Comparison of patients hospitalized with COVID-19, H7N9 and H1N1

Blood Features Associated with Viral Infection Severity: An Experience from COVID-19-Pandemic Patients Hospitalized in the Center of Iran, Yazd

Pandemics such as coronavirus disease 2019 (COVID-19) can manifest as systemic infections that affect multiple organs and show laboratory manifestations. We aimed to analyze laboratory findings to understand possible mechanisms of organ dysfunction and risk stratification of hospitalized patients in these epidemics. Methods. This retrospective study was conducted among patients admitted to COVID-19 referral treatment center, Shahid Sadoughi Hospital, Yazd, Iran, from April 21 to November 21, 2021. It was the fifth peak of COVID-19 in Iran, and Delta (VOC-21APR-02; B.1-617.2) was the dominant and most concerning strain. All cases were positive for COVID-19 by RT-PCR test. Lab information of included patients and association of sex, age, and outcome were analyzed, on admission. Results. A total of 466 COVID-19 patients were included in the study, the majority of whom were women (68.9%). The average age of hospitalized patients in male and female patients was 57.68 and 41.32 years, respectively (p < 0.01). During hospitalization, abnormality in hematological and biochemical parameters was significant and was associated with the outcome of death in patients. There was incidence of lymphopenia, neutrophilia, anemia, and thrombocytopenia. The changes in neutrophil/lymphocyte (N/L) and hematocrit/albumin (Het/Alb) ratio and potassium and calcium levels were significant. Conclusion. Based on these results, new biochemical and hematological parameters can be used to predict the spread of infection and the underlying molecular mechanism. Viral infection may spread through blood cells and the immune system.

Clinical Features of COVID-19 and Differentiation from Other Causes of CAP

Community-acquired pneumonia (CAP) is a significant cause of morbidity and mortality, one of the most common reasons for infection-related death worldwide. Causes of CAP include numerous viral, bacterial, and fungal pathogens, though frequently no specific organism is found. Beginning in 2019, the COVID-19 pandemic has caused incredible morbidity and mortality. COVID-19 has many features typical of CAP such as fever, respiratory distress, and cough, and can be difficult to distinguish from other types of CAP. Here, we highlight unique clinical features of COVID-19 pneumonia such as olfactory and gustatory dysfunction, lymphopenia, and distinct imaging appearance.

Antifungal Effect of Nanoparticles against COVID-19 Linked Black Fungus: A Perspective on Biomedical Applications

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a highly transmissible and pathogenic coronavirus that has caused a 'coronavirus disease 2019' (COVID-19) pandemic in multiple waves, which threatens human health and public safety. During this pandemic, some patients with COVID-19 acquired secondary infections, such as mucormycosis, also known as black fungus disease. Mucormycosis is a serious, acute, and deadly fungal infection caused by Mucorales-related fungal species, and it spreads rapidly. Hence, prompt diagnosis and treatment are necessary to avoid high mortality and morbidity rates. Major risk factors for this disease include uncontrolled diabetes mellitus and immunosuppression that can also facilitate increases in mucormycosis infections. The extensive use of steroids to prevent the worsening of COVID-19 can lead to black fungus infection. Generally, antifungal agents dedicated to medical applications must be biocompatible, non-toxic, easily soluble, efficient, and hypoallergenic. They should also provide long-term protection against fungal growth. COVID-19-related black fungus infection causes a severe increase in fatalities. Therefore, there is a strong need for the development of novel and efficient antimicrobial agents. Recently, nanoparticle-containing products available in the market have been used as antimicrobial agents to prevent bacterial growth, but little is known about their efficacy with respect to preventing fungal growth, especially black fungus. The present review focuses on the effect of various types of metal nanoparticles, specifically those containing silver, zinc oxide, gold, copper, titanium, magnetic, iron, and carbon, on the growth of various types of fungi. We particularly focused on how these nanoparticles can impact the growth of black fungus. We also discussed black fungus co-infection in the context of the global COVID-19 outbreak, and management and guidelines to help control COVID-19-associated black fungus infection. Finally, this review aimed to elucidate the relationship between COVID-19 and mucormycosis.

