Diagnostic accuracy of a rapid RT-PCR assay for point-of-care detection of influenza A/B virus at emergency department admission: A prospective evaluation during the 2017/2018 influenza season

A SARS-CoV-2 and influenza rapid antigen test-based hospital isolation policy awaiting RT-PCR, a prospective observational study

OBJECTIVES

This study aimed to evaluate the clinical performance of a combined SARS-CoV-2/influenza rapid antigen test (SIRAT) and to evaluate a SIRAT-based hospital isolation policy awaiting RT-PCR results for patients presenting at the emergency department (ED).

METHODS

We performed a prospective observational study including all adult patients presenting with influenza-like symptoms at the ED of two hospitals from 31 October 2022 to 31 March 2023. A SIRAT and SARS-CoV-2 and influenza RT-PCR were performed on upper respiratory samples. SIRAT results were compared with RT-PCR. Droplet and contact isolation measures (DCIM) were imposed based on SIRAT results awaiting RT-PCR. We monitored symptomatic nosocomial SARS-CoV-2 and influenza infections potentially caused by delayed isolation of patients with false negative SIRAT and the hours of unnecessary DCIM saved.

RESULTS

We included 1740 patients of whom 1296 were hospitalized. SARS-CoV-2 and influenza A/B prevalence were 12.7% (221/1740) and 9.9% (171/1740). Sensitivity and specificity of the SIRAT were 67.7% (95% CI 61.1-73.9%) (149/220) and 99.4% (95% CI 99.0-99.8%) (1510/1518) for SARS-CoV-2 and 52.7% (95% CI 44.9-60.4%) (89/169) and 99.1% (95% CI 98.5-99.5%) (1530/1544) for influenza A/B. We found a 0% nosocomial transmission risk for SARS-CoV-2 (95% CI 0-8.8%) and influenza (95% CI 0-10%). In all, 8712 hours in total or a median up to 6 hours 59 minutes (IQR (interquartile range) 11h03) per patient of unnecessary DCIM were saved.

DISCUSSION

A SIRAT-guided hospital isolation policy awaiting RT-PCR results for patients who present at the ED can save unnecessary isolation hours without having to lead to significant symptomatic nosocomial transmission of SARS-CoV-2 or influenza viruses.

Managing Viral Emerging Infectious Diseases via Current and Future Molecular Diagnostics

Emerging viral infectious diseases have been a constant threat to global public health in recent times. In managing these diseases, molecular diagnostics has played a critical role. Molecular diagnostics involves the use of various technologies to detect the genetic material of various pathogens, including viruses, in clinical samples. One of the most commonly used molecular diagnostics technologies for detecting viruses is polymerase chain reaction (PCR). PCR amplifies specific regions of the viral genetic material in a sample, making it easier to detect and identify viruses. PCR is particularly useful for detecting viruses that are present in low concentrations in clinical samples, such as blood or saliva. Another technology that is becoming increasingly popular for viral diagnostics is next-generation sequencing (NGS). NGS can sequence the entire genome of a virus present in a clinical sample, providing a wealth of information about the virus, including its genetic makeup, virulence factors, and potential to cause an outbreak. NGS can also help identify mutations and discover new pathogens that could affect the efficacy of antiviral drugs and vaccines. In addition to PCR and NGS, there are other molecular diagnostics technologies that are being developed to manage emerging viral infectious diseases. One of these is CRISPR-Cas, a genome editing technology that can be used to detect and cut specific regions of viral genetic material. CRISPR-Cas can be used to develop highly specific and sensitive viral diagnostic tests, as well as to develop new antiviral therapies. In conclusion, molecular diagnostics tools are critical for managing emerging viral infectious diseases. PCR and NGS are currently the most commonly used technologies for viral diagnostics, but new technologies such as CRISPR-Cas are emerging. These technologies can help identify viral outbreaks early, track the spread of viruses, and develop effective antiviral therapies and vaccines.

Evaluation of missed influenza vaccination opportunities in the emergency department

BACKGROUND

Seasonal influenza is associated with significant healthcare resource utilization. An estimated 490,000 hospitalizations and 34,000 deaths were attributed to influenza during the 2018-2019 season. Despite robust influenza vaccination programs in both the inpatient and outpatient setting, the emergency department (ED) represents a missed opportunity to vaccinate patients at high risk for influenza who do not have access to routine preventive care. Feasibility and implementation of ED-based influenza vaccination programs have been previously described but have stopped short of describing the predicted health resource impact. The goal of our study was to describe the potential impact of an influenza vaccination program in an urban adult emergency department population using historic patient data.

METHODS

This was a retrospective study of all encounters within a tertiary care hospital-based ED and three freestanding EDs during influenza season (defined as October 1 - April 30) over a two-years, 2018-2020. Data was obtained from the electronic medical record (EPIC®). All ED encounters during the study period were screened for inclusion using ICD 10 codes. Patients with a confirmed positive influenza test and no documented influenza vaccine for the current season were reviewed for any ED encounter at least 14 days prior to the influenza-positive encounter and during the concurrent influenza season. These ED visits were deemed a missed opportunity to provide vaccination and potentially prevent the influenza-positive encounter. Healthcare resource utilization, including subsequent ED encounters and inpatient admissions, were evaluated for patients with a missed vaccination opportunity.

RESULTS

A total of 116,140 ED encounters occurred during the study and were screened for inclusion. Of these, 2115 were influenza-positive encounters, which represented 1963 unique patients. There were 418 patients (21.3%) that had a missed opportunity to be vaccinated during an ED encounter at least 14 days prior to the influenza-positive encounter. Of those with a missed vaccination opportunity, 60 patients (14.4%) had subsequent influenza-related encounters, including 69 ED visits and 7 inpatient admissions.

CONCLUSION

Patients presenting to the ED with influenza frequently had opportunities to be vaccinated during prior ED encounters. An ED-based influenza vaccination program could potentially reduce influenza-related burden on healthcare resources by preventing future influenza-related ED encounters and hospitalizations.

Determination of the frequency of influensa-A and B antigens in swab samples in differentiating the diagnosis of influensa infection from other causes of upper respiratory tract infection

Aim: The aim of this study is to determine the frequency of influenza-A and B antigens in swab samples and to examine their potential changes at the time of initial diagnosis in differentiating the diagnosis of influenza infection from other causes of upper respiratory tract infection by physical examination and clinical vital signs in the emergency room. Materials and Methods: This retrospective cross-sectional descriptive research analyzed 113 patients with Influensa-A (n:8 and B (n:15) over the age of 18 who applied to the emergency department in the last three years, were diagnosed with acute upper respiratory tract and underwent nasopharyngeal swab sampling were included in the study. The data of the patients were accessed digitally from the University hospital database. Results: Verbal dysphagia scores (p0.05). White blood cells in blood count parameters were lower in the influenza test-positive group (p0.05). Conclusion: Influenza infections should be examined in detail regarding costs to public health and social security institutions, considering the burdens of diagnosis and treatment on the patient and society.

Comparing the cobas Influenza A/B Nucleic acid test for use on the cobas Liat System (Liat) with rapid antigen tests for clinical management of Japanese patients at the point of care

Background

Rapid diagnosis of influenza is critical in preventing the spread of infection and ensuring patients quickly receive antiviral medication to reduce the severity and duration of influenza symptoms, whilst controlling the spread of the causative virus. In Japan patients are often administered anti-influenza medication following a positive rapid antigen detection test (RADT) result. However, the sensitivity of RADTs can lead to false negative results. The cobas^® Influenza A/B Nucleic acid test for use on the cobas Liat^® System (Liat) is a molecular point-of-care method that can provide a more sensitive alternative to RADTs for rapid influenza diagnosis and treatment.

Methods

In this prospective multicenter study, diagnostic performance of the Liat test was compared with RADTs in patients presenting with influenza-like-illness. Test performance was also assessed by time since symptom onset.

Results

Of 419 patients enrolled, 413 were evaluable for all designated tests. Most patients had type-A infection, and only one patient had influenza type B. In 413 patients, the sensitivity and specificity (95% CI) of the Liat test were 99.5% (97.2–99.9%) and 99.5% (97.4–99.9%), respectively, and were 79.7% (73.5–84.7%) and 95.4% (91.7–97.5%) for RADTs. For patients tested <12 hours from symptom onset, the Liat test had significantly higher sensitivity than RADTs (p<0.0001).

Conclusion

Overall, compared with standard of care RADTs, the Liat test was more sensitive and specific in children and adults, particularly in the early stages of infection. Greater sensitivity can enable earlier diagnosis and may better inform appropriate antiviral treatment decisions.

Incidence of respiratory virus illness and hospitalizations in a Panama and El Salvador birth cohort, 2014-2018

Background

Respiratory viruses remain a key cause of early childhood illness, hospitalization, and death globally.The recent pandemic has rekindled interest in the control of respiratory viruses among paediatric populations. We estimate the burden of such viruses among children <2 years.

Methods

Enrolled neonates were followed until two years of age. Weekly active symptom monitoring for the development of acute respiratory illnesses (ARI) defined as cough, rhinorrhoea, difficulty breathing, asthenia, anorexia, irritability, or vomiting was conducted. When the child had ARI and fever, nasopharyngeal swabbing was performed, and samples were tested through singleplex RT-PCR. Incidence of respiratory viruses was calculated by dividing the number of laboratory-confirmed detections by the person-time accrued during weeks when that virus was detectable through national surveillance then corrected for under-ascertainment among untested children.

Findings

During December 2014-November 2017, 1567 enrolled neonates contributed 2,186.9 person-years (py). Six in ten (64·4%) children developed ARI (total 2493 episodes). Among children <2 years, incidence of respiratory syncytial virus (RSV)-associated ARI episodes (21·0, 95%CI 19·3-22·8, per 100py) and rhinovirus-associated (20·5, 95%CI 20·4-20·7) were similar and higher than parainfluenza 1-3-associated (14·2, 95%CI 12·2-16·1), human metapneumovirus-associated (9·2, 95%CI 7·7-10·8), influenza-associated (5·9, 95%CI 4·4-7·5), and adenovirus-associated ARI episodes (5·1, 95%CI 5·0-5·2). Children aged <3 months had the highest rates of RSV ARI (49·1, 95%CI 44·0-54·1 per 100py) followed by children aged 3-5 (25·1, 95%CI 20·1-30·0), 6-11 (17·6, 95%CI 13·2-21·9), and 12-23 months (11·9, 95%CI 10·8-12·9). One in ten children with RSV was referred to the hospital (2·5, 95%CI 2·1-2·8, per 100py).

Interpretation

Children frequently developed viral ARI and a substantive proportion required hospital care. Such findings suggest the importance of exploring the value of new interventions and increasing uptake of existing prevention measures to mitigate burden of epidemic-prone respiratory viruses.

Funding

The study was supported by the Centers for Disease Control and Prevention.

Quantitative reverse transcription PCR assay to detect a genetic marker of pyrethroid resistance in Culex mosquitoes

Pyrethroid insecticides are widely used to control mosquitoes that transmit pathogens such as West Nile virus (WNV) to people. Single nucleotide polymorphisms (SNP) in the knockdown resistance locus (kdr) of the voltage gated sodium channel (Vgsc) gene in Culex mosquitoes are associated with knockdown resistance to pyrethroids. RNAseq was used to sequence the coding region of Vgsc for Culex tarsalis Coquillett and Culex erythrothorax Dyar, two WNV vectors. The cDNA sequences were used to develop a quantitative reverse transcriptase PCR assay that detects the L1014F kdr mutation in the Vgsc. Because this locus is conserved, the assay was used successfully in six Culex spp. The resulting Culex RTkdr assay was validated using quantitative PCR and sequencing of PCR products. The accuracy of the Culex RTkdr assay was 99%. The L1014F kdr mutation associated with pyrethroid resistance was more common among Cx. pipiens than other Culex spp. and was more prevalent in mosquitoes collected near farmland. The Culex RTkdr assay takes advantage of the RNA that vector control agencies routinely isolate to assess arbovirus prevalence in mosquitoes. We anticipate that public health and vector control agencies may employ the Culex RTkdr assay to define the geographic distribution of the L1014F kdr mutation in Culex species and improve the monitoring of insecticide resistance that will ultimately contribute to effective control of Culex mosquitoes.

Effect of a multimodal strategy for prevention of nosocomial influenza: a retrospective study at Grenoble Alpes University Hospital from 2014 to 2019

Background

A multimodal strategy to prevent nosocomial influenza was implemented in 2015–2016 in Grenoble Alpes University Hospital. Three modalities were implemented in all units: promotion of vaccination among healthcare workers, epidemiologic surveillance and communication campaigns. Units receiving a high number of patients with influenza implemented 2 additional modalities: improvement of diagnosis capacities and systematic surgical mask use. The main objective was to assess the effectiveness of the strategy for reducing the risk of nosocomial influenza.

Methods

A study was conducted retrospectively investigating 5 epidemic seasons (2014–2015 to 2018–2019) including all patients hospitalized with a positive influenza test at Grenoble Alpes University Hospital. The weekly number of nosocomial influenza cases was analyzed by Poisson regression and incidence rate ratios (IRR) were estimated.

Results

A total of 1540 patients, resulting in 1559 stays, were included. There was no significant difference between the 5 influenza epidemic seasons in the units implementing only 3 measures. In the units implementing the 5 measures, there was a reduction of nosocomial influenza over the seasons when the strategy was implemented compared to the 2014–2015 epidemic season (IRR = 0.56, 95% CI = 0.23–1.34 in 2015–2016; IRR = 0.39, 95% CI = 0.19–0.81 in 2016–2017; IRR = 0.50, 95% CI = 0.24–1.03 in 2017–2018; IRR = 0.48, 95% CI = 0.23–0.97 in 2018–2019).

Conclusions

Our data mainly suggested that the application of the strategy with 5 modalities, including systematic surgical mask use and rapid diagnosis, seemed to reduce by half the risk of nosocomial influenza. Further data, including medico-economic studies, are necessary to determine the opportunity of extending these measures at a larger scale.

Effect of point-of-care influenza tests on antibiotic prescriptions by emergency physicians in a French hospital

BACKGROUND

Influenza is a public health issue worldwide. Although antibiotics should not be used to treat viral infections, they are often prescribed to patients with influenza-like illness (ILI). Such misuse promotes antibiotic resistance. The role of rapid point-of-care tests (POCT) in preventing antibiotic misuse in adults with ILI symptoms remains relatively unexplored.

AIM

To evaluate whether POCT implemented in 2018-2019 to detect influenza viruses lead to a decrease in antibiotic prescriptions compared to laboratory based influenza tests.

METHODS

Adult patients with ILI in one emergency department (ED) were retrospectively enrolled over three epidemic seasons (from 2016-2017 to 2018-2019). The primary outcome was the rate of antibiotic prescriptions, which was compared between the three seasons in bivariate and multivariate analyses. Prescriptions for ancillary laboratory tests, chest X-rays and oseltamivir were also compared, along with hospitalisations and length of stay (LOS) at the ED.

FINDINGS

Overall, 1849 patients were included. Median age was over 70 throughout all three seasons. The number of antibiotic prescriptions was significantly different between the three periods in bivariate analysis (48.3% in 2016/2017, 44% in 2017/2018 and 31.1% in 2018/2019; p<0,0001) and in multivariate analysis (adjusted Odds Ratio [aOR]=0.48, 95%CI=0.30-0.76 for 2018/2019 and aOR=0.99, 95%CI=0.67-1.46 for 2017/2018, compared to 2016/2017). There were significantly fewer prescriptions of ancillary laboratory tests, X-rays, hospitalisations and more oseltamivir prescriptions in 2018/2019, compared to the previous seasons. LOS was significantly lower in 2018/2019 only for influenza-positive patients.

CONCLUSION

ED influenza POCT decreased antibiotic use and lead to less ancillary testing, X-rays and hospitalisations among patients with ILI. However, medico-economic studies are necessary before formulating definite recommendations.

Pathogenesis and Treatment of Cytokine Storm Induced by Infectious Diseases

Cytokine storm is a phenomenon characterized by strong elevated circulating cytokines that most often occur after an overreactive immune system is activated by an acute systemic infection. A variety of cells participate in cytokine storm induction and progression, with profiles of cytokines released during cytokine storm varying from disease to disease. This review focuses on pathophysiological mechanisms underlying cytokine storm induction and progression induced by pathogenic invasive infectious diseases. Strategies for targeted treatment of various types of infection-induced cytokine storms are described from both host and pathogen perspectives. In summary, current studies indicate that cytokine storm-targeted therapies can effectively alleviate tissue damage while promoting the clearance of invading pathogens. Based on this premise, "multi-omics" immune system profiling should facilitate the development of more effective therapeutic strategies to alleviate cytokine storms caused by various diseases.

Feasibility of Radiomics to Differentiate Coronavirus Disease 2019 (COVID-19) from H1N1 Influenza Pneumonia on Chest Computed Tomography: A Proof of Concept

BACKGROUND

Chest computed tomography (CT) plays an essential role in diagnosing coronavirus disease 2019 (COVID-19). However, CT findings are often nonspecific among different viral pneumonia conditions. The differentiation between COVID-19 and influenza can be challenging when seasonal influenza concurs with the COVID-19 pandemic. This study was conducted to test the ability of radiomics-artificial intelligence (AI) to perform this task.

METHODS

In this retrospective study, chest CT images from 47 patients with COVID-19 (after February 2020) and 19 patients with H1N1 influenza (before September 2019) pneumonia were collected from three hospitals affiliated with Arak University of Medical Sciences, Arak, Iran. All pulmonary lesions were segmented on CT images. Multiple radiomics features were extracted from the lesions and used to develop support-vector machine (SVM), k-nearest neighbor (k-NN), decision tree, neural network, adaptive boosting (AdaBoost), and random forest.

RESULTS

The patients with COVID-19 and H1N1 influenza were not significantly different in age and sex (P=0.13 and 0.99, respectively). Nonetheless, the average time between initial symptoms/hospitalization and chest CT was shorter in the patients with COVID-19 (P=0.001 and 0.01, respectively). After the implementation of the inclusion and exclusion criteria, 453 pulmonary lesions were included in this study. On the harmonized features, random forest yielded the highest performance (area under the curve=0.97, sensitivity=89%, precision=90%, F1 score=89%, and classification accuracy=89%).

CONCLUSION

In our preliminary study, radiomics feature extraction, conjoined with AI, especially random forest and neural network, appeared to yield very promising results in the differentiation between COVID-19 and H1N1 influenza on chest CT.

Optical Biosensor Platforms Display Varying Sensitivity for the Direct Detection of Influenza RNA

Detection methods that do not require nucleic acid amplification are advantageous for viral diagnostics due to their rapid results. These platforms could provide information for both accurate diagnoses and pandemic surveillance. Influenza virus is prone to pandemic-inducing genetic mutations, so there is a need to apply these detection platforms to influenza diagnostics. Here, we analyzed the Fast Evaluation of Viral Emerging Risks (FEVER) pipeline on ultrasensitive detection platforms, including a waveguide-based optical biosensor and a flow cytometry bead-based assay. The pipeline was also evaluated in silico for sequence coverage in comparison to the U.S. Centers for Disease Control and Prevention's (CDC) influenza A and B diagnostic assays. The influenza FEVER probe design had a higher tolerance for mismatched bases than the CDC's probes, and the FEVER probes altogether had a higher detection rate for influenza isolate sequences from GenBank. When formatted for use as molecular beacons, the FEVER probes detected influenza RNA as low as 50 nM on the waveguide-based optical biosensor and 1 nM on the flow cytometer. In addition to molecular beacons, which have an inherently high background signal we also developed an exonuclease selection method that could detect 500 pM of RNA. The combination of high-coverage probes developed using the FEVER pipeline coupled with ultrasensitive optical biosensors is a promising approach for future influenza diagnostic and biosurveillance applications.

Point-of-care testing for influenza in a university emergency department: A prospective study

BACKGROUND

Seasonal influenza is a burden for emergency departments (ED). The aim of this study was to investigate whether point-of-care (POC) PCR testing can be used to reduce staff sick days and improve diagnostic and therapeutic procedures.

OBJECTIVES

The aim of this study was to investigate whether point-of-care (POC) PCR testing can be used to reduce staff sick days and improve diagnostic and therapeutic procedures.

METHODS

Using a cross-over design, the cobas® Liat® Influenza A/B POC PCR test (Liat) was compared with standard clinical practice during the 2019/2020 influenza season. All adult patients (aged ≥ 18 years) with fever (≥38°C) and respiratory symptoms were included. Primary end points were the prevalence of influenza infections in the ED and staff sick days. Secondary end points were frequency of antiviral and antibacterial therapy, time between admission and test result or treatment initiation, patient disposition, ED length of stay (LOS), and for inpatients mortality and LOS. Nurses were interviewed about handling and integration of POC testing. The occurrence of SARS-CoV-2 infections coincided with the second half of the study.

RESULTS

A total of 828 patients were enrolled in the study. All 375 patients of the intervention group were tested with Liat, and 103 patients of them (27.6%) tested positive. During the intervention period, staff sick days were reduced by 34.4% (P = .023). Significantly, more patients in the intervention group received antiviral therapy with neuraminidase inhibitors (7.2% vs 3.8%, P = .028) and tested patients received antibiotics more frequently (40.0% vs 31.6%, P = .033). Patients with POC test were transferred to external hospitals significantly more often (5.6% vs 1.3%, P = .01).

CONCLUSION

We conclude that POC testing for influenza is useful in the ED, especially if it is heavily frequented by patients with respiratory symptoms.

Screening of Additive Formulations Enables Off-Chip Drop Reverse Transcription Quantitative Polymerase Chain Reaction of Single Influenza A Virus Genomes

The miniaturization of polymerase chain reaction (PCR) using drop-based microfluidics allows for amplification of single nucleic acids in aqueous picoliter-sized drops. Accurate data collection during PCR requires that drops remain stable to coalescence during thermocycling and drop contents are retained. Following systematic testing of known PCR additives, we identified an optimized formulation of 1% w/v Tween-20, 0.8 μg/μL bovine serum albumin, 1 M betaine in the aqueous phase, and 3 wt % (w/w) of the polyethylene glycol-perfluoropolyether₂ surfactant in the oil phase of 50 μm diameter drops that maintains drop stability and prevents dye transport. This formulation enables a method we call off-chip drop reverse transcription quantitative PCR (OCD RT-qPCR) in which drops are thermocycled in a qPCR machine and sampled at various cycle numbers "off-chip", or outside of a microfluidic chip. qPCR amplification curves constructed from hundreds of individual drops using OCD RT-qPCR and imaged using epifluorescence microscopy correlate with amplification curves of ≈300,000 drops thermocycled using a qPCR machine. To demonstrate the utility of OCD RT-qPCR, influenza A virus (IAV) RNA was detected down to a single viral genome copy per drop, or 0.320 cpd. This work was extended to perform multiplexed detection of IAV M gene RNA and cellular β-actin DNA in drops, and direct amplification of IAV genomes from infected cells without a separate RNA extraction step. The optimized additive formulation and the OCD-qPCR method allow for drop-based RT-qPCR without complex devices and demonstrate the ability to quantify individual or rare nucleic acid species within drops with minimal processing.

Diagnosis of respiratory syncytial virus and influenza A and B with cobas® Liat® from nasopharyngeal aspirations in pediatrics

The cobas® Liat® Influenza A/B and respiratory syncytial virus assay was tested on nasopharