study of 13-year follow-up

BACKGROUND

The relaxation of the "zero-COVID" policy on Dec. 7, 2022, in China posed a major public health threat recently. Complete blood count test was discovered to have complicated relationships with COVID-19 after the infection, while very few studies could track long-term monitoring of the health status and identify the characterization of hematological parameters prior to COVID-19.

METHODS

Based on a 13-year longitudinal prospective health checkup cohort of ~ 480,000 participants in West China Hospital, the largest medical center in western China, we documented 998 participants with a laboratory-confirmed diagnosis of COVID-19 during the 1 month after the policy. We performed a time-to-event analysis to explore the associations of severe COVID-19 patients diagnosed, with 34 different hematological parameters at the baseline level prior to COVID-19, including the whole and the subtypes of white and red blood cells.

RESULTS

A total of 998 participants with a positive SARS-CoV-2 test were documented in the cohort, 42 of which were severe cases. For white blood cell-related parameters, a higher level of basophil percentage (HR = 6.164, 95% CI = 2.066-18.393, P = 0.001) and monocyte percentage (HR = 1.283, 95% CI = 1.046-1.573, P = 0.017) were found associated with the severe COVID-19. For lymphocyte-related parameters, a lower level of lymphocyte count (HR = 0.571, 95% CI = 0.341-0.955, P = 0.033), and a higher CD4/CD8 ratio (HR = 2.473, 95% CI = 1.009-6.059, P = 0.048) were found related to the risk of severe COVID-19. We also observed that abnormality of red cell distribution width (RDW), mean corpuscular hemoglobin concentration (MCHC), and hemoglobin might also be involved in the development of severe COVID-19. The different trajectory patterns of RDW-SD and white blood cell count, including lymphocyte and neutrophil, prior to the infection were also discovered to have significant associations with the risk of severe COVID-19 (all P < 0.05).

CONCLUSIONS

Our findings might help decision-makers and clinicians to classify different risk groups of population due to outbreaks including COVID-19. They could not only optimize the allocation of medical resources, but also help them be more proactive instead of reactive to long COVID-19 or even other outbreaks in the future.

The blood routine test holds screening values for influenza A in 2023: a retrospective study

Background

Influenza A is the most common viral pathogen isolated from pediatric clinics during influenza seasons. Some young patients with influenza manifest rapid progression with high fever and severe sequelae, such as pneumonia and meningitis. Therefore, early diagnosis and prompt treatment are highly important. Specific diagnostic tests currently include antigen detection, antibody detection, nucleic acid test and virus isolation. Rapid antigen testing is the most commonly adopted method in the outpatient setting, but false negative results are frequently observed, which causes delayed treatment and severe outcome. Routine blood test is the most commonly used detection for the outpatients. Incorporating specific blood cell counts into rapid antigen test may overcome some technical issues and enable accurate early diagnosis.

Methods

We enrolled 537 children with influenza-like symptoms like fever or respiratory symptoms from pediatric outpatients and 110 children without infectious diseases for control. Routine blood tests detected by a routine analyzer and influenza A virus antigen detection were performed in the patients. Significant blood routine parameters between groups were examined by statistical tests. Parameters in routine blood test were assessed by the receiver operating characteristic curve to find the screening indicators of influenza A. Multivariate logistic regression were used to establish the optimal combinations of blood routine parameters in our screening model.

Results

Two subgroups were set according to age: ≤6 years old group and >6 years old group. In each group, patients were further divided into three subgroups: the influenza A-positive-result group (A+ group) (n=259), influenza A-negative-result group (A- group) (n=277) and healthy control group (H group) (n=110). Most routine blood parameters showed significant differences among the three subgroups in each age group. Notably, lymphocyte (LYM) number, platelet (PLT) number, lymphocyte-to-monocyte ratio (LMR) and LYM multiplied by PLT (LYM*PLT) exhibited extremely significant differences. Using A- group as a reference based on the area under the curve (AUC), both age groups had a similar trend. For A- group, the optimal cutoff value of LYM*PLT was 221.6, the AUC, the sensitivity and specificity were 0.6830, 55.71% and 76.92% in the ≤6 years old group. Meanwhile, the cutoff value of LYM*PLT was 196.7, and the AUC, the sensitivity and specificity were 0.6448, 53.97% and 70.81%, respectively in the >6 years old group. Screening model based on multivariate logistic regression model revealed that LYM*PLT was the optimal parameter combinations in ≤6 years old group (AUC =0.7202), while LYM and PLT were the optimal parameter combinations in >6 years old group (AUC =0.6760).

Conclusions

Several blood routine parameters in children with influenza A demonstrate differential levels in both age subgroups. The LYM*PLT exhibits the potential screening value of influenza infection.

Can Haematological Parameters Discriminate COVID-19 from Influenza?

Symptoms of COVID-19 are similar to the influenza virus, but because treatments and prognoses are different, it is important to accurately and rapidly differentiate these diseases. The aim of this study was to evaluate whether the analysis of complete blood count (CBC), including cellular population (CPD) data of leukocytes and automated flow cytometry analysis, could discriminate these pathologies. In total, 350 patients with COVID-19 and 102 patients with influenza were included between September 2021 and April 2022 in the tertiary hospital of Suresnes (France). Platelets were lower in patients with influenza than in patients with COVID-19, whereas the CD16pos monocyte count and the ratio of the CD16pos monocytes/total monocyte count were higher. Significant differences were observed for 9/56 CPD of COVID-19 and flu patients. A logistic regression model with 17 parameters, including among them 11 CPD, the haemoglobin level, the haematocrit, the red cell distribution width, and B-lymphocyte and CD16pos monocyte levels, discriminates COVID-19 patients from flu patients. The sensitivity and efficiency of the model were 96.2 and 86.6%, respectively, with an area under the curve of 0.862. Classical parameters of CBC are very similar among the three infections, but CPD, CD16pos monocytes, and B-lymphocyte levels can discriminate patients with COVID-19.

Gender perspective on the association between liver enzyme markers and non-alcoholic fatty liver disease: insights from the general population

Objective

Every distinct liver enzyme biomarker exhibits a strong correlation with non-alcoholic fatty liver disease (NAFLD). This study aims to comprehensively analyze and compare the associations of alanine aminotransferase (ALT), aspartate aminotransferase (AST), and gamma-glutamyl transferase (GGT) with NAFLD from a gender perspective.

Methods

This study was conducted on 6,840 females and 7,411 males from the NAGALA cohort. Multivariable logistic regression analysis was used to compare the associations between liver enzyme markers and NAFLD in both genders, recording the corresponding adjusted odds ratios (ORs) and 95% confidence intervals (CIs). Receiver operating characteristic (ROC) curves were used to evaluate the accuracy of individual liver enzyme markers and different combinations of them in identifying NAFLD.

Results

Liver enzyme markers ALT, AST, and GGT were all independently associated with NAFLD and exhibited significant gender differences (All P-interaction<0.05). In both genders, ALT exhibited the most significant association with NAFLD, with adjusted standardized ORs of 2.19 (95% CI: 2.01-2.39) in males and 1.60 (95% CI: 1.35-1.89) in females. Additionally, ROC analysis showed that ALT had significantly higher accuracy in identifying NAFLD than AST and GGT in both genders (Delong P-value < 0.05), and the accuracy of ALT in identifying NAFLD in males was higher than that in females [Area under the ROC curve (AUC): male 0.79, female 0.77]. Furthermore, out of the various combinations of liver enzymes, ALT+GGT showed the highest accuracy in identifying NAFLD in both genders, with AUCs of 0.77 (95% CI: 0.75-0.79) in females and 0.79 (95% CI: 0.78-0.81) in males.

Conclusion

Our study revealed significant gender differences in the associations of the three commonly used liver enzyme markers with NAFLD. In both genders, the use of ALT alone may be the simplest and most effective tool for screening NAFLD, especially in males.

MultiCOVID: a multi modal deep learning approach for COVID-19 diagnosis

The rapid spread of the severe acute respiratory syndrome coronavirus 2 led to a global overextension of healthcare. Both Chest X-rays (CXR) and blood test have been demonstrated to have predictive value on Coronavirus Disease 2019 (COVID-19) diagnosis on different prevalence scenarios. With the objective of improving and accelerating the diagnosis of COVID-19, a multi modal prediction algorithm (MultiCOVID) based on CXR and blood test was developed, to discriminate between COVID-19, Heart Failure and Non-COVID Pneumonia and healthy (Control) patients. This retrospective single-center study includes CXR and blood test obtained between January 2017 and May 2020. Multi modal prediction models were generated using opensource DL algorithms. Performance of the MultiCOVID algorithm was compared with interpretations from five experienced thoracic radiologists on 300 random test images using the McNemar-Bowker test. A total of 8578 samples from 6123 patients (mean age 66 ± 18 years of standard deviation, 3523 men) were evaluated across datasets. For the entire test set, the overall accuracy of MultiCOVID was 84%, with a mean AUC of 0.92 (0.89-0.94). For 300 random test images, overall accuracy of MultiCOVID was significantly higher (69.6%) compared with individual radiologists (range, 43.7-58.7%) and the consensus of all five radiologists (59.3%, P < .001). Overall, we have developed a multimodal deep learning algorithm, MultiCOVID, that discriminates among COVID-19, heart failure, non-COVID pneumonia and healthy patients using both CXR and blood test with a significantly better performance than experienced thoracic radiologists.

Factors influencing recurrent emergency department visits for mild acute respiratory tract infections caused by the influenza virus

Background

Seasonal viral outbreaks, exemplified by influenza A and B viruses, lead to spikes in emergency department (ED) visits, straining healthcare facilities. Addressing ED overcrowding has become paramount due to its implications for patient care and healthcare operations. Recurrent visits among influenza patients remain an underexplored aspect, necessitating investigation into factors influencing such revisits.

Methods

Conducted within a tertiary care university hospital, this study adopts an observational retrospective cohort design. The study included adult patients with acute respiratory symptoms diagnosed with influenza using rapid antigen testing. The cohort was divided into single and recurrent ED visitors based on revisits within 10 days of initial discharge. A comparative analysis was performed, evaluating demographics, laboratory parameters, and clinical process data between recurrent visitors and single visitors.

Results

Among 218 patients, 36.2% (n = 139) experienced recurrent ED visits. Age and gender disparities were not significant. Antibiotics were prescribed for 55.5% (n = 121) and antivirals for 92.7% (n = 202) of patients, with no notable influence on recurrence. Recurrent visitors exhibited lower monocyte counts, hemoglobin levels, higher PDW and P-LCR percentages, and increased anemia prevalence (p = 0.036, p = 0.01, p = 0.004, p = 0.029, p = 0.017, respectively). C-reactive protein (CRP) levels did not significantly affect recurrence.

Conclusion

This study highlights the pressing concern of recurrent ED visits among mild influenza patients, magnifying the challenges of ED overcrowding. The observed notable prescription rates of antibiotics and antivirals underscore the intricate landscape of influenza management. Diminished monocyte counts, hemoglobin levels, and altered platelet parameters signify potential markers for identifying patients at risk of recurrent visits.

Single-Center Experience in Detecting Influenza Virus, RSV and SARS-CoV-2 at the Emergency Department

Reverse transcription polymerase chain reaction (RT-PCR) on respiratory tract swabs has become the gold standard for sensitive and specific detection of influenza virus, respiratory syncytial virus (RSV) and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). In this retrospective analysis, we report on the successive implementation and routine use of multiplex RT-PCR testing for patients admitted to the Internal Medicine Emergency Department (ED) at a tertiary care center in Western Austria, one of the hotspots in the early coronavirus disease 2019 (COVID-19) pandemic in Europe. Our description focuses on the use of the Cepheid^® Xpert^® Xpress closed RT-PCR system in point-of-care testing (POCT). Our indications for RT-PCR testing changed during the observation period: From the cold season 2016/2017 until the cold season 2019/2020, we used RT-PCR to diagnose influenza or RSV infection in patients with fever and/or respiratory symptoms. Starting in March 2020, we used the RT-PCR for SARS-CoV-2 and a multiplex version for the combined detection of all these three respiratory viruses to also screen subjects who did not present with symptoms of infection but needed in-hospital medical treatment for other reasons. Expectedly, the switch to a more liberal RT-PCR test strategy resulted in a substantial increase in the number of tests. Nevertheless, we observed an immediate decline in influenza virus and RSV detections in early 2020 that coincided with public SARS-CoV-2 containment measures. In contrast, the extensive use of the combined RT-PCR test enabled us to monitor the re-emergence of influenza and RSV detections, including asymptomatic cases, at the end of 2022 when COVID-19 containment measures were no longer in place. Our analysis of PCR results for respiratory viruses from a real-life setting at an ED provides valuable information on the epidemiology of those infections over several years, their contribution to morbidity and need for hospital admission, the risk for nosocomial introduction of such infection into hospitals from asymptomatic carriers, and guidance as to how general precautions and prophylactic strategies affect the dynamics of those infections.

Coronavirus disease 2019 (COVID-19): Focus on peripheral blood cell morphology

Numerous studies have shown peculiar morphological anomalies in COVID-19 patients' smears. We searched all the peer-reviewed scientific publications that explicitly reference the cytomorphological alterations on peripheral blood smears of patients with COVID-19. We extracted data from sixty-five publications (case reports, patient group studies, reviews, and erythrocyte morphology studies). The results show that frequent alterations concern the morphology of lymphocytes (large lymphocytes with weakly basophilic cytoplasm, plasmacytoid lymphocytes, large granular lymphocytes). Neutrophils display abnormal nuclei and cytoplasm in a distinctive cytomorphological picture. Besides a left shift in maturation, granulations can be increased (toxic type) or decreased with areas of basophilia. Nuclei are often hyposegmented (pseudo-Pelger-Huёt anomaly). Apoptotic or pycnotic cells are not uncommon. Monocytes typically have a large cytoplasm loaded with heterogeneous and coalescing vacuoles. Platelets show large and giant shapes. The presence of erythrocyte fragments and schistocytes is especially evident in the forms of COVID-19 that are associated with thrombotic microangiopathies. Such atypia of blood cells reflects the generalized activation in severe COVID-19, which has been demonstrated with immunophenotypic, molecular, genetic, and functional methods. Neutrophils, in particular, are involved in the pathophysiology of hyperinflammation with cytokine storm, which characterizes the most unfavorable evolution.

Antibody-receptor bioengineering and its implications in designing bioelectronic devices

Antibodies play a crucial role in the defense mechanism countering pathogens or foreign antigens in eukaryotes. Its potential as an analytical and diagnostic tool has been exploited for over a century. It forms immunocomplexes with a specific antigen, which is the basis of immunoassays and aids in developing potent biosensors. Antibody-based sensors allow for the quick and accurate detection of various analytes. Though classical antibodies have prolonged been used as bioreceptors in biosensors fabrication due to their increased fragility, they have been engineered into more stable fragments with increased exposure of their antigen-binding sites in the recent era. In biosensing, the formats constructed by antibody engineering can enhance the signal since the resistance offered by a conventional antibody is much more than these fragments. Hence, signal amplification can be observed when antibody fragments are utilized as bioreceptors instead of full-length antibodies. We present the first systematic review on engineered antibodies as bioreceptors with the description of their engineering methods. The detection of various target analytes, including small molecules, macromolecules, and cells using antibody-based biosensors, has been discussed. A comparison of the classical polyclonal, monoclonal, and engineered antibodies as bioreceptors to construct highly accurate, sensitive, and specific sensors is also discussed.

Usefulness of laboratory parameters and chest CT in the early diagnosis of COVID-19

In the present study, the importance of laboratory parameters and CT findings in the early diagnosis of COVID-19 was investigated. To this end, 245 patients admitted between April 1st, and May 30th, 2020 with suspected COVID-19 were enrolled. The patients were divided into three groups according to chest CT findings and RT-PCR results. The non-COVID-19 group consisted of 71 patients with negative RT-PCR results and no chest CT findings. Ninety-five patients with positive RT-PCR results and negativechest CT findings were included in the COVID-19 group; 79 patients with positive RT-PCR results and chest CT findings consistent with COVID-19 manifestations were included in COVID-19 pneumonia group. Chest CT findings were positive in 45% of all COVID-19 patients. Patients with positive chest CT findings had mild (n=30), moderate (n=21) andor severe (n=28) lung involvement. In the COVID-19 group, CRP levels and the percentage of monocytes increased significantly. As disease progressed from mild to severe, CRP, LDH and ferritin levels gradually increased. In the ROC analysis, the area under the curve corresponding to the percentage value of monocytes (AUC=0.887) had a very good accuracy in predicting COVID-19 cases. The multinomial logistic regression analysis showed that CRP, LYM and % MONO were independent factors for COVID-19. Furthermore, the chest CT evaluation is a relevant tool in patients with clinical suspicion of COVID-19 pneumonia and negative RT-PCR results. In addition to decreased lymphocyte count, the increased percentage of monocytes may also guide the diagnosis.

What we know and still ignore on COVID-19 immune pathogenesis and a proposal based on the experience of allergic disorders

The coronavirus disease 2019 (COVID-19) pandemic started in March 2020 and caused over 5 million confirmed deaths worldwide as far August 2021. We have been recently overwhelmed by a wide literature on how the immune system recognizes severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and contributes to COVID-19 pathogenesis. Although originally considered a respiratory viral disease, COVID-19 is now recognized as a far more complex, multi-organ-, immuno-mediated-, and mostly heterogeneous disorder. Though efficient innate and adaptive immunity may control infection, when the patient fails to mount an adequate immune response at the start, or in advanced disease, a high innate-induced inflammation can lead to different clinical outcomes through heterogeneous compensatory mechanisms. The variability of viral load and persistence, the genetic alterations of virus-driven receptors/signaling pathways and the plasticity of innate and adaptive responses may all account for the extreme heterogeneity of pathogenesis and clinical patterns. As recently applied to some inflammatory disorders as asthma, rhinosinusitis with polyposis, and atopic dermatitis, herein we suggest defining different endo-types and the related phenotypes along COVID-19. Patients should be stratified for evolving symptoms and tightly monitored for surrogate biomarkers of innate and adaptive immunity. This would allow to preventively identify each endo-type (and its related phenotype) and to treat patients precisely with agents targeting pathogenic mechanisms.

Relationship Between Vitamin D Level and Platelet Parameters in Children With Viral Respiratory Infections

Apart from their classical roles, both platelets and vitamin D play important roles in inflammation and infectious diseases. This study evaluated the platelet response to viral respiratory tract infection in children aged 4-16 years, 32 with influenza, 27 with non-influenza viral infection tested by nasopharyngeal swab and 21 healthy children of the same age. Blood count, including platelet count (PLT), mean platelet volume (MPV) and other platelet indices, erythrocyte sedimentation rate (ESR), C-reactive protein (CRP) and vitamin D (vit D) levels were compared. The influenza group showed lower PLT and platelet mass (PLT^*MPV), and the non-influenza group showed significantly lower MPV, which was correlated with the vit D levels, but not CRP or ESR, and the value vit D^*MPV was significantly lower in this group. These results revealed that platelet activation in viral respiratory tract infections in children, as measured by MPV, is related to the vit D level, with differences between influenza and non-influenza infection.

CONCLUSIONS

Viral respiratory tract infection in children can diminish the platelet size most likely by suppressing the platelet activation. This response is associated with low levels of vit D. Whether the vit D status is associated with the virus-platelet immune/inflammatory process needs further investigation.

Comparison of Clinical Characteristics for Distinguishing COVID-19 From Influenza During the Early Stages in Guangdong, China

Background: To explore the differences in clinical manifestations and infection marker determination for early diagnosis of coronavirus disease-2019 (COVID-19) and influenza (A and B).

Methods: A hospital-based retrospective cohort study was designed. Patients with COVID-19 and inpatients with influenza at a sentinel surveillance hospital were recruited. Demographic data, medical history, laboratory findings, and radiographic characteristics were summarized and compared between the two groups. The chi-square test or Fisher's exact test was used for categorical variables, and Kruskal–Wallis H-test was used for continuous variables in each group. Receiver operating characteristic curve (ROC) was used to differentiate the intergroup characteristics. The Cox proportional hazards model was used to analyze the predisposing factors.

Results: About 23 patients with COVID-19 and 74 patients with influenza were included in this study. Patients with influenza exhibited more symptoms of cough and sputum production than COVID-19 (p < 0.05). CT showed that consolidation and pleural effusion were more common in influenza than COVID-19 (p < 0.05). Subgroup analysis showed that patients with influenza had high values of infection and coagulation function markers, but low values of blood routine and biochemical test markers than patients with COVID-19 (mild or moderate groups) (p < 0.05). In patients with COVID-19, the ROC analysis showed positive predictions of albumin and hematocrit, but negative predictions of C-reactive protein (CRP), procalcitonin (PCT), lactate dehydrogenase (LDH), hydroxybutyrate dehydrogenase (HBDH), and erythrocyte sedimentation rate. Multivariate analysis revealed that influenza might associate with risk of elevated CRP, PCT, and LDH, whereas COVID-19 might associated with high HBDH.

Conclusion: Patients with influenza had more obvious clinical symptoms but less common consolidation lesions and pleural effusion than those with COVID-19. These findings suggested that influenza likely presents with stronger inflammatory reactions than COVID-19, which provides some insights into the pathogenesis of these two contagious respiratory illnesses.

Complete blood count alterations in COVID-19 patients: A narrative review

Coronavirus disease 2019 (COVID-19) pandemic represents a scientific and social crisis. One of the main unmet needs for coronavirus disease 2019 is its unpredictable clinical course, which can rapidly change in an irreversible outcome. COVID-19 patients can be classified into mild, moderate, and severe. Several haematological parameters, such as platelets, white blood cell total count, lymphocytes, neutrophils, (together with neutrophil-lymphocyte and platelet-lymphocyte ratio), and haemoglobin were described to be associated with COVID-19 infection and severity. The purpose of these review is to describe the current state of the art about complete blood count alterations during COVID-19 infection, and to summarize the crucial role of some haematological parameters during the course of the disease. Decreased platelet, lymphocyte, haemoglobin, eosinophil, and basophil count, increased neutrophil count and neutrophil-lymphocyte and platelet-lymphocyte ratio have been associated with COVID-19 infection and a worse clinical outcome. Our study adds some novelty about the identification of effective biomarkers of progressive disease, and might be helpful for diagnosis, prevention of complications, and effective therapy.

Ruling Out Coronavirus Disease 2019 in Patients with Pneumonia: The Role of Blood Cell Count and Lung Ultrasound

Coronavirus disease 2019 (COVID-19) is characterized by a distinctive blood leucocyte pattern and B-lines on lung ultrasound (LUS) as marker of alveolar-interstitial syndrome. We aimed to evaluate the accuracy of blood leucocyte count alone or in combination with LUS for COVID-19 diagnosis. We retrospectively enrolled consecutive patients diagnosed with community acquired pneumonia (CAP) at hospital admission to derive and validate cutoff values for blood cell count that could be predictive of COVID-19 before confirmation by the nucleic acid amplification test (NAAT). Cutoff values, generated and confirmed in inception (41/115, positive/negative patients) and validation (100/180, positive/negative patients) cohorts, were ≤17 and ≤10 cells/mm³ for basophils and eosinophils, respectively. Basophils and/or eosinophils below cutoff were associated with sensitivity of 98% (95%CI, 94–100) and negative likelihood ratio of 0.04 (95%CI, 0.01–0.11). In a subgroup of 265 subjects, the sensitivity of B-line on LUS was 15% lower (p < 0.001) than that of basophils and/or eosinophils below cutoff. The combination of B-lines with basophils and eosinophils below cutoff was associated with a moderate increase of the positive likelihood ratio: 5.0 (95%CI, 3.2–7.7). In conclusion, basophil and eosinophil counts above the generated cutoff virtually rule out COVID-19 in patients with CAP. Our findings can help optimize patient triage pending the NAAT results.