Comparison of acute respiratory distress syndrome in patients with COVID-19 and influenza A (H7N9) virus infection

OBJECTIVES

We aimed to compared the clinical features of acute respiratory distress syndrome (ARDS) induced by COVID-19 and H7N9 virus infections.

METHODS

Clinical data of 100 patients with COVID-19 and 46 patients with H7N9 were retrospectively analyzed.

RESULTS

Elevated inflammatory indices and coagulation disorders were more common in COVID-19-ARDS group than in the H7N9-ARDS group. The median interval from illness onset to ARDS development was shorter in H7N9-ARDS. The PaO₂/FiO₂ level was lower in H7N9-ARDS, whereas the Sepsis-related Organ Failure Assessment score was higher in COVID-19-ARDS. The proportion of patients with disseminated intravascular coagulation and liver injury in COVID-19-ARDS and H7N9-ARDS was 45.5% versus 3.1% and 28.8% versus 50%, respectively (P <0.05). The mean interval from illness onset to death was shorter in H7N9-ARDS. A total of 59.1% patients with H7N9-ARDS died of refractory hypoxemia compared with 28.9% with COVID-19-ARDS (P = 0.014). Patients with COVID-19-ARDS were more likely to die of septic shock and multiple organ dysfunction compared with H7N9-ARDS (71.2% vs 36.4%, P = 0.005).

CONCLUSION

Patients with H7N9 were more susceptible to develop severe ARDS and showed a more acute disease course. COVID-19-ARDS was associated with severe inflammatory response and coagulation dysfunction, whereas liver injury was more common in H7N9-ARDS. The main causes of death between patients with the two diseases were different.

Comparison of temporal evolution of computed tomography imaging features in COVID-19 and influenza infections in a multicenter cohort study

Purpose

To compare temporal evolution of imaging features of coronavirus disease 2019 (COVID-19) and influenza in computed tomography and evaluate their predictive value for distinction.

Methods

In this retrospective, multicenter study 179 CT examinations of 52 COVID-19 and 44 influenza critically ill patients were included. Lung involvement, main pattern (ground glass opacity, crazy paving, consolidation) and additional lung and chest findings were evaluated by two independent observers. Additional findings and clinical data were compared patient-wise. A decision tree analysis was performed to identify imaging features with predictive value in distinguishing both entities.

Results

In contrast to influenza patients, lung involvement remains high in COVID-19 patients > 14 days after the diagnosis. The predominant pattern in COVID-19 evolves from ground glass at the beginning to consolidation in later disease. In influenza there is more consolidation at the beginning and overall less ground glass opacity (p = 0.002). Decision tree analysis yielded the following: Earlier in disease course, pleural effusion is a typical feature of influenza (p = 0.007) whereas ground glass opacities indicate COVID-19 (p = 0.04). In later disease, particularly more lung involvement (p < 0.001), but also less pleural (p = 0.005) and pericardial (p = 0.003) effusion favor COVID-19 over influenza. Regardless of time point, less lung involvement (p < 0.001), tree-in-bud (p = 0.002) and pericardial effusion (p = 0.01) make influenza more likely than COVID-19.

Conclusions

This study identified differences in temporal evolution of imaging features between COVID-19 and influenza. These findings may help to distinguish both diseases in critically ill patients when laboratory findings are delayed or inconclusive.

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Decision tree analysis helps to distinguish COVID-19 and Influenza.

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Pleural effusion is a typical feature of influenza in early disease.

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Ground glass opacities indicate COVID-19 in early disease.

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Lung involvement remains high in COVID-19 patients > 14 days after the diagnosis.

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Pleural and pericardial effusion favor influenza over COVID-19 in later disease.

Impact of rhinovirus on hospitalization during the COVID-19 pandemic: a prospective cohort study

Background

Although the clinical course of the COVID-19 in adults has been extensively described, the impact of the co-detection of SARS-CoV-2 and rhinovirus on severity outcomes is not understood.

Objectives

This study aimed to compare the risk of hospitalization of outpatients with COVID-19 with and without the co-detection of rhinovirus in southern Brazil. Secondarily, such risk was also compared between all individuals with COVID-19 and those with single rhinovirus infection.

Study design

Outpatients (>18 years) with acute signs of cough, fever, or sore throat were prospectively enrolled at two emergency departments from May to September 2020. Sample collection was performed to detect SARS-CoV-2 and other 20 respiratory pathogens. Participants were followed for 28 days through telephone interviews.

Results

1,047 participants were screened and 1,044 were included. Of these, 4.9% were lost during follow-up, and 993/1,044 (95.1%) were included in severity-related analysis. Rhinovirus was the most prevalent pathogen (25.0%, 248/993), followed by SARS-CoV-2 (22.6%, 224/993), with coinfection of these two viruses occurring in 91/993 (9.2%) participants. The risk of COVID-19-related hospitalizations were not different between individuals with and without co-detection of rhinovirus (9.9% vs. 7.6%, respectively, P = 0.655). Conversely, subjects with COVID-19 had a higher hospitalization risk than single rhinovirus infection (8.3 vs 0.4%, respectively, P < 0.001).

Conclusions

The co-detection of SARS-CoV-2 and rhinovirus did not change the risk of hospitalizations in adults. Furthermore, COVID-19 was more severe than single rhinovirus infection.

Signs and symptoms to determine if a patient presenting in primary care or hospital outpatient settings has COVID-19

BACKGROUND

COVID-19 illness is highly variable, ranging from infection with no symptoms through to pneumonia and life-threatening consequences. Symptoms such as fever, cough, or loss of sense of smell (anosmia) or taste (ageusia), can help flag early on if the disease is present. Such information could be used either to rule out COVID-19 disease, or to identify people who need to go for COVID-19 diagnostic tests. This is the second update of this review, which was first published in 2020.

OBJECTIVES

To assess the diagnostic accuracy of signs and symptoms to determine if a person presenting in primary care or to hospital outpatient settings, such as the emergency department or dedicated COVID-19 clinics, has COVID-19.

SEARCH METHODS

We undertook electronic searches up to 10 June 2021 in the University of Bern living search database. In addition, we checked repositories of COVID-19 publications. We used artificial intelligence text analysis to conduct an initial classification of documents. We did not apply any language restrictions.

SELECTION CRITERIA

Studies were eligible if they included people with clinically suspected COVID-19, or recruited known cases with COVID-19 and also controls without COVID-19 from a single-gate cohort. Studies were eligible when they recruited people presenting to primary care or hospital outpatient settings. Studies that included people who contracted SARS-CoV-2 infection while admitted to hospital were not eligible. The minimum eligible sample size of studies was 10 participants. All signs and symptoms were eligible for this review, including individual signs and symptoms or combinations. We accepted a range of reference standards.

DATA COLLECTION AND ANALYSIS

Pairs of review authors independently selected all studies, at both title and abstract, and full-text stage. They resolved any disagreements by discussion with a third review author. Two review authors independently extracted data and assessed risk of bias using the QUADAS-2 checklist, and resolved disagreements by discussion with a third review author. Analyses were restricted to prospective studies only. We presented sensitivity and specificity in paired forest plots, in receiver operating characteristic (ROC) space and in dumbbell plots. We estimated summary parameters using a bivariate random-effects meta-analysis whenever five or more primary prospective studies were available, and whenever heterogeneity across studies was deemed acceptable.

MAIN RESULTS

We identified 90 studies; for this update we focused on the results of 42 prospective studies with 52,608 participants. Prevalence of COVID-19 disease varied from 3.7% to 60.6% with a median of 27.4%. Thirty-five studies were set in emergency departments or outpatient test centres (46,878 participants), three in primary care settings (1230 participants), two in a mixed population of in- and outpatients in a paediatric hospital setting (493 participants), and two overlapping studies in nursing homes (4007 participants). The studies did not clearly distinguish mild COVID-19 disease from COVID-19 pneumonia, so we present the results for both conditions together. Twelve studies had a high risk of bias for selection of participants because they used a high level of preselection to decide whether reverse transcription polymerase chain reaction (RT-PCR) testing was needed, or because they enrolled a non-consecutive sample, or because they excluded individuals while they were part of the study base. We rated 36 of the 42 studies as high risk of bias for the index tests because there was little or no detail on how, by whom and when, the symptoms were measured. For most studies, eligibility for testing was dependent on the local case definition and testing criteria that were in effect at the time of the study, meaning most people who were included in studies had already been referred to health services based on the symptoms that we are evaluating in this review. The applicability of the results of this review iteration improved in comparison with the previous reviews. This version has more studies of people presenting to ambulatory settings, which is where the majority of assessments for COVID-19 take place. Only three studies presented any data on children separately, and only one focused specifically on older adults. We found data on 96 symptoms or combinations of signs and symptoms. Evidence on individual signs as diagnostic tests was rarely reported, so this review reports mainly on the diagnostic value of symptoms. Results were highly variable across studies. Most had very low sensitivity and high specificity. RT-PCR was the most often used reference standard (40/42 studies). Only cough (11 studies) had a summary sensitivity above 50% (62.4%, 95% CI 50.6% to 72.9%)); its specificity was low (45.4%, 95% CI 33.5% to 57.9%)). Presence of fever had a sensitivity of 37.6% (95% CI 23.4% to 54.3%) and a specificity of 75.2% (95% CI 56.3% to 87.8%). The summary positive likelihood ratio of cough was 1.14 (95% CI 1.04 to 1.25) and that of fever 1.52 (95% CI 1.10 to 2.10). Sore throat had a summary positive likelihood ratio of 0.814 (95% CI 0.714 to 0.929), which means that its presence increases the probability of having an infectious disease other than COVID-19. Dyspnoea (12 studies) and fatigue (8 studies) had a sensitivity of 23.3% (95% CI 16.4% to 31.9%) and 40.2% (95% CI 19.4% to 65.1%) respectively. Their specificity was 75.7% (95% CI 65.2% to 83.9%) and 73.6% (95% CI 48.4% to 89.3%). The summary positive likelihood ratio of dyspnoea was 0.96 (95% CI 0.83 to 1.11) and that of fatigue 1.52 (95% CI 1.21 to 1.91), which means that the presence of fatigue slightly increases the probability of having COVID-19. Anosmia alone (7 studies), ageusia alone (5 studies), and anosmia or ageusia (6 studies) had summary sensitivities below 50% but summary specificities over 90%. Anosmia had a summary sensitivity of 26.4% (95% CI 13.8% to 44.6%) and a specificity of 94.2% (95% CI 90.6% to 96.5%). Ageusia had a summary sensitivity of 23.2% (95% CI 10.6% to 43.3%) and a specificity of 92.6% (95% CI 83.1% to 97.0%). Anosmia or ageusia had a summary sensitivity of 39.2% (95% CI 26.5% to 53.6%) and a specificity of 92.1% (95% CI 84.5% to 96.2%). The summary positive likelihood ratios of anosmia alone and anosmia or ageusia were 4.55 (95% CI 3.46 to 5.97) and 4.99 (95% CI 3.22 to 7.75) respectively, which is just below our arbitrary definition of a 'red flag', that is, a positive likelihood ratio of at least 5. The summary positive likelihood ratio of ageusia alone was 3.14 (95% CI 1.79 to 5.51). Twenty-four studies assessed combinations of different signs and symptoms, mostly combining olfactory symptoms. By combining symptoms with other information such as contact or travel history, age, gender, and a local recent case detection rate, some multivariable prediction scores reached a sensitivity as high as 90%.

AUTHORS' CONCLUSIONS

Most individual symptoms included in this review have poor diagnostic accuracy. Neither absence nor presence of symptoms are accurate enough to rule in or rule out the disease. The presence of anosmia or ageusia may be useful as a red flag for the presence of COVID-19. The presence of cough also supports further testing. There is currently no evidence to support further testing with PCR in any individuals presenting only with upper respiratory symptoms such as sore throat, coryza or rhinorrhoea. Combinations of symptoms with other readily available information such as contact or travel history, or the local recent case detection rate may prove more useful and should be further investigated in an unselected population presenting to primary care or hospital outpatient settings. The diagnostic accuracy of symptoms for COVID-19 is moderate to low and any testing strategy using symptoms as selection mechanism will result in both large numbers of missed cases and large numbers of people requiring testing. Which one of these is minimised, is determined by the goal of COVID-19 testing strategies, that is, controlling the epidemic by isolating every possible case versus identifying those with clinically important disease so that they can be monitored or treated to optimise their prognosis. The former will require a testing strategy that uses very few symptoms as entry criterion for testing, the latter could focus on more specific symptoms such as fever and anosmia.

Comparison of Hospitalized Coronavirus Disease 2019 and Influenza Patients Requiring Supplemental Oxygen in a Cohort Study: Clinical Impact and Resource Consumption

BACKGROUND

To compare clinical characteristics, outcomes, and resource consumption of patients with coronavirus disease 2019 (COVID-19) and seasonal influenza requiring supplemental oxygen.

METHODS

Retrospective cohort study conducted at a tertiary-care hospital. Patients admitted because of seasonal influenza between 2017 and 2019, or with COVID-19 between March and May 2020 requiring supplemental oxygen were compared. Primary outcome: 30-day mortality. Secondary outcomes: 90-day mortality and hospitalization costs. Attempted sample size to detect an 11% difference in mortality was 187 patients per group.

RESULTS

COVID-19 cases were younger (median years of age, 67; interquartile range [IQR] 54-78 vs 76 [IQR 64-83]; P < .001) and more frequently overweight, whereas influenza cases had more hypertension, immunosuppression, and chronic heart, respiratory, and renal disease. Compared with influenza, COVID-19 cases had more pneumonia (98% vs 60%, <.001), higher Modified Early Warning Score (MEWS) and CURB-65 (confusion, blood urea nitrogen, respiratory rate, systolic blood pressure, and age >65 years) scores and were more likely to show worse progression on the World Health Organization ordinal scale (33% vs 4%; P < .001). The 30-day mortality rate was higher for COVID-19 than for influenza: 15% vs 5% (P = .001). The median age of nonsurviving cases was 81 (IQR 74-88) and 77.5 (IQR 65-84) (P = .385), respectively. COVID-19 was independently associated with 30-day (hazard ratio [HR], 4.6; 95% confidence interval [CI], 2-10.4) and 90-day (HR, 5.2; 95% CI, 2.4-11.4) mortality. Sensitivity and subgroup analyses, including a subgroup considering only patients with pneumonia, did not show different trends. Regarding resource consumption, COVID-19 patients had longer hospital stays and higher critical care, pharmacy, and complementary test costs.

CONCLUSIONS

Although influenza patients were older and had more comorbidities, COVID-19 cases requiring supplemental oxygen on admission had worse clinical and economic outcomes.

Comparison of patient characteristics and in-hospital mortality between patients with COVID-19 in 2020 and those with influenza in 2017-2020: a multicenter, retrospective cohort study in Japan

Background

COVID-19 has worse mortality than influenza in American and European studies, but evidence from the Western Pacific region is scarce.

Methods

Using a large-scale multicenter inpatient claims data in Japan, we identified individuals hospitalised with COVID-19 in 2020 or influenza in 2017–2020. We compared patient characteristics, supportive care, and in-hospital mortality, with multivariable logistic regression analyses for in-hospital mortality overall, by age group, and among patients with mechanical ventilation.

Findings

We identified 16,790 COVID-19 patients and 27,870 influenza patients, with the different age distribution (peak at 70–89 years in COVID-19 vs. bimodal peaks at 0–9 and 80–89 years in influenza). On admission, the use of mechanical ventilation was similar in both groups (1·4% vs. 1·4%) but higher in the COVID-19 group (3·3% vs. 2·5%; p<0·0001) during the entire hospitalisation. The crude in-hospital mortality was 5·1% (856/16,790) for COVID-19 and 2·8% (791/27,870) for influenza. Adjusted for potential confounders, the in-hospital mortality was higher for COVID-19 than for influenza (adjusted odds ratio [aOR] 1·83, 95% confidence interval [CI] 1·64–2·04). In age-stratified analyses, the aOR (95%CI) were 0·78 (0·56–1·08) and 2·05 (1·83–2·30) in patients aged 20–69 years and ≥70 years, respectively (p-for-interaction<0·0001). Among patients with mechanical ventilation, the aOR was 0·79 (0·59–1·05).

Interpretation

Patients hospitalised with COVID-19 in Japan were more likely to die than those with influenza. However, this was mainly driven by findings in older people, and there was no difference once mechanical ventilation was started.

Funding

Ministry of Health, Labour and Welfare of Japan (21AA2007).

Abnormal Airway Mucus Secretion Induced by Virus Infection

The airway mucus barrier is a primary defensive layer at the airway surface. Mucins are the major structural components of airway mucus that protect the respiratory tract. Respiratory viruses invade human airways and often induce abnormal mucin overproduction and airway mucus secretion, leading to airway obstruction and disease. The mechanism underlying the virus-induced abnormal airway mucus secretion has not been fully studied so far. Understanding the mechanisms by which viruses induce airway mucus hypersecretion may open new avenues to treatment. In this article, we elaborate the clinical and experimental evidence that respiratory viruses cause abnormal airway mucus secretion, review the underlying mechanisms, and also discuss the current research advance as well as potential strategies to treat the abnormal airway mucus secretion caused by SARS-CoV-2.

Through Their Eyes: Health Care Worker Compliance With Personal Protective Equipment During the COVID-19 Pandemic

BACKGROUND

Personal protective equipment (PPE) plays a critical role in protecting health care workers (HCWs). During the coronavirus disease-2019 (COVID-19) pandemic, shortages of PPE supplies drastically changed the way PPE was obtained and used by HCWs.

PURPOSE

The objective was to investigate the impact of the COVID-19 pandemic and patient isolation type on PPE compliance.

METHODS

This investigation was a survey of HCWs at a level 1 trauma teaching hospital regarding PPE compliance patterns prior to and during the COVID-19 pandemic.

RESULTS

HCWs reported an increase in PPE compliance during the COVID-19 pandemic. Nearly half (48.6%) of respondents reported that isolation type impacted the decision to wear PPE, of which most were likely to forgo PPE with contact precautions.

CONCLUSIONS

HCWs identified multiple barriers to compliance. The underutilization of PPE with contact precautions suggests that the risk of exposure is interpreted as low, and this could be a future target of education.

Triage Modeling for Differential Diagnosis Between COVID-19 and Human Influenza A Pneumonia: Classification and Regression Tree Analysis

Background: The coronavirus disease 2019 (COVID-19) pandemic has lasted much longer than an influenza season, but the main signs, symptoms, and some imaging findings are similar in COVID-19 and influenza patients. The aim of the current study was to construct an accurate and robust model for initial screening and differential diagnosis of COVID-19 and influenza A.

Methods: All patients in the study were diagnosed at Fuyang No. 2 People's Hospital, and they included 151 with COVID-19 and 155 with influenza A. The patients were randomly assigned to training set or a testing set at a 4:1 ratio. Predictor variables were selected based on importance, assessed by random forest algorithms, and analyzed to develop classification and regression tree models.

Results: In the optimal model A, the best single predictor of COVID-19 patients was a normal or high level of low-density lipoprotein cholesterol, followed by low level of creatine kinase, then the presence of <3 respiratory symptoms, then a highest temperature on the first day of admission <38°C. In the suboptimal model B, the best single predictor of COVID-19 was a low eosinophil count, then a normal monocyte ratio, then a normal hematocrit value, then a highest temperature on the first day of admission of <37°C, then a complete lack of respiratory symptoms.

Conclusions: The two models provide clinicians with a rapid triage tool. The optimal model can be used to developed countries/regions and major hospitals, and the suboptimal model can be used in underdeveloped regions and small hospitals.

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.

Impact of both socioeconomic level and occupation on antibody prevalence to SARS-CoV-2 in an Egyptian cohort: The first episode

We studied the impact of socioeconomic level on the anti-SARS-CoV-2-antibodies prevalence in an Egyptian cohort. The low socioeconomic standard group (LSS) included 51 humans, 30 females (F) and 21 males (M). The high socioeconomic standard group (HSS) included 55 subjects, 24 F and 31 M. Of the 30 LSSF, 6 were immunoglobulin M (IgM), 21 immunoglobulin G (IgG), and 6 double positive. Of the 21 LSSM, 5 were IgM, 12 IgG, and 5 double positive. Of the 24 HSSF, 6 were IgM, 11 IgG, and 5 double positive. Of the 31 HSSM, 6 were IgM, 14 IgG, and 4 double positive. Of the 51 LSS humans, 26 were symptomatic (S) and 25 asymptomatic (AS). Of the 26 S, 20 were IgG and 8 IgM/IgG double positive. Of the 25 AS, 13 were IgG and 3 IgM/IgG double positive. Of the 55 HSS humans, 38 were S and 17 AS. Of the 38S, 24 were IgG and 11 IgM positive of whom, 9 were double positive. Of the 17 AS, one was IgG and one IgM positive. The IgM prevalence was higher among the HSS humans. The IgG prevalence was significantly higher among the LSS humans. In the two different socioeconomic standards, the prevalence of either IgM or IgG was higher among F. An inverse correlation was observed between age and the anti-SARS-CoV-2-antibodies prevalence except for LSSF-IgG and LSSM-IgM. In conclusion, socioeconomic standard, gender, and age impact humoral responses to SARS-CoV-2 with a clear heterogeneity in individualized responses to the infection in terms of symptoms.

Efficacy of the combination of modern medicine and traditional Chinese medicine in pulmonary fibrosis arising as a sequelae in convalescent COVID-19 patients: a randomized multicenter trial

Background

The coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has led to a significant number of mortalities worldwide. COVID-19 poses a serious threat to human life. The clinical manifestations of COVID-19 are diverse and severe and 20% of infected patients are reported to be in a critical condition. A loss in lung function and pulmonary fibrosis are the main manifestations of patients with the severe form of the disease. The lung function is affected, even after recovery, thereby greatly affecting the psychology and well-being of patients, and significantly reducing their quality of life.

Methods

Participants must meet the following simultaneous inclusion criteria: over 18 years of age, should have recovered from severe or critical COVID-19 cases, should exhibit pulmonary fibrosis after recovery, and should exhibit Qi-Yin deficiency syndrome as indicated in the system of traditional Chinese medicine (TCM). The eligible candidates will be randomized into treatment or control groups. The treatment group will receive modern medicine (pirfenidone) plus TCM whereas the control group will be administered modern medicine plus TCM placebo. The lung function index will be continuously surveyed and recorded. By comparing the treatment effect between the two groups, the study intend to explore whether TCM can improve the effectiveness of modern medicine in patients with pulmonary fibrosis arising as a sequelae after SARS-CoV-2 infection.

Discussion

Pulmonary fibrosis is one of fatal sequelae for some severe or critical COVID-19 cases, some studies reveal that pirfenidone lead to a delay in the decline of forced expiratory vital capacity, thereby reducing the mortality partly. Additionally, although TCM has been proven to be efficacious in treating pulmonary fibrosis, its role in treating pulmonary fibrosis related COVID-19 has not been explored. Hence, a multicenter, parallel-group, randomized controlled, interventional, prospective clinical trial has been designed and will be conducted to determine if a new comprehensive treatment for pulmonary fibrosis related to COVID-19 is feasible and if it can improve the quality of life of patients.

Trial registration: This multicenter, parallel-group, randomized controlled, interventional, prospective trial was registered at the Chinese Clinical Trial Registry (ChiCTR2000033284) on 26th May 2020 (prospective registered).