Clinical features of COVID-19 and influenza: a comparative study on Nord Franche-Comte cluster

A syndromic diagnostic assay on a macrochannel-to-digital microfluidic platform for automatic identification of multiple respiratory pathogens

The worldwide COVID-19 pandemic has changed people's lives and the diagnostic landscape. The nucleic acid amplification test (NAT) as the gold standard for SARS-CoV-2 detection has been applied in containing its transmission. However, there remains a lack of an affordable on-site detection system at resource-limited areas. In this study, a low cost "sample-in-answer-out" system incorporating nucleic acid extraction, purification, and amplification was developed on a single macrochannel-to-digital microfluidic chip. The macrochannel fluidic subsystem worked as a world-to-chip interface receiving 500-1000 μL raw samples, which then underwent bead-based extraction and purification processes before being delivered to DMF. Electrodes actuate an eluent dispensed to eight independent droplets for reverse transcription quantitative polymerase chain reaction (RT-qPCR). By reading with 4 florescence channels, the system can accommodate a maximum of 32 detection targets. To evaluate the proposed platform, a comprehensive assessment was conducted on the microfluidic chip as well as its functional components (i.e., extraction and amplification). The platform demonstrated a superior performance. In particular, using clinical specimens, the chip targeting SARS-CoV-2 and Flu A/B exhibited 100% agreement with off-chip diagnoses. Furthermore, the fabrication of chips is ready for scaled-up manufacturing and they are cost-effective for disposable use since they are assembled using a printed circuit board (PCB) and prefabricated blocks. Overall, the macrochannel-to-digital microfluidic platform coincides with the requirements of point-of-care testing (POCT) because of its advantages: low-cost, ease of use, comparable sensitivity and specificity, and availability for mass production.

Network-based integrative multi-omics approach reveals biosignatures specific to COVID-19 disease phases

Background

COVID-19 disease is characterized by a spectrum of disease phases (mild, moderate, and severe). Each disease phase is marked by changes in omics profiles with corresponding changes in the expression of features (biosignatures). However, integrative analysis of multiple omics data from different experiments across studies to investigate biosignatures at various disease phases is limited. Exploring an integrative multi-omics profile analysis through a network approach could be used to determine biosignatures associated with specific disease phases and enable the examination of the relationships between the biosignatures.

Aim

To identify and characterize biosignatures underlying various COVID-19 disease phases in an integrative multi-omics data analysis.

Method

We leveraged a multi-omics network-based approach to integrate transcriptomics, metabolomics, proteomics, and lipidomics data. The World Health Organization Ordinal Scale WHO Ordinal Scale was used as a disease severity reference to harmonize COVID-19 patient metadata across two studies with independent data. A unified COVID-19 knowledge graph was constructed by assembling a disease-specific interactome from the literature and databases. Disease-state specific omics-graphs were constructed by integrating multi-omics data with the unified COVID-19 knowledge graph. We expanded on the network layers of multiXrank, a random walk with restart on multilayer network algorithm, to explore disease state omics-specific graphs and perform enrichment analysis.

Results

Network analysis revealed the biosignatures involved in inducing chemokines and inflammatory responses as hubs in the severe and moderate disease phases. We observed distinct biosignatures between severe and moderate disease phases as compared to mild-moderate and mild-severe disease phases. Mild COVID-19 cases were characterized by a unique biosignature comprising C-C Motif Chemokine Ligand 4 (CCL4), and Interferon Regulatory Factor 1 (IRF1). Hepatocyte Growth Factor (HGF), Matrix Metallopeptidase 12 (MMP12), Interleukin 10 (IL10), Nuclear Factor Kappa B Subunit 1 (NFKB1), and suberoylcarnitine form hubs in the omics network that characterizes the moderate disease state. The severe cases were marked by biosignatures such as Signal Transducer and Activator of Transcription 1 (STAT1), Superoxide Dismutase 2 (SOD2), HGF, taurine, lysophosphatidylcholine, diacylglycerol, triglycerides, and sphingomyelin that characterize the disease state.

Conclusion

This study identified both biosignatures of different omics types enriched in disease-related pathways and their associated interactions (such as protein-protein, protein-transcript, protein-metabolite, transcript-metabolite, and lipid-lipid interactions) that are unique to mild, moderate, and severe COVID-19 disease states. These biosignatures include molecular features that underlie the observed clinical heterogeneity of COVID-19 and emphasize the need for disease-phase-specific treatment strategies. The approach implemented here can be used to find associations between transcripts, proteins, lipids, and metabolites in other diseases.

Evaluating an extraction-free sample preparation method for multiplex detection of SARS-Cov-2, influenza A/B, and RSV with implementation on a microfluidic chip

Following the relaxation of COVID-19 restrictions, other respiratory viruses such as influenza and respiratory syncytial virus (RSV), whose transmission were decreased due to COVID-19 precautions, are rising again. Because of similar clinical features and reported co-infections, multiplex detection of SARS-CoV-2, influenza A/B, and RSV is required to use specific treatments. This study assessed an extraction-free sample preparation (heat treatment at 95°C for 3 minutes) for multiplex detection using rRT-PCR. Despite an observed Ct-delay (∆Ct) averageing 1.26 compared to the standard method, an acceptable total sensitivity of 92 % and a negative predictive value (NPV) of 96 % were obtained. Moreover, Implementation on a microfluidic chip demonstrated efficiency, maintaining an excellent correlation (R2=0.983) with the standard method. Combining this extraction-free procedure with rRT-PCR on a microfluidic chip seems promising, because it simplifies the design and reduces the cost and complexity of the integrated assay for multiplex detection of SARS-CoV-2, influenza A/B, and RSV.

Comparative Analysis of the Clinical Presentation of Individuals Who Test Positive or Negative for SARS-CoV-2: Results from a Test Street Study

The common cold, the flu, and the 2019 coronavirus disease (COVID-19) have many symptoms in common. As such, without testing for severe-acute-respiratory-syndrome-related coronavirus 2 (SARS-CoV-2), it is difficult to conclude whether or not one is infected with SARS-CoV-2. The aim of the current study was to compare the presence and severity of COVID-19-related symptoms among those who tested positive or negative for the beta variant of SARS-CoV-2 (B.1.351) and identify the clinical presentation with the greatest likelihood of testing positive for SARS-CoV-2. n = 925 individuals that were tested for SARS-CoV-2 at Dutch mass testing sites (i.e., test streets) were invited to complete a short online survey. The presence and severity of 17 COVID-19-related symptoms were assessed. In addition, mood, health correlates, and quality of life were assessed for the week before the test. Of the sample, n = 88 tested positive and n = 837 tested negative for SARS-CoV-2. Individuals who tested positive for SARS-CoV-2 reported experiencing a significantly greater number, as well as greater overall symptom severity, compared to individuals who tested negative for SARS-CoV-2. A binary logistic regression analysis revealed that increased severity levels of congestion, coughing, shivering, or loss of smell were associated with an increase in the odds of testing positive for SARS-CoV-2, whereas an increase in the severity levels of runny nose, sore throat, or fatigue were associated with an increase in the odds of testing negative for SARS-CoV-2. No significant differences in mood or health correlates were found between those who tested positive or negative for SARS-CoV-2, except for a significantly higher stress score among those who tested negative for SARS-CoV-2. In conclusion, individuals that tested positive for SARS-CoV-2 experienced a significantly greater number and more severe COVID-19-related symptoms compared to those who tested negative for SARS-CoV-2. Experiencing shivering and loss of smell may be the best indicators for increased likelihood of testing positive for SARS-CoV-2.

Comparison of the incidence of smell and taste disorders between influenza and COVID-19

OBJECTIVE

Smell and taste disorders among patients with COVID-19 has become increasingly reported in the literature, however the prevalence varies. Post-infectious respiratory dysfunction has also been linked to influenza. In this study, we aimed to compare the rates of smell and taste disorders between COVID-19 and Influenza in unvaccinated patients.

STUDY DESIGN

Retrospective cohort study.

SETTING

TriNetX research network.

METHODS

Two queries were made on 7/1/2023 to include Influenza without a diagnosis of COVID-19 and a COVID-19 without a diagnosis of Influenza. The queries included patients from January 1 to December 31, 2022 from 102 Healthcare Organizations. The resultant population of patients with ICD-10 codes for COVID-19 and Influenza were matched using demographic characteristics to evaluate the risk of smell disorders.

RESULTS

The overall 3-month incidence of smell and taste disorders was 0.73 % in the COVID-19 population and 0.1 % in the influenza population. The 3-month matched risk ratios were 11.1 [95 % CI (8.8,13.8)]; p < 0.001) times higher for disorders of the smell and taste secondary to COVID-19 compared to influenza.

CONCLUSIONS

Disorders of the smell and taste are more common among patients with COVID-19 compared to patients with Influenza. Beyond smell loss, patients experience additional nasal and sinus-related rhinological symptoms, pointing to COVID-19's and influenza's wider impact on overall rhinological health. We believe that due to the transient nature of these disorders, they might go underreported.