Comparison of clinical and biochemical features of hospitalized COVID-19 and influenza pneumonia patients

Both severe acute respiratory syndrome coronavirus 2 and influenza viruses cause similar clinical presentations. It is essential to assess severely ill patients presenting with a viral syndrome for diagnostic and prognostic purposes. We aimed to compare clinical and biochemical features between pneumonia patients with coronavirus disease 2019 (COVID‐19) and H1N1. Sixty patients diagnosed with COVID‐19 pneumonia and 61 patients diagnosed with influenza pneumonia were hospitalized between October 2020–January 2021 and October 2017–December 2019, respectively. All the clinical data and laboratory results, chest computed tomography scans, intensive care unit admission, invasive mechanical ventilation, and outcomes were retrospectively evaluated. The median age was 65 (range 32–96) years for patients with a COVID‐19 diagnosis and 58 (range 18–83) years for patients with influenza (p = 0.002). The comorbidity index was significantly higher in patients with COVID‐19 (p = 0.010). Diabetes mellitus and hypertension were statistically significantly more common in patients with COVID‐19 (p = 0.019, p = 0.008, respectively). The distribution of severe disease and mortality was not significantly different among patients with COVID‐19 than influenza patients (p = 0.096, p = 0.049).). In comparison with inflammation markers; C‐reactive protein (CRP) levels were significantly higher in influenza patients than patients with COVID‐19 (p = 0.033). The presence of sputum was predictive for influenza (odds ratio [OR] 0.342 [95% confidence interval [CI], 2.1.130–0.899]). CRP and platelet were also predictive for COVID‐19 (OR 4.764 [95% CI, 1.003–1.012] and OR 0.991 [95% CI 0.984–0.998], respectively. We conclude that sputum symptoms by itself are much more detected in influenza patients. Besides that, lower CRP and higher PLT count would be discriminative for COVID‐19.

It is essential to distinguish two respiratory viral infections COVID‐19 and influenzae. We aimed to compare clinical and biochemical features between pneumonia patients with two diseases.While sputum symptoms by itself are much more detected in influenza patients, lower CRP and higher PLT count would be discriminative for COVID‐19.

Association between the peripheral blood eosinophil counts and COVID-19: A meta-analysis

BACKGROUND

The conclusions about the relationship between eosinophil counts and the severity of coronavirus disease 2019 (COVID-19) were controversial, so we updated the evidences and reassessed it.

METHODS

We searched the PubMed, Cochrane library, Excerpta Medica Database, and Web of Science to compare the eosinophil counts about non-severe disease group (mild pneumonia, moderate pneumonia, non-critical disease and recovery group) and severe disease group (severe pneumonia, critical pneumonia, critical disease and death group) in COVID-19.

RESULTS

A total of 1228 patients from 10 studies were included. Compared with non-severe group, severe group had strikingly lower average eosinophil counts (SMD 0.65, 95% confidence intervals [CI] 0.29-1.01; P < .001). The result of subgroup analysis of different countries showed SMD 0.66, 95% CI 0.26-1.06; P < .001. Another subgroup analysis between mild-moderate pneumonia versus severe-critical pneumonia showed SMD 0.69, 95% CI 0.25-1.13; P < .001, and no significant risk of publication bias (Begg test 0.063 and Egger test 0.057) in this subgroup. The heterogeneity was substantial, but the sensitivity analyses showed no significant change when individual study was excluded, which suggested the crediblity and stablity of our results.

CONCLUSIONS

The eosinophil counts had important value as an indicator of severity in patients with COVID-19.

PROSPERO REGISTRATION NUMBER

CRD42020205497.

A predictive paradigm for COVID-19 prognosis based on the longitudinal measure of biomarkers

Novel coronavirus disease 2019 (COVID-19) is an emerging, rapidly evolving crisis, and the ability to predict prognosis for individual COVID-19 patient is important for guiding treatment. Laboratory examinations were repeatedly measured during hospitalization for COVID-19 patients, which provide the possibility for the individualized early prediction of prognosis. However, previous studies mainly focused on risk prediction based on laboratory measurements at one time point, ignoring disease progression and changes of biomarkers over time. By using historical regression trees (HTREEs), a novel machine learning method, and joint modeling technique, we modeled the longitudinal trajectories of laboratory biomarkers and made dynamically predictions on individual prognosis for 1997 COVID-19 patients. In the discovery phase, based on 358 COVID-19 patients admitted between 10 January and 18 February 2020 from Tongji Hospital, HTREE model identified a set of important variables including 14 prognostic biomarkers. With the trajectories of those biomarkers through 5-day, 10-day and 15-day, the joint model had a good performance in discriminating the survived and deceased COVID-19 patients (mean AUCs of 88.81, 84.81 and 85.62% for the discovery set). The predictive model was successfully validated in two independent datasets (mean AUCs of 87.61, 87.55 and 87.03% for validation the first dataset including 112 patients, 94.97, 95.78 and 94.63% for the second validation dataset including 1527 patients, respectively). In conclusion, our study identified important biomarkers associated with the prognosis of COVID-19 patients, characterized the time-to-event process and obtained dynamic predictions at the individual level.

Distinctive clinical and laboratory features of COVID-19 and H1N1 influenza infections among hospitalized pediatric patients

BACKGROUND

It had been documented in many studies that pediatric coronavirus disease 2019 (COVID-19) is characterized by low infectivity rates, low mortalities, and benign disease course. On the other hand, influenza type A viruses are recognized to cause severe and fatal infections in children populations worldwide. This study is aimed to compare the clinical and laboratory characteristics of COVID-19 and H1N1 influenza infections.

METHODS

A retrospective study comprising 107 children hospitalized at Abha Maternity and Children Hospital, Southern region of Saudi Arabia, with laboratory-confirmed COVID-19 and H1N1 influenza infections was carried out. A complete follow-up for all patients from the hospital admission until discharge or death was made. The clinical data and laboratory parameters for these patients were collected from the medical records of the hospital.

RESULTS

Out of the total enrolled patients, 73 (68.2%) were diagnosed with COVID-19, and 34 (31.8%) were diagnosed with H1N1 influenza. The median age is 12 months for COVID-19 patients and 36 months for influenza patients. A relatively higher number of patients with influenza had a fever and respiratory symptoms than COVID-19 patients. In contrast, gastrointestinal symptoms were observed in a higher number of COVID-19 patients than in influenza patients. A statistically significant increase in white cell counts is noted in COVID-19 but not in influenza patients (P < 0.05). There are no obvious variations in the mean period of duration of hospitalization between COVID-19 and influenza patients. However, the total intensive care unit length of stay was longer for influenza compared to COVID-19 patients.

CONCLUSIONS

A considerable number of children infected with COVID-19 and H1N1 influenza were noted and reported in this study. There were no significant variations in the severity of the symptomatology and laboratory findings between the two groups of patients. Significant differences between these patients in some hospitalization factors and diagnosis upon admission also were not observed. However, more severe clinical manifestations and serious consequences were observed among pediatric patients hospitalized with influenza infections than among those with COVID-19.

Pneumonia Caused by Severe Acute Respiratory Syndrome Coronavirus 2 and Influenza Virus: A Multicenter Comparative Study

Background

Detailed differences in clinical information between severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pneumonia (CP), which is the main phenotype of SARS-CoV-2 disease, and influenza pneumonia (IP) are still unclear.

Methods

A prospective, multicenter cohort study was conducted by including patients with CP who were hospitalized between January and June 2020 and a retrospective cohort of patients with IP hospitalized from 2009 to 2020. We compared the clinical presentations and studied the prognostic factors of CP and IP.

Results

Compared with the IP group (n = 66), in the multivariate analysis, the CP group (n = 362) had a lower percentage of patients with underlying asthma or chronic obstructive pulmonary disease (P < .01), lower neutrophil-to-lymphocyte ratio (P < .01), lower systolic blood pressure (P < .01), higher diastolic blood pressure (P < .01), lower aspartate aminotransferase level (P < .05), higher serum sodium level (P < .05), and more frequent multilobar infiltrates (P < .05). The diagnostic scoring system based on these findings showed excellent differentiation between CP and IP (area under the receiver operating characteristic curve, 0.889). Moreover, the prognostic predictors were different between CP and IP.

Conclusions

Comprehensive differences between CP and IP were revealed, highlighting the need for early differentiation between these 2 pneumonias in clinical settings.

Performance of Diagnostic Model for Differentiating Between COVID-19 and Influenza: A 2-Center Retrospective Study

Background

COVID-19 and influenza share many similarities, such as mode of transmission and clinical symptoms. Failure to distinguish the 2 diseases may increase the risk of transmission. A fast and convenient differential diagnosis between COVID-19 and influenza has significant clinical value, especially for low- and middle-income countries with a shortage of nucleic acid detection kits. We aimed to establish a diagnostic model to differentiate COVID-19 and influenza based on clinical data.

Material/Methods

A total of 493 patients were enrolled in the study, including 282 with COVID-19 and 211 with influenza. All data were collected and reviewed retrospectively. The clinical and laboratory characteristics of all patients were analyzed and compared. We then randomly divided all patients into development sets and validation sets to establish a diagnostic model using multivariate logistic regression analysis. Finally, we validated the diagnostic model using the validation set.

Results

We preliminarily established a diagnostic model for differentiating COVID-19 from influenza that consisted of 5 variables: age, dry cough, fever, white cell count, and D-dimer. The model showed good performance for differential diagnosis.

Conclusions

This initial model including clinical features and laboratory indices effectively differentiated COVID-19 from influenza. Patients with a high score were at a high risk of having COVID-19, while patients with a low score were at a high risk of having influenza. This model could help clinicians quickly identify and isolate cases in the absence of nucleic acid tests, especially during the cocirculation of COVID-19 and influenza. Owing to the study’s retrospective nature, further prospective study is needed to validate the accuracy of the model.

A Comparative Systematic Review of COVID-19 and Influenza

Background: Both SARS-CoV-2 and influenza virus share similarities such as clinical features and outcome, laboratory, and radiological findings. Methods: Literature search was done using PubMed to find MEDLINE indexed articles relevant to this study. As of 25 November 2020, the search has been conducted by combining the MeSH words “COVID-19” and “Influenza”. Results: Eighteen articles were finally selected in adult patients. Comorbidities such as cardiovascular diseases, diabetes, and obesity were significantly higher in COVID-19 patients, while pulmonary diseases and immunocompromised conditions were significantly more common in influenza patients. The incidence rates of fever, vomiting, ocular and otorhinolaryngological symptoms were found to be significantly higher in influenza patients when compared with COVID-19 patients. However, neurologic symptoms and diarrhea were statistically more frequent in COVID-19 patients. The level of white cell count and procalcitonin was significantly higher in influenza patients, whereas thrombopenia and elevated transaminases were significantly more common in COVID-19 patients. Ground-grass opacities, interlobular septal thickening, and a peripheral distribution were more common in COVID-19 patients than in influenza patients where consolidations and linear opacities were described instead. COVID-19 patients were significantly more often transferred to intensive care unit with a higher rate of mortality. Conclusions: This study estimated differences of COVID-19 and influenza patients which can help clinicians during the co-circulation of the two viruses.

Circulating Platelet-Derived Extracellular Vesicles Are a Hallmark of Sars-Cov-2 Infection

Sars-Cov-2 infection causes fever and cough that may rapidly lead to acute respiratory distress syndrome (ARDS). Few biomarkers have been identified but, unfortunately, these are individually poorly specific, and novel biomarkers are needed to better predict patient outcome. The aim of this study was to evaluate the diagnostic performance of circulating platelets (PLT)-derived extracellular vesicles (EVs) as biomarkers for Sars-Cov-2 infection, by setting a rapid and reliable test on unmanipulated blood samples. PLT-EVs were quantified by flow cytometry on two independent cohorts of Sars-CoV-2+ (n = 69), Sars-Cov-2- (n = 62) hospitalized patients, and healthy controls. Diagnostic performance of PLT-EVs was evaluated by receiver operating characteristic (ROC) curve. PLT-EVs count were higher in Sars-Cov-2+ compared to Sars-Cov-2- patients or HC. ROC analysis of the combined cohorts showed an AUC = 0.79 and an optimal cut-off value of 1472 EVs/μL, with 75% sensitivity and 74% specificity. These data suggest that PLT-EVs might be an interesting biomarker deserving further investigations to test their predictive power.

Eosinophils and COVID-19: diagnosis, prognosis, and vaccination strategies

The unprecedented impact of the coronavirus disease 2019 (COVID-19) pandemic has resulted in global challenges to our health-care systems and our economic security. As such, there has been significant research into all aspects of the disease, including diagnostic biomarkers, associated risk factors, and strategies that might be used for its treatment and prevention. Toward this end, eosinopenia has been identified as one of many factors that might facilitate the diagnosis and prognosis of severe COVID-19. However, this finding is neither definitive nor pathognomonic for COVID-19. While eosinophil-associated conditions have been misdiagnosed as COVID-19 and others are among its reported complications, patients with pre-existing eosinophil-associated disorders (e.g., asthma, eosinophilic gastrointestinal disorders) do not appear to be at increased risk for severe disease; interestingly, several recent studies suggest that a diagnosis of asthma may be associated with some degree of protection. Finally, although vaccine-associated aberrant inflammatory responses, including eosinophil accumulation in the respiratory tract, were observed in preclinical immunization studies targeting the related SARS-CoV and MERS-CoV pathogens, no similar complications have been reported clinically in response to the widespread dissemination of either of the two encapsulated mRNA-based vaccines for COVID-19.

Distinguishing between COVID-19 and influenza during the early stages by measurement of peripheral blood parameters

Coronavirus disease 2019 (COVID-19) is caused by severe acute respiratory syndrome coronavirus 2 infection. This study aims to examine the changes in peripheral blood parameters during the early stages of COVID-19 and influenza. We analyzed the peripheral blood parameters of 169 COVID-19 patients and 131 influenza patients during the early-onset stage. Results from the patients with COVID-19 were compared with those from healthy controls and influenza patients. In addition, results from patients with common and severe COVID-19 were further compared. There were significant differences between COVID-19 and influenza patients in terms of age, white blood cell count, platelet count, percentage of neutrophils, percentage of lymphocytes, percentage of monocytes, percentage of eosinophils, percentage of basophils, neutrophil, count and monocyte count. Two parameters (monocyte count and percentage of basophils) were combined to clarify the diagnostic efficacy of COVID-19 and influenza and the area under the curve was found to be 0.772. Comparison of peripheral blood parameters from common COVID-19, severe COVID-19, and influenza patients revealed many differences during the early disease stages. The diagnostic formula developed by this study will be of benefit for physicians in the differentiation of COVID-19 and influenza.