Perturbations in inflammatory pathways are associated with shortness of breath profiles in oncology patients receiving chemotherapy

PURPOSE

One plausible mechanistic hypothesis is the potential contribution of inflammatory mechanisms to shortness of breath. This study was aimed to evaluate for associations between the occurrence of shortness of breath and perturbations in inflammatory pathways.

METHODS

Patients with cancer reported the occurrence of shortness of breath six times over two cycles of chemotherapy. Latent class analysis was used to identify subgroups of patients with distinct shortness of breath occurrence profiles (i.e., none (70.5%), decreasing (8.2%), increasing (7.8%), high (13.5%)). Using an extreme phenotype approach, whole transcriptome differential gene expression and pathway impact analyses were performed to evaluate for perturbed signaling pathways associated with shortness of breath between the none and high classes. Two independent samples (RNA-sequencing (n = 293) and microarray (n = 295) methodologies) were evaluated. Fisher's combined probability method was used to combine these results to obtain a global test of the null hypothesis. In addition, an unweighted knowledge network was created using the specific pathway maps to evaluate for interconnections among these pathways.

RESULTS

Twenty-nine Kyoto Encyclopedia of Genes and Genomes inflammatory signaling pathways were perturbed. The mitogen-activated protein kinase signaling pathway node had the highest closeness, betweenness, and degree scores. In addition, five common respiratory disease-related pathways, that may share mechanisms with cancer-related shortness of breath, were perturbed.

CONCLUSIONS

Findings provide preliminary support for the hypothesis that inflammation contribute to the occurrence of shortness of breath in patients with cancer. In addition, the mechanisms that underlie shortness of breath in oncology patients may be similar to other respiratory diseases.

Comparative Clinical Assessment and Risk Stratification of COVID-19 and Influenza Infections in Adults and Children: A Comprehensive Systematic Review and Meta-Analysis

Objective

This study aimed to compare the clinical risks and outcomes of COVID-19 and influenza.

Methods

The search for relevant articles was conducted using both a database search method and a manual search, which involved searching through the reference lists of articles related to the topic for additional studies. The Quality assessment was carried out using the Newcastle Ottawa tool, and the data analysis was conducted using the Review Manager Software (RevMan 5.4.1).

Results

The meta-analysis results indicated that COVID-19 patients had similar lengths of hospital stays (SMD: -0.25; 95% CI: -0.60-0.11; p=0.17). However, COVID-19 patients had significantly higher mortality rates (RR: 0.28; 95% CI: 0.21-0.37; p<0.0001), in-hospital complications (RR: 0.57; 95% CI: 0.50-0.65; p<0.00001), intensive care unit (ICU) admissions (OR: 0.48; 95% CI: 0.37-0.61; p<0.00001), length of ICU stay (SMD: -0.45; 95% CI: -0.83-0.06; p=0.02), and mechanical ventilation use (OR: 0.36; 95% CI: 0.28-0.46; p<0.00001).

Conclusion

The findings suggested that COVID-19 was more severe than influenza. Therefore, "flu-like" symptoms should not be dismissed without a clear diagnosis, especially during the winter when influenza is more prevalent.

Comparing COVID-19 and influenza: Epidemiology, clinical characteristics, outcomes and mortality in the ICU

RATIONALE

Several authors have compared COVID-19 infection with influenza in the ICU.

OBJECTIVE

This study aimed to compare the baseline clinical profiles, care procedures, and mortality outcomes of patients admitted to the intensive care unit, categorized by infection status (Influenza vs. COVID-19).

METHODS

Retrospective observational study. Data were extracted from the Toulouse University Hospital from March 2014 to March 2021. To compare survival curves, we plotted the survival at Day-90 using the Kaplan-Meier curve and conducted a log-rank test. Additionally, we performed propensity score matching to adjust for confounding factors between the COVID-19 and influenza groups. Furthermore, we use the CART model for multivariate analysis.

RESULTS

The study included 363 patients admitted to the ICU due to severe viral pneumonia: 152 patients (41.9 %) with influenza and 211 patients (58.1 %) with COVID-19. COVID-19 patients exhibited a higher prevalence of cardiovascular risk factors, whereas influenza patients had significantly higher severity scores (SOFA: 10 [6-12] vs. 6 [3-9], p<0.01 and SAPS II: 51 [35-67] vs. 37 [29-50], p<0.001). Overall mortality rates were comparable between the two groups (27.6 % (n = 42) in the influenza group vs. 21.8 % (n = 46) in the COVID-19 group, p=NS). Mechanical ventilation was more commonly employed in the influenza group (76.3 % (n = 116) vs. 59.7 % (n = 126), p<0.001); however, COVID-19 patients required longer durations of mechanical ventilation (18 [9-29] days vs. 13 [5-24] days, p<0.006) and longer hospital stays (23 [13-34] days vs. 18.5 [9-34.5] days, p = 0.009). The CART analysis revealed that the use of extra renal replacement therapy was the most influential prognostic factor in the influenza group, while the PaO2/FiO2-PEEP ratio played a significant role in the COVID-19 group.

CONCLUSIONS

Despite differences in clinical presentation and prognostic factors, the mortality rates at 90 days, after adjusting for confounding factors, were similar between COVID-19 and influenza patients.

Comparison of the clinical features and outcomes of severe seasonal influenza and COVID-19 patients in Tunisia between 2021 and 2022

Background

We compared patients diagnosed at a SARI (severe acute respiratory infections) surveillance site with COVID-19 and those with seasonal influenza to investigate the clinical differences, common features, and outcomes.

Methods

We conducted a descriptive, retrospective study in the Medical Intensive Care Unit (ICU) at Abderrahman Mami Hospital between September 2021 and April 2022. Demographic, clinical, and biological data as well as outcomes were recorded for all patients.

Results

Among 223 SARI patients, 83 were confirmed COVID-19, and 22 were influenza positive. The distribution according to gender was similar; but patients with influenza were younger than those suffering from COVID-19(mean age 60.36 SD 17.28 vs. 61.88 SD 17.91; P = 0.601). In terms of underlying chronic diseases, the frequency was 84.3% in the COVID-19 group and 72.7% in the influenza group. COVID-19 patients had a longer duration of hospitalization (mean [SD], 9.51 days [8.47 days] vs. 7.33 days [8.82 days]; P = 0.003), and a more frequent need for invasive ventilation (80 [97.4%] vs. 20 [92.3]). Case fatality was also higher among this group compared to the latter (39 [47%] vs. 6 [27.3%], P = 0.01).

Conclusion

This exploratory study suggests higher severity of COVID-19 compared to seasonal influenza among SARI hospitalized patients even during the Omicron wave. Further research on higher sample sizes is required to confirm this conclusion.

An early warning precision public health approach for assessing COVID-19 vulnerability in the UK: the Moore-Hill Vulnerability Index (MHVI)

BACKGROUND

Most COVID-19 vulnerability indices rely on measures that are biased by rates of exposure or are retrospective like mortality rates that offer little opportunity for intervention. The Moore-Hill Vulnerability Index (MHVI) is a precision public health early warning alternative to traditional infection fatality rates that presents avenues for mortality prevention.

METHODS

We produced an infection-severity vulnerability index by calculating the proportion of all recorded positive cases that were severe and attended by ambulances at small area scale for the East Midlands of the UK between May 2020 and April 2022. We produced maps identifying regions with high and low vulnerability, investigated the accuracy of the index over shorter and longer time periods, and explored the utility of the MHVI compared to other common proxy measures and indices. Analysis included exploring the correlation between our novel index and the Index of Multiple Deprivation (IMD).

RESULTS

The MHVI captures geospatial dynamics that single metrics alone often overlook, including the compound health challenges associated with disadvantaged and declining coastal towns inhabited by communities with post-industrial health legacies. A moderate negative correlation between MHVI and IMD reflects spatial analysis which suggests that high vulnerability occurs in affluent rural as well as deprived coastal and urban communities. Further, the MHVI estimates of severity rates are comparable to infection fatality rates for COVID-19.

CONCLUSIONS

The MHVI identifies regions with known high rates of poor health outcomes prior to the pandemic that case rates or mortality rates alone fail to identify. Pre-hospital early warning measures could be utilised to prevent mortality during a novel pandemic.

A Comparison of the Epidemiological Characteristics Between Influenza and COVID-19 Patients: A Retrospective, Observational Cohort Study

Background and objective It is crucial to make early differentiation between coronavirus disease 2019 (COVID-19) and seasonal influenza infections at the time of a patient's presentation to the emergency department (ED). In light of this, this study aimed to identify key epidemiological, initial laboratory, and radiological differences that would enable early recognition during co-circulation. Methods This was a retrospective, observational cohort study. All adult patients presenting to our ED at the Watford General Hospital, UK, with a laboratory-confirmed diagnosis of COVID-19 (2019/20) or influenza (2018/19) infection were included in this study. Demographic, laboratory, and radiological data were collected. Binary logistic regression was employed to determine features associated with COVID-19 infection rather than influenza. Results Chest radiographs suggestive of viral pneumonitis and older age (≥80 years) were associated with increased odds of having COVID-19 [odds ratio (OR): 47.00, 95% confidence interval (CI): 21.63-102.13 and OR: 64.85, 95% CI: 19.96-210.69 respectively]. Low eosinophils (<0.02 x 109/L) were found to increase the odds of COVID-19 (OR: 2.12, 95% CI: 1.44-3.10, p<0.001). Conclusions Gaining awareness about the epidemiological, biological, and radiologic presentation of influenza-like illness can be useful for clinicians in ED to differentiate between COVID-19 and influenza. This study showed that older age, eosinopenia, and radiographic evidence of viral pneumonitis significantly increase the odds of having COVID-19 compared to influenza. Further research is needed to determine if these findings are affected by acquired or natural immunity.

COVID-19 and H1N1 Influenza: Are They 2 Sides of the Same Coin?

Background

Swine flu (H1N1) and Coronavirus diseases (COVID-19) have been compared in the past few months. Both pandemics sparked a worldwide major panic. Although both have some common symptoms and diagnoses, they are quite different in many aspects. The current study aimed to investigate the differences in clinical and viral behaviors between H1N1 Influenza and COVID-19 pneumonia.

Methods

This was a retrospective study of adult patients hospitalized with H1N1 influenza pneumonia between January 2019 and February 2020, and patients hospitalized with COVID-19 during the outbreak. A demographic and clinical characteristic of H1N1 influenza and COVID-19 patients were recorded. Both groups were compared-using an independent samples student t test for continuous variables and a chi-square test for categorical data-to identify significantly different parameters between the 2 diseases.

Results

A total of 78 patients were included and divided into 2 groups: 33 patients (42.3%) with H1N1 and 45 patients (57.7%) with COVID-19. The mean age of the patients was 43.3 ± 10.6 years. Bronchial asthma was significantly higher among patients with H1N1, while diabetes mellitus was significantly higher among patients with COVID-19. Right lower lobe affection was significantly present among those with H1N1 than those with COVID (100% vs 0%). The monocytic count was significantly higher among those with H1N1 than COVID-19 (11.63 ± 1.50 vs 7.76 ± 1.68; P < 0.001). Respiratory rates of more than 22 c/min significantly increased in patients with HINI than in those with COVID-19 (18.2% vs 4.4%; P = 0.05). Mortality increased in patients with HINI than in those with COVID-19 (18.2% vs 6.7%). However, the difference did not reach statistical significance (P = 0.15).

Conclusion

Clinically, it is difficult to distinguish between H1N1 and COVID-19. Thus, a polymerase chain reaction is recommended for all patients suffering from influenza-like symptoms to rule out influenza A subtype H1N1 and/or SARS-CoV2.

Clinical spectrum of ocular manifestations in COVID-19: a case series

In this current case series, all Coronavirus disease 2019 patients had predominant ophthalmological presentation. Only one patient sough care for concomitant respiratory symptoms. We reported herein 2 cases with cranial oculomotor nerve palsy, one patient with confirmed diagnosis of branch retinal vein occlusion, and the last one patient presenting for acute kareto-conjunctivitis with several recurrences, which was unsuccessfully treated with steroids and requiring cliclosporin. These case series highlights the importance of collecting a careful history of ocular presentation, including exposures to possible infected patients with SARS-CoV-2. This this will lead to an early diagnosis and treatment and to make appropriate infection control measures.

COVID-19 Disease Prediction Utilizing Dilated Convolution Neural Network Based Levy Flight Tunicate Swarm Optimization

The worldwide pandemic of COVID-19 illness has wreaked havoc on the health and lives of countless individuals in more than 200 countries. More than 44 million individuals have been afflicted by October 2020, with over 1,000,000 fatalities reported. This disease, which is classified as a pandemic, is still being researched for diagnosis and therapy. It is critical to diagnose this condition early in order to save a person's life. Diagnostic investigations based on deep learning are speeding up this procedure. As a result, in order to contribute to this sector, our research proposes a deep learning-based technique that may be employed for illness early detection. Based on this insight, gaussian filter is applied to the collected CT images and the filtered images are subjected to the proposed tunicate dilated convolutional neural network, whereas covid and non-covid disease are categorized to improve the accuracy requirement. The hyperparameters involved in the proposed deep learning techniques are optimally tuned using the proposed levy flight based tunicate behaviour. To validate the proposed methodology, evaluation metrics are tested and shows superiority of the proposed approach during COVID-19 diagnostic studies.

The Risk Factors for Acute Cerebrovascular Accident (Stroke) in Patients with Severe Acute Respiratory Syndrome Coronavirus (SARS-CoV-2)

Severe Acute Respiratory Syndrome Coronavirus (SARS-CoV-2) patients may experience an acute ischemic stroke; however, risk factors, in-hospital deaths, and outcomes have not been thoroughly investigated. This study investigates the risk factors, comorbidities, and outcomes in patients with SARS-VoV-2 infection and acute ischemic stroke compared to patients without these conditions. The present retrospective study was conducted in the King Abdullah International Medical Research Centre (KAIMRC), Ministry of National Guard, Health Affairs, Riyadh, Saudi Arabia, during the period from April 2020 to February 2022. This study investigates the risk variables among the individuals who were diagnosed with either SARS-CoV-2 with stroke or patients with stroke alone. A total of 42,688 COVID-19 patients were registered, 187 cases of strokes were listed in COVID-19 patients, however, 5395 cases with stroke without SARS-CoV-2 infection. The results revealed that factors including age, hypertension, deep vein thrombosis, and ischemic heart disease are associated with an increased risk of ischemic stroke. The results also displayed an elevated frequency of in-hospital deaths in COVID-19 patients with acute ischemic stroke. The results also showed that SARS-CoV-2 together predicts the probability of stroke and death in the study sample. The study findings conclude that ischemic strokes were infrequent in patients with SARS-CoV-2 and usually occur in the presence of other risk factors. The risk factors of ischemic strokes in patients with SARS-CoV-2 are old age, male gender, hypertension, hyperlipidaemia, DVT, ischemic heart disease, and diabetes mellitus. Furthermore, the results showed a higher frequency of in-hospital deaths in COVID-19 patients with stroke compared to COVID-19 patients without stroke.

Evaluating chest pain in patients with post COVID conditions permission to think outside of the box

Chest pain is among the most common symptoms of post-COVID-19 Conditions (PCC) that prompts medical attention. Because the SARS-CoV-2 virus has proclivity for many organs and organ systems in the chest, ranging from the heart, lungs, great vessels, lymphatics, and peripheral nerves, clinicians evaluating patients with chest pain must consider a broad differential diagnosis and take a comprehensive approach to management.

In Patients Hospitalized for Community-Acquired Pneumonia, SARS-CoV-2 Is Associated with Worse Clinical Outcomes When Compared to Influenza

SARS-CoV-2 and influenza are primary causes of viral community-acquired pneumonia (CAP). Both pathogens have exhibited high transmissibility and are recognized causes of pandemics. Controversy still exists regarding the clinical outcomes between patients hospitalized with CAP due to these viruses. This secondary analysis identified patients with either influenza or SARS-CoV-2 infections from three cohorts of patients hospitalized for CAP. Clinical outcomes between patients with CAP due to influenza or due to SARS-CoV-2 were evaluated. Primary outcomes included length of stay and in-hospital mortality. To account for population differences between cohorts, each case of influenza CAP was matched to two controls with SARS-CoV-2 CAP. Matching criteria included sex, age, and nursing home residency. Stratified cox-proportional hazards regression or conditional logistic regression were used where appropriate. A total of 259 patients with influenza CAP were matched to two controls with SARS-CoV-2 CAP, totaling to 518 controls. Patients with SARS-CoV-2 CAP were 2.23 times more likely to remain hospitalized at any point in time (95% confidence interval: 1.77-2.80), and had 3.84 times higher odds of dying in-hospital (95% confidence interval: 1.91-7.76) when compared to patients with influenza CAP. After matching and adjusting for confounding variables, patients admitted with SARS-CoV-2 CAP had consistently worse outcomes in comparison to their influenza CAP counterparts. This information can help clinicians decide on the level of care needed for patients with confirmed infections due to these pathogens. Additionally, estimates of disease burden can inform individuals at-risk for poor clinical outcomes, and further highlight the importance of effective preventative strategies.

In vitro antiviral activity of stabilized chlorine dioxide containing oral care products

OBJECTIVE

To determine the in vitro antiviral activity of oral care products containing stabilized chlorine dioxide toward infectious viruses that harbor in the oral cavity. Specfically, severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), SARS-CoV, human coronavirus (HCoV) 229E, influenza A (H3N2), rhinovirus type 14, adenovirus type 5, and herpes simplex virus (HSV) type 1 and 2 were examined.

METHODS

Validated in vitro suspension virucidal assays were used. Test product was mixed with the test virus for 30, 60, or 120 s, neutralized with sodium thiosulfate, serially diluted in dilution medium in a 96-well plate and incubated in a carbon dioxide incubator for 7 days. The 50% Tissue Culture Infectious Dose per milliliter was determined.

RESULTS

Two rinses, one oral spray and one fluoride toothpaste showed log reduction of severe acute respiratory syndrome coronavirus-2 ranging from 1.81 to 2.98 and of influenza A from 2.58 to 4.13, respectively, within 30 s of contact time; similar results were obtained at 60 s. Further, the Ultra Sensitive rinse showed 0.19, 0.75, 1.58, 1.75, 2.66, and 3.24 log reduction of severe acute respiratory syndrome coronavirus, human coronavirus 229E, rhinovirus type 14, adenovirus type 5, and herpes simplex virus type 1 and type 2, respectively, within 30 s of contact time.

CONCLUSION

Stabilized chlorine dioxide containing ClōSYS^® oral care products reduced the viral load of multiple viruses within 30 s. The results warrant further investigation for potential in vivo applications.

Dissociating COVID-19 from other respiratory infections based on acoustic, motor coordination, and phonemic patterns

In the face of the global pandemic caused by the disease COVID-19, researchers have increasingly turned to simple measures to detect and monitor the presence of the disease in individuals at home. We sought to determine if measures of neuromotor coordination, derived from acoustic time series, as well as phoneme-based and standard acoustic features extracted from recordings of simple speech tasks could aid in detecting the presence of COVID-19. We further hypothesized that these features would aid in characterizing the effect of COVID-19 on speech production systems. A protocol, consisting of a variety of speech tasks, was administered to 12 individuals with COVID-19 and 15 individuals with other viral infections at University Hospital Galway. From these recordings, we extracted a set of acoustic time series representative of speech production subsystems, as well as their univariate statistics. The time series were further utilized to derive correlation-based features, a proxy for speech production motor coordination. We additionally extracted phoneme-based features. These features were used to create machine learning models to distinguish between the COVID-19 positive and other viral infection groups, with respiratory- and laryngeal-based features resulting in the highest performance. Coordination-based features derived from harmonic-to-noise ratio time series from read speech discriminated between the two groups with an area under the ROC curve (AUC) of 0.94. A longitudinal case study of two subjects, one from each group, revealed differences in laryngeal based acoustic features, consistent with observed physiological differences between the two groups. The results from this analysis highlight the promise of using nonintrusive sensing through simple speech recordings for early warning and tracking of COVID-19.

Clinical Features of COVID-19, Dengue, and Influenza among Adults Presenting to Emergency Departments and Urgent Care Clinics-Puerto Rico, 2012-2021

Dengue and influenza are pathogens of global concern and cause febrile illness similar to COVID-19. We analyzed data from an enhanced surveillance system operating from three emergency departments and an urgent care clinic in Puerto Rico to identify clinical features predictive of influenza or dengue compared with COVID-19. Participants with fever or respiratory symptoms and aged ≥18 years enrolled May 2012-January 2021 with dengue, influenza, or SARS-CoV-2 confirmed by reverse transcriptase polymerase chain reaction were included. We calculated adjusted odds ratios (aORs) and 95% CIs using logistic regression to assess clinical characteristics of participants with COVID-19 compared to those with dengue or influenza, adjusting for age, subregion, and days from illness onset to presentation for clinical care. Among 13,431 participants, we identified 2,643 with dengue (N = 303), influenza (N = 2,064), or COVID-19 (N = 276). We found differences in days from onset to presentation among influenza (2 days [interquartile range: 1-3]), dengue (3 days [2-4]), and COVID-19 cases (4 days [2-7]; P < 0.001). Cough (aOR: 0.12 [95% CI: 0.07-0.19]) and shortness of breath (0.18 [0.08-0.44]) were less common in dengue compared with COVID-19. Facial flushing (20.6 [9.8-43.5]) and thrombocytopenia (24.4 [13.3-45.0]) were more common in dengue. Runny nose was more common in influenza compared with COVID-19 (8.3 [5.8-12.1]). In summary, cough, shortness of breath, facial flushing, and thrombocytopenia helped distinguish between dengue and COVID-19. Although few features distinguished influenza from COVID-19, presentation > 4 days after symptom onset suggests COVID-19. These findings may assist clinicians making time-sensitive decisions regarding triage, isolation, and management while awaiting pathogen-specific testing.

Successful Treatment of Complicated Influenza A(H3N2) Virus Infection and Rhabdomyolysis with Compassionate Use of IV Zanamivir

In 2019, EMA licensed intravenous (IV) zanamivir for severe influenza virus infection in children over 6 months as well as adults. Prior to that, it was possible via a compassionate use program. We present successful compassionate use of IV zanamivir in a 14-year-old female with severe influenza A(H3N2) and multi-organ failure, who had failed oral oseltamivir. Her illness was complicated by acute respiratory distress syndrome and rhabdomyolysis requiring extracorporeal membrane oxygenation and hemofiltration. Considering the broad safety margins with neuraminidase inhibitors, an adult dose of 600 mg IV BID was administered in this 60 kg patient. Influenza virus was cleared rapidly and undetectable on day 13. Creatine kinase (CK) values were dropping from 38,000 to 500 within nine days. Given the recent licensure of IV zanamivir, multi-center prospective observational studies in pediatric Intensive Care Unit patients would be beneficial to guide the most appropriate use of IV zanamivir in this vulnerable age group.

The comparison of COVID-19 vs seasonal influenza in children

BACKGROUND

Influenza in children has been well described, whereas there has been a paucity of pediatric data regarding COVID-19. It is crucial for clinicians to differentiate cases of COVID-19 from cases of influenza because of the upcoming influenza season in the new pandemic era.

METHODS

This retrospective study included pediatric patients who were diagnosed with laboratory-confirmed COVID-19 between March and September 2020, or seasonal influenza between October 2019 and March 2020.

RESULTS

A total of 315 children were included in this study; 151 were diagnosed with influenza and 164 had confirmed COVID-19. The median age of patients with COVID-19 was 10 years (interquartile range [IQR]: 3-15 years), whereas the median age of patients with influenza was 4 years (IQR: 1-6 years) (p = 0.001). In the COVID-19 group, 6.3% of patients had underlying diseases, the most frequent being neurological conditions (3%). In the influenza group, 20.9% of patients had an underlying disease, the most frequent being asthma (14.5%). Fever (odds ratio [OR]: 20.476; 95% confidence interval [CI]: 2.438-171.995; p = 0.005), dyspnea/tachypnea (OR 13.950; 95% CI: 2.607-74.634; p = 0.002), and increased C-reactive protein (CRP) (OR: 7.650; 95% CI: 2.094-27.955; p = 0.002) were main predictors of influenza diagnosis in comparison to COVID-19. Lymphopenia was detected in 43.2% of patients with influenza and 19.9% of patients with COVID-19 (p = 0.001).

CONCLUSIONS

The accurate differentiation between "influenza or COVID-19" seems possible by evaluating a combination of factors including cough, fever, vomiting, leucopenia, lymphopenia, pneumonia, in pediatric patients with high CRP as well as age.

COVID-19 and pneumonia diagnosis from chest X-ray images using convolutional neural networks

X-ray is a useful imaging modality widely utilized for diagnosing COVID-19 virus that infected a high number of people all around the world. The manual examination of these X-ray images may cause problems especially when there is lack of medical staff. Usage of deep learning models is known to be helpful for automated diagnosis of COVID-19 from the X-ray images. However, the widely used convolutional neural network architectures typically have many layers causing them to be computationally expensive. To address these problems, this study aims to design a lightweight differential diagnosis model based on convolutional neural networks. The proposed model is designed to classify the X-ray images belonging to one of the four classes that are Healthy, COVID-19, viral pneumonia, and bacterial pneumonia. To evaluate the model performance, accuracy, precision, recall, and F1-Score were calculated. The performance of the proposed model was compared with those obtained by applying transfer learning to the widely used convolutional neural network models. The results showed that the proposed model with low number of computational layers outperforms the pre-trained benchmark models, achieving an accuracy value of 89.89% while the best pre-trained model (Efficient-Net B2) achieved accuracy of 85.7%. In conclusion, the proposed lightweight model achieved the best overall result in classifying lung diseases allowing it to be used on devices with limited computational power. On the other hand, all the models showed a poor precision on viral pneumonia class and confusion in distinguishing it from bacterial pneumonia class, thus a decrease in the overall accuracy.

Mortality in cancer patients with SARS-CoV-2 or seasonal influenza: an observational cohort study from a German-wide hospital network

PURPOSE

At the beginning of the COVID-19 pandemic, SARS-CoV-2 was often compared to seasonal influenza. We aimed to compare the outcome of hospitalized patients with cancer infected by SARS-CoV-2 or seasonal influenza including intensive care unit admission, mechanical ventilation and in-hospital mortality.

METHODS

We analyzed claims data of patients with a lab-confirmed SARS-CoV-2 or seasonal influenza infection admitted to one of 85 hospitals of a German-wide hospital network between January 2016 and August 2021.

RESULTS

29,284 patients with COVID-19 and 7442 patients with seasonal influenza were included. Of these, 360 patients with seasonal influenza and 1625 patients with COVID-19 had any kind of cancer. Cancer patients with COVID-19 were more likely to be admitted to the intensive care unit than cancer patients with seasonal influenza (29.4% vs 24.7%; OR 1.31, 95% CI 1.00-1.73 p < .05). No statistical significance was observed in the mechanical ventilation rate for cancer patients with COVID-19 compared to those with seasonal influenza (17.2% vs 13.6% OR 1.34, 95% CI 0.96-1.86 p = .09). 34.9% of cancer patients with COVID-19 and 17.9% with seasonal influenza died (OR 2.45, 95% CI 1.81-3.32 p < .01). Risk factors among cancer patients with COVID-19 or seasonal influenza for in-hospital mortality included the male gender, age, a higher Elixhauser comorbidity index and metastatic cancer.

CONCLUSION

Among cancer patients, SARS-CoV-2 was associated with a higher risk for in-hospital mortality than seasonal influenza. These findings underline the need of protective measurements to prevent an infection with either COVID-19 or seasonal influenza, especially in this high-risk population.

Taste loss as a distinct symptom of COVID-19: a systematic review and meta-analysis

Chemosensory scientists have been skeptical that reports of COVID-19 taste loss are genuine, in part because before COVID-19 taste loss was rare and often confused with smell loss. Therefore, to establish the predicted prevalence rate of taste loss in COVID-19 patients, we conducted a systematic review and meta-analysis of 376 papers published in 2020-2021, with 235 meeting all inclusion criteria. Drawing on previous studies and guided by early meta-analyses, we explored how methodological differences (direct vs. self-report measures) may affect these estimates. We hypothesized that direct measures of taste are at least as sensitive as those obtained by self-report and that the preponderance of evidence confirms taste loss is a symptom of COVID-19. The meta-analysis showed that, among 138,015 COVID-19-positive patients, 36.62% reported taste dysfunction (95% confidence interval: 33.02%-40.39%), and the prevalence estimates were slightly but not significantly higher from studies using direct (n = 15) versus self-report (n = 220) methodologies (Q = 1.73, df = 1, P = 0.1889). Generally, males reported lower rates of taste loss than did females, and taste loss was highest among middle-aged adults. Thus, taste loss is likely a bona fide symptom of COVID-19, meriting further research into the most appropriate direct methods to measure it and its underlying mechanisms.

Clinical manifestations of COVID-19 versus other upper respiratory tract infections in pediatric patients

OBJECTIVES

To explore the differences between COVID-19 and upper respiratory tract infections (URTI) in the pediatric population, emphasizing smell and taste disturbances.

METHODS

A case-control study included 468 patients, 234 with COVID-19 (cases) and 234 with URTI (controls) at a tertiary hospital, Riyadh, Saudi Arabia, from 2020-2021. Patients with bacterial URTI, lower tract respiratory infections, and speech or developmental delays were excluded. Statistical analysis was carried out using Statistical Analysis System, 9.2 version. A p-value of ≤0.05 was considered significant.

RESULTS

The male-to-female ratio was almost equal, with a mean age of 9.90±2.34. Multivariable logistic regression analysis showed that a change in taste significantly increases the probability of COVID-19 by 21.98 times. On the other hand, sore throat (81.5%), dyspnea (63.5%), nasal obstruction (72.7%), and otalgia significantly (74.8%) decrease the likelihood of COVID-19.

CONCLUSION

Taste disturbances increase the probability of COVID-19 infections, whereas sore throat, dyspnea, nasal obstruction, and otalgia increase the likelihood of other URTIs. The described differences might aid physicians in their differential diagnosis and treatment during the pandemic.

Olfactory dysfunction in COVID-19: new insights into the underlying mechanisms

The mechanisms of olfactory dysfunction in COVID-19 are still unclear. In this review, we examine potential mechanisms that may explain why the sense of smell is lost or altered. Among the current hypotheses, the most plausible is that death of infected support cells in the olfactory epithelium causes, besides altered composition of the mucus, retraction of the cilia on olfactory receptor neurons, possibly because of the lack of support cell-derived glucose in the mucus, which powers olfactory signal transduction within the cilia. This mechanism is consistent with the rapid loss of smell with COVID-19, and its rapid recovery after the regeneration of support cells. Host immune responses that cause downregulation of genes involved in olfactory signal transduction occur too late to trigger anosmia, but may contribute to the duration of the olfactory dysfunction.

COVID-19 and Influenza Coinfection Outcomes among Hospitalized Patients in the United States: A Propensity Matched Analysis of National Inpatient Sample

This study aims to provide comparative data on clinical features and in-hospital outcomes among U.S. adults admitted to the hospital with COVID-19 and influenza infection using a nationwide inpatient sample (N.I.S.) data 2020. Data were collected on patient characteristics and in-hospital outcomes, including patient's age, race, sex, insurance status, median income, length of stay, mortality, hospitalization cost, comorbidities, mechanical ventilation, and vasopressor support. Additional analysis was performed using propensity matching. In propensity-matched cohort analysis, influenza-positive (and COVID-positive) patients had higher mean hospitalization cost (USD 129,742 vs. USD 68,878, p = 0.04) and total length of stay (9.9 days vs. 8.2 days, p = 0.01), higher odds of needing mechanical ventilation (OR 2.01, 95% CI 1.19-3.39), and higher in-hospital mortality (OR 2.09, 95% CI 1.03-4.24) relative to the COVID-positive and influenza-negative cohort. In conclusion, COVID-positive and influenza-negative patients had lower hospital charges, shorter hospital stays, and overall lower mortality, thereby supporting the use of the influenza vaccine in COVID-positive patients.

Evaluation of the Kaira COVID-19/Flu/RSV Detection Kit for detection of SARS-CoV-2, influenza A/B, and respiratory syncytial virus: A comparative study with the PowerChek SARS-CoV-2, influenza A&B, RSV Multiplex Real-time PCR Kit

BACKGROUND

Co-circulation of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and other respiratory viruses, such as influenza and respiratory syncytial virus (RSV), can be a severe threat to public health. The accurate detection and differentiation of these viruses are essential for clinical laboratories. Herein, we comparatively evaluated the performance of the Kaira COVID-19/Flu/RSV Detection Kit (Kaira; Optolane, Seongnam, Korea) for detection of SARS-CoV-2, influenza A and B, and RSV in nasopharyngeal swab (NPS) specimens with that of the PowerChek SARS-CoV-2, Influenza A&B, RSV Multiplex Real-time PCR Kit (PowerChek; Kogene Biotech, Seoul, Korea).

METHODS

A total of 250 archived NPS specimens collected for routine clinical testing were tested in parallel by the Kaira and PowerChek assays. RNA standards were serially diluted and tested by the Kaira assay to calculate the limit of detection (LOD).

RESULTS

The positive and negative percent agreements between the Kaira and PowerChek assays were as follows: 100% (49/49) and 100% (201/201) for SARS-CoV-2; 100% (50/50) and 99.0% (198/200) for influenza A; 100% (50/50) and 100% (200/200) for influenza B; and 100% (51/51) and 100% (199/199) for RSV, respectively. The LODs of the Kaira assay for SARS-CoV-2, influenza A and B, and RSV were 106.1, 717.1, 287.3, and 442.9 copies/mL, respectively.

CONCLUSIONS

The Kaira assay showed comparable performance to the PowerChek assay for detection of SARS-CoV-2, influenza A and B, and RSV in NPS specimens, indicating that the Kaira assay could be a useful diagnostic tool when these viruses are co-circulating.

SARS COV-2 and other viral etiology as a possible clue for the olfactory dilemma

Background

Post-viral anosmia is responsible for more than 40% of cases of anosmia. Anosmia has been a neglected symptom in the primary healthcare setting until the emergence of the SARS-CoV-2 pandemic. The spread of SARS-CoV-2 infection highlighted new atypical symptoms of the disease, including anosmia, which has become one of the diagnostic symptoms of the disease, and epidemiological concern. We aimed to detect the incidence of SARS-CoV-2 infection within patients presented with anosmia and to test for other respiratory viruses in the negative COVID-19 patients. We also detected the recovery of anosmia and IgM/IgG against COVID-19. We prospectively included 60 outpatients with the major complaint of anosmia. Nasopharyngeal swabs were done for SARS-CoV-2 real-time PCR, and if negative, PCR to other respiratory pathogens was tested. After one month, we inquired about the recovery of smell loss together with testing for antibodies against SARS-CoV-2.

Results

Sixty patients were enrolled in the study. Forty-six patients (76.7%) were SARS-CoV-2 PCR positive and 14 (23.3%) were negative. Rhinovirus was the commonest isolated pathogen in the negative cases (5/14). Complete recovery of anosmia occurred in 34 patients (56.7%), while partial recovery in 24 (40.0%), and no recovery in 2 patients (3.3%). The median time to complete recovery was 10 days. 28.3% (13/46) of the patients showed negative antibody response for both IgG and IgM.

Conclusions

Sudden-onset anosmia is a symptom that is highly predictive of being COVID-19-infected. While recovery is expected within 2 weeks, some patients have no antibodies against SARS-CoV-2.

Impact of upper and lower respiratory symptoms on COVID-19 outcomes: a multicenter retrospective cohort study

BACKGROUND

Respiratory symptoms are associated with coronavirus disease 2019 (COVID-19) outcomes. However, the impacts of upper and lower respiratory symptoms on COVID-19 outcomes in the same population have not been compared. The objective of this study was to characterize upper and lower respiratory symptoms and compare their impacts on outcomes of hospitalized COVID-19 patients.

METHODS

This was a multicenter, retrospective cohort study; the database from the Japan COVID-19 Task Force was used. A total of 3314 COVID-19 patients were included in the study, and the data on respiratory symptoms were collected. The participants were classified according to their respiratory symptoms (Group 1: no respiratory symptoms, Group 2: only upper respiratory symptoms, Group 3: only lower respiratory symptoms, and Group 4: both upper and lower respiratory symptoms). The impacts of upper and lower respiratory symptoms on the clinical outcomes were compared. The primary outcome was the percentage of patients with poor clinical outcomes, including the need for oxygen supplementation via high-flow oxygen therapy, mechanical ventilation, and extracorporeal membrane oxygenation or death.

RESULTS

Of the 3314 COVID-19 patients, 605, 1331, 1229, and 1149 were classified as Group 1, Group 2, Group 3, and Group 4, respectively. In univariate analysis, patients in Group 2 had the best clinical outcomes among all groups (odds ratio [OR]: 0.21, 95% confidence interval [CI]: 0.11-0.39), while patients in Group 3 had the worst outcomes (OR: 3.27, 95% CI: 2.43-4.40). Group 3 patients had the highest incidence of pneumonia, other complications due to secondary infections, and thrombosis during the clinical course.

CONCLUSIONS

Upper and lower respiratory tract symptoms had vastly different impacts on the clinical outcomes of COVID-19.

COVID-19 pneumonia: lessons learned, challenges, and preparing for the future

Coronavirus disease 2019 (COVID-19) is a viral disease that causes life-threatening health problems during acute illness, causing a pandemic and millions of deaths. Although computed tomography (CT) was used as a diagnostic tool for COVID-19 in the early period of the pan demic due to the inaccessibility or long duration of the polymerase chain reaction tests, cur rent studies have revealed that CT scan should not be used to diagnose COVID-19. However, radiologic findings are vital in assessing pneumonia severity and investigating complications in patients with COVID-19. Long-term symptoms, also known as long COVID, in people recovering from COVID-19 affect patients' quality of life and cause global health problems. Herein, we aimed to summarize the lessons learned in COVID-19 pneumonia, the challenges in diagnosing the disease and complications, and the prospects for future studies.

In-hospital incidence of and risk factors for influenza-associated respiratory failure

BACKGROUND

Respiratory failure (RF) is the most important complication of influenza virus infection. Its definition and incidence are heterogeneous in the literature.

METHODS

This systematic review and meta-analysis aim to determine the incidence of and risk factors for RF in patients hospitalized with influenza. Electronic databases were searched for articles on RF in patients hospitalized for influenza infection up to December 2021 regardless of their geographical location. Observational and experimental studies were considered for inclusion, excluding case series. The Newcastle-Ottawa and Johanna Briggs scales were used for quality assessment. A random-effects meta-analysis was performed, followed by subgroup analyses according to, among others, presence/absence of pneumonia, RF definition, serotype and time period. PRISMA guidelines were followed for this review.

RESULTS

Thirty-six studies were finally included in the meta-analysis. Overall, RF incidence was 24% (range 5%-85%, 95% confidence interval [95CI] 19%-31%). Significantly higher incidences of RF were found in patients with pneumonia (42%, 95CI 28%-57%, p = .006), when RF was defined as hypoxemia (58%, 95CI 31%-81%, p < .001), and during the 2009 pandemic (25%, 95CI 16%-36%) and postpandemic period (23%, 95CI 15%-34%, p = .01). No differences were found between human influenza serotypes. Assessment of risk factors associated with the development of RF was not possible due to their inconsistent and heterogeneous reporting.

CONCLUSION

Respiratory failure is frequent in hospitalized influenza patients, especially in patients with pneumonia and since the 2009 pandemic, although its definition and reporting widely vary in the literature. This complicates its characterization and comparison between cohorts and with other respiratory viruses.

Therapeutic and palliative role of a Unani herbal decoction in COVID-19 and similar respiratory viral illnesses: Phytochemical & pharmacological perspective

ETHNOPHARMACOLOGICAL RELEVANCE

Outbreaks of respiratory viral infections like Severe Acute Respiratory Syndrome, Middle-East Respiratory Syndrome, and Coronavirus Disease-2019 have been a regular occurrence in the past 100 years. A significant proportion of the morbidity and mortality in influenza is attributed to the co-morbidities and complications induced by the disease, involving the vital organs and physiological functions. In this context, traditional medicines offer effective protective, palliative, and therapeutic benefits, as observed in several studies on various types of influenza, including COVID-19. The Unani herbal decoction comprising of 'Unnāb (Ziziphus jujuba Mill. fruit), Sapistān (Cordia dichotoma G. Forst. fruit), and Behīdāna (Cydonia oblonga Mill. seed) was originally prescribed by Hakim Ajmal Khan (1868-1927 AD) for various respiratory ailments as a bronchodilator, anti-inflammatory, and for clearing the respiratory tract. During COVID-19, the decoction was prescribed by the Ministry of Ayurveda, Yoga, Unani, Siddha, and Homeopathy (AYUSH), Government of India, for mild patients in home isolation, and also as a self-care drink for healthy people. Preliminary studies are of the view that the decoction could reduce COVID-19 incidence and prevent severe disease in the population where it was administered.

AIMS OF THE STUDY

We intend to review the pharmacological activity of the Unani decoction ingredients, i.e., Z. jujuba, C. dichotoma, and C. oblonga, in context with respiratory viral infections and their co-morbidities, to develop an understanding of its action mechanism.

METHODOLOGY

We reviewed Unani classical textbooks for information on the therapeutic activity of the decoction ingredients. Scientific studies published in English from the year 2000 onwards on leading scientific websites (PubMed, MEDLINE, Scopus, and Springer) were searched for information regarding the efficacy of the drugs in influenza and its common complications. Non-English language articles, or those published prior to 2000, and those which included plant parts other than those traditionally included in the decoction were excluded.

OBSERVATIONS

A wide range of therapeutic and palliative effects have been observed in the three herbs included in the Unani decoction, including anti-viral, anti-bacterial, immuno-modulatory, anti-inflammatory, hepato-, and nephroprotective, anti-atherosclerotic, anti-tussive, broncho-dilatory, and regulation of gut microbiota. Together, these effects can help to mitigate and prevent most of the complications caused as a result of respiratory viral infections.

CONCLUSION

The combined effects of ingredients in this Unani herbal decoction can potentially help to mitigate most of the pathological changes and complications caused by influenza viruses. With further clinical research, the decoction may be potentially utilized as a prophylactic and therapeutic against viral influenza.

Serum ACE2 Level is Associated With Severe SARS-CoV-2 Infection: A Cross-Sectional Observational Study

Objectives:

Angiotensin-converting enzyme 2 (ACE2) represents the primary receptor for SARS-CoV-2 to enter endothelial cells, causing coronavirus disease of 2019 (COVID-19). In this study, we investigate the association between circulating ACE2 levels with the severity of COVID-19.

Methods:

Serum ACE2 levels were measured in 144 COVID-19-positive subjects at hospital admission, and 123 COVID-19-negative control subjects. The association between ACE2 and clinical outcomes was analyzed.

Results:

About 144 COVID-19 patients and 123 healthy controls data were analyzed, the mean age of patients was 62 years and 50% of them were males. The mean age of the control group was 55 years and 63% were males. ACE-II level was measured and compared between COVID-19 patients and controls and revealed no significant differences (P > .05). ACE-II level was measured in COVID-19 patients and compared between different patient’s subgroups, ACE II level was not dependent on gender, smoking, ACE intake, or comorbidities (P > .05), and was significantly correlated with cardiovascular diseases (CVS) (P-value = .046) ICU admission (P-value = .0007) and Death (P-value = .0082).

Conclusion:

There was no significant difference between the COVID-19 and Control group, however, ACE2 serum level was significantly higher in patients with COVID-19 who were critically ill or non-survivors, its increased level is also associated with length of stay. Elevated ACE2 level is associated with the severity of COVID-19 disease, and it has the potential to be a predictor of the severity of the disease.

Outbreak control management: Lessons from SARS-CoV-2 infections in 2020-2022 in Hong Kong, an international municipality with high-frequency travelers

The control management of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections is one of the most challenges in the 21st century. By May 8th, 2022, SARS-CoV-2 has infected over 510 million people with 6.2 million death worldwide and over 1.2 million people with 9133 deaths in the fifth wave of infection in Hong Kong. The government responded rapidly in the early days of the 2020 outbreak, and the results were encouraging to control COVID-19 outbreak unavailable of vaccine. The quick responses to the epidemic alerts, for example, public education and control policies, kept residents safe from infection in the city with such a high population density and large-scale travelers. Nevertheless, the extremely high infectivity, Omicron variant infections, and the shortcomings of transmission control measures led to uncontrollable outbreak in 2022. The weak immunity groups, elderly and children, experienced a high hospitalization rate and mortality rate because of low vaccination rate. Currently, the infection is under well controlled. This study timely summarizes the challenges, policy, and lessons of SARS-CoV-2 outbreak control from 2020 to 2022. More importantly, the lesson and policy revealed from this study may be beneficial and applied to other cities with the outbreak of highly infectious SARS-CoV-2.

Lab practices that improve coronavirus disease 2019 detection accuracy using real-time PCR

The number of coronavirus disease 2019 (COVID-19) cases significantly increased with the emergence of multiple variants of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). This has led to an ongoing effort focused on developing the diagnostic detection tests. Among the currently available tests, real-time reverse transcriptase PCR (RT-PCR) has been considered as the ‘golden method’ for the detection of SARS-COV-2. However, a significant number of inaccurate (false-negative/false-positive) results have been reported in spite of this method's reliability and effectiveness. These unreliable results may arise because of various issues encountered throughout the entire testing process starting with the sampling phase, going through the PCR process, and ending with the result analysis. This article aims to shed light on the errors that occur during the COVID-19 testing process and suggest ways to overcome them effectively. Accurate testing could be optimized by following the correct swabbing technique, using adequate RT-PCR kits and controls, setting clear lab guidelines, and properly interpreting the results.

Stellate Ganglion Block for Anosmia and Dysgeusia Due to Long COVID

Anosmia and parosmia refer to the loss or dysfunction of smell, respectively. Dysgeusia refers to taste disturbance. The coronavirus disease 2019 (COVID-19) pandemic and the subsequent phenomenon of Long COVID syndrome have been associated with an increased incidence of anosmia and dysgeusia. Smell and taste disturbances associated with COVID-19 are usually self-limiting but can persist for longer periods in some cases. Imbalances of the autonomic nervous system, especially dysregulation of the sympathetic system, are implicated in the persistence of anosmia and dysgeusia post-COVID-19 infection. Stellate ganglion block (SGB) can diminish the increased sympathetic activity and potentially resolve anosmia and dysgeusia occurring due to Long COVID. The authors report the successful resolution of persistent anosmia and dysgeusia due to Long COVID in a female patient after she underwent SGB.

Prevalence of symptoms in 1512 COVID-19 patients: have dizziness and vertigo been underestimated thus far?

The relationship between SARS-CoV-2 infection and dizziness is still unclear. The aim of this study is to assess the prevalence and characteristics of dizziness and vertigo among patients with mild-to-moderate COVID-19. Patients discharged from the emergency rooms with a confirmed SARS-CoV-2 diagnosis were assisted by daily telephone calls until nasopharyngeal swab negativization, and specific symptoms concerning balance disorders were investigated through targeted questions posed by experienced physicians. The study included 1512 subjects (765 females, 747 males), with a median age of 51 ± 18.4 years. New-onset dizziness was reported by 251 (16.6%) patients, among whom 110 (43.8%) complained of lightheadedness, 70 (27.9%) of disequilibrium, 41 (16.3%) of presyncope, and 30 (12%) of vertigo. This study analyzed in detail the prevalence and pathophysiological mechanisms of the different types of balance disorders in a large sample, and the results suggest that dizziness should be included among the main symptoms of COVID-19 because one-sixth of patients reported this symptom, with females being significantly more affected than males (20.3 vs 12.9%, P < 0.001). Most cases of dizziness were attributable to lightheadedness, which was probably exacerbated by psychophysical stress following acute infection and mandatory quarantine. Vertigo should not be underestimated because it might underlie serious vestibular disorders, and disequilibrium in elderly individuals should be monitored due to the possible risk of falls.

Patient outcomes following emergency admission to hospital for COVID-19 compared with influenza: retrospective cohort study

BACKGROUND

We examine differences in posthospitalisation outcomes, and health system resource use, for patients hospitalised with COVID-19 during the UK's first pandemic wave in 2020, and influenza during 2018 and 2019.

METHODS

This retrospective cohort study used routinely collected primary and secondary care data. Outcomes, measured for 90 days follow-up after discharge were length of stay in hospital, mortality, emergency readmission and primary care activity.

RESULTS

The study included 5132 patients admitted to hospital as an emergency, with COVID-19 and influenza cohorts comprising 3799 and 1333 patients respectively. Patients in the COVID-19 cohort were more likely to stay in hospital longer than 10 days (OR 3.91, 95% CI 3.14 to 4.65); and more likely to die in hospital (OR 11.85, 95% CI 8.58 to 16.86) and within 90 days of discharge (OR 7.92, 95% CI 6.20 to 10.25). For those who survived, rates of emergency readmission within 90 days were comparable between COVID-19 and influenza cohorts (OR 1.07, 95% CI 0.89 to 1.29), while primary care activity was greater among the COVID-19 cohort (incidence rate ratio 1.30, 95% CI 1.23 to 1.37).

CONCLUSIONS

Patients admitted for COVID-19 were more likely to die, more likely to stay in hospital for over 10 days and interact more with primary care after discharge, than patients admitted for influenza. However, readmission rates were similar for both groups. These findings, while situated in the context of the first wave of COVID-19, with the associated pressures on the health system, can inform health service planning for subsequent waves of COVID-19, and show that patients with COVID-19 interact more with healthcare services as well as having poorer outcomes than those with influenza.

Performance Evaluation of the PowerChek SARS-CoV-2, Influenza A & B Multiplex Real-Time PCR Kit in Comparison with the BioFire Respiratory Panel

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) and influenza viruses may pose enormous challenges to our healthcare system. We evaluated the performance of the PowerChek SARS-CoV-2, Influenza A & B Multiplex Real-time PCR Kit (PowerChek; Kogene Biotech, Seoul, Korea) in comparison with the BioFire Respiratory Panels 2 and 2.1 (RP2 and RP2.1; bioMérieux, Marcy l’Étoile, France), using 147 nasopharyngeal swabs. The limit of detection (LOD) of the PowerChek assay was determined using SARS-CoV-2, influenza A, and B RNA standards. The LOD values of the PowerChek assay for SARS-CoV-2 and influenza A and B were 1.12, 1.24, and 0.61 copies/μL, respectively. The positive and negative percent agreements of the PowerChek assay compared with RP2 and RP2.1 were 97.5% (39/40) and 100% (107/107) for SARS-CoV-2; 100% (39/39) and 100% (108/108) for influenza A; and 100% (35/35) and 100% (112/112) for influenza B, respectively. The performance of the PowerChek assay was comparable to that of RP2 and RP2.1 for detecting SARS-CoV-2 and influenza A and B, suggesting its use in diagnosing SARS-CoV-2 and influenza infections.

Significance of digestive symptoms after COVID-19 vaccination: A retrospective single-center study

Objective

There is insufficient research on digestive symptoms and outcomes following coronavirus disease (COVID-19) vaccination. We aimed to investigate digestive symptoms and related complications among South Koreans who were administered COVID-19 vaccines.

Methods

Forty-six patients (men: 22, women: 24) with a median age of 68 years (interquartile range:55.5, 73.8 years) who experienced digestive symptoms following COVID-19 vaccination between March 1 and July 30, 2021, were included. This retrospective single-center study collected information on clinical symptoms, laboratory tests, imaging results, comorbidities, complications, treatment type, and prognosis.

Results

Thirty-three (71.7%), nine (19.6%), and three (6.5%) patients were administered AZD1222 (AstraZeneca), BNT162b2 (Pfizer/BioNTech), and JNJ-78436735 (Johnson and Johnson) vaccines, respectively. Patients were classified with mild (25 patients, 54.3%), moderate (five patients, 10.9%), and severe (16 patients, 34.8%) based on disease severity. Digestive symptoms included abdominal pain, diarrhea, dyspepsia, and nausea, which usually developed within 1 day (78.3%) following the first vaccination. In total, 14 (30.4%) patients experienced only gastrointestinal symptoms, whereas 32 (69.6%) experienced non-gastrointestinal symptoms. Complications included enterocolitis (76%), acute kidney injury (9%), anaphylactoid reaction (2%), and duodenal perforation (2%).

Conclusions

COVID-19 vaccines caused digestive symptoms and other complications that ranged from mild to severe. While further validation is required, our results suggest that monitoring digestive symptoms following COVID-19 vaccination can help detect rather severe complications that require medical intervention.

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.

Antibody levels remain high to one-year's follow-up after moderate and severe COVID-19, but not after mild cases

BACKGROUND

Understanding the longevity of antibodies against SARS-CoV-2 infection is of utmost importance in predicting the further course of the pandemic and to plan vaccination strategies. Here we report a cohort of COVID-19 patients with different disease severities whose antibody dynamics we evaluated during one-year of follow-up.

METHODS

We conducted a longitudinal study of 123 COVID-19 patients and 45 SARS CoV-2 negative outpatients with upper respiratory tract infection. We analyzed the demographic and clinical features of the patients with COVID-19 in relation to different disease severities according to the WHO classification. The antibody response was evaluated by a Luciferase Immunoprecipitation System (LIPS) assay at 3, 6, and 12 months after the acute infection.

RESULTS

Amongst the enrolled COVID-19 patients, 15 (12%) had mild, 42 (34%) had moderate, 39 (32%) had severe and 27 (22%) had critical disease courses; 79% of the patients were hospitalized. During follow-up, all patients had anti-SARS RBD-IgG levels above the cut-off value on all visits, but the antibody levels varied significantly between the different disease severity groups. Between the six- and 12-month follow-up visits, 41% of patients were vaccinated, which enhanced their antibody levels significantly.

CONCLUSION

Our data demonstrate sustained antibody levels at one-year after moderate and severe COVID-19 infection. Vaccination of patients with the mild disease is important to raise the antibody levels to a protective level.

Influenza is More Severe than Our Newest Enemy (COVID-19) in Hospitalized Children: Experience from a Tertiary Center

Understanding differences in terms of clinical phenotypes and outcomes of coronavirus disease 2019 (COVID‐19) compared with influenza is vital to optimizing the management of patients and planning healthcare. Herein, we aimed to investigate the clinical differences and outcomes in hospitalized patients with severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) and influenza. We performed a retrospective study of hospitalized children who were positive for SARS‐CoV‐2 between March 2020 and March 2021 and for influenza between January 2016 and February 2020 in respiratory samples. The primary outcome of this study was pediatric intensive care unit (PICU) admission, and the secondary outcome was the need for respiratory support. A total of 74 patients with influenza and 71 who were positive for SARS‐CoV‐2 were included. The distribution among the sexes was similar, but patients with COVID‐19 were older than patients with influenza (96 vs. 12, p < 0.001). In terms of underlying chronic diseases, the frequency was 26.7% in the COVID‐19 group and 54% in the influenza group (p = 0.001). The comparison of symptoms revealed that fatigue, headache, nausea, vomiting, and abdominal pain occurred more frequently with COVID‐19 (for all p < 0.05) and runny nose with influenza (p = 0.002). The frequency of admission to the PICU was relatively higher (18.9%) in the influenza group than with COVID‐19 (2.8%) with a significant ratio (p = 0.001), secondary bacterial infections were observed more frequently in the influenza group (20.2% vs. 4.2%, p = 0.003). Some 88.7% of patients with COVID‐19 did not need respiratory support, whereas 59.4% of patients with influenza did require respiratory support (p < 0.001). This study noted that influenza caused more frequent admissions to the PICU and a greater need for respiratory support in hospitalized pediatric patients than COVID‐19.

Differential anchoring effects of vaccination comparator selection: characterizing a potential bias due to healthcare utilization in COVID-19 versus influenza

Background

Observational data enables large-scale vaccine safety surveillance but requires careful evaluation of the potential sources of bias. One potential source of bias is the index date selection procedure for the unvaccinated cohort or unvaccinated comparison time (“anchoring”).

Objective

Here, we evaluated the different index date selection procedures for 2 vaccinations: COVID-19 and influenza.

Methods

For each vaccine, we extracted patient baseline characteristics on the index date and up to 450 days prior and then compared them to the characteristics of the unvaccinated patients indexed on (1) an arbitrary date or (2) a date of a visit. Additionally, we compared vaccinated patients indexed on the date of vaccination and the same patients indexed on a prior date or visit.

Results

COVID-19 vaccination and influenza vaccination differ drastically from each other in terms of the populations vaccinated and their status on the day of vaccination. When compared to indexing on a visit in the unvaccinated population, influenza vaccination had markedly higher covariate proportions, and COVID-19 vaccination had lower proportions of most covariates on the index date. In contrast, COVID-19 vaccination had similar covariate proportions when compared to an arbitrary date. These effects attenuated, but were still present, with a longer lookback period. The effect of day 0 was present even when the patients served as their own controls.

Conclusions

Patient baseline characteristics are sensitive to the choice of the index date. In vaccine safety studies, unexposed index event should represent vaccination settings. Study designs previously used to assess influenza vaccination must be reassessed for COVID-19 to account for a potentially healthier population and lack of medical activity on the day of vaccination.

Clinical Characteristics, Risk Factors for Severity and Pharmacotherapy in Hospitalized COVID-19 Patients in the United Arab Emirates

Data on the clinical characteristics, severity and management of COVID-19 from the Middle East region, especially the United Arab Emirates (UAE), is very limited. We studied the clinical characteristics, laboratory biomarkers, risk factors for severity and pharmacotherapy of hospitalized COVID-19 patients in this single-center, analytical cross-sectional study conducted in a secondary care hospital of the UAE. A total of 585 patients were included in the study (median age, 49 years (IQR, 39−59); 66% male). Age > 45 years (OR = 2.07, 95% CI: 1.04−4.14, p = 0.040), male gender (OR = 3.15, 95% CI: 1.52−6.51, p = 0.002), presentation symptoms such as fever (OR = 3.68, 95% CI:1.34−10.11, p = 0.011) and shortness of breath/dyspnea (OR = 5.36, 95% CI: 2.69−10.67, p < 0.001), Hb < 13 g/dL (OR = 3.17, 95% CI: 1.51−6.65, p = 0.002), neutrophils > 7 × 103/mcL (OR = 4.89, 95% CI: 1.66−14.37, p=0.004), lymphocytes < 1 × 103/mcL (OR = 7.78, 95% CI: 1.01−60.19, p = 0.049), sodium < 135 mmol/L (OR = 5.42, 95% CI: 1.05−27.95, p = 0.044), potassium < 3.6 mmol/L (OR = 3.36, 95% CI: 1.03−11.01, p = 0.045), urea > 6.5 mmol/L (OR = 3.37, 95% CI: 1.69−6.73, p = 0.001) and LDH > 227 IU/L (OR = 6.26, 95% CI: 1.61−24.32, p = 0.008) were independent predictors of the severity of COVID-19. Antivirals (524, 89.6%) and corticosteroids (358, 61.2%) were prescribed for the management of COVID-19. In conclusion, older age, male gender, presentation symptoms such as fever and dyspnea, low hemoglobin, neutrophilia, lymphopenia, hyponatremia, hypokalemia, elevated levels of urea and lactate dehydrogenase were found to be independent risk factors for severe COVID-19. The pharmacotherapy of COVID-19 patients in our study was diverse, and the medications were prescribed based on the clinical condition of the patients.

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.

Molecular Evidence of Coinfection with Acute Respiratory Viruses and High Prevalence of SARS-CoV-2 among Patients Presenting Flu-Like Illness in Bukavu City, Democratic Republic of Congo

The coronavirus disease 2019 (COVID-19) is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), with clinical manifestation cases that are almost similar to those of common respiratory viral infections. This study determined the prevalence of SARS-CoV-2 and other acute respiratory viruses among patients with flu-like symptoms in Bukavu city, Democratic Republic of Congo. We screened 1352 individuals with flu-like illnesses seeking treatment in 10 health facilities. Nasopharyngeal swab specimens were collected to detect SARS-CoV-2 using real-time reverse transcription-polymerase chain reaction (RT-PCR), and 10 common respiratory viruses were detected by multiplex reverse transcription-polymerase chain reaction assay. Overall, 13.9% (188/1352) of patients were confirmed positive for SARS-CoV-2. Influenza A 5.6% (56/1352) and Influenza B 0.9% (12/1352) were the most common respiratory viruses detected. Overall, more than two cases of the other acute respiratory viruses were detected. Frequently observed symptoms associated with SARS-CoV-2 positivity were shivering (47.8%; OR = 1.8; CI: 0.88–1.35), cough (89.6%; OR = 6.5, CI: 2.16–28.2), and myalgia and dizziness (59.7%; OR = 2.7; CI: 1.36–5.85). Moreover, coinfection was observed in 12 (11.5%) specimens. SARS-CoV-2 and influenza A were the most cooccurring infections, accounting for 33.3% of all positive cases. This study demonstrates cases of COVID-19 infections cooccurring with other acute respiratory infections in Bukavu city during the ongoing outbreak of COVID-19. Therefore, testing for respiratory viruses should be performed in all patients with flu-like symptoms for effective surveillance of the transmission patterns in the COVID-19 affected areas for optimal treatment and effective disease management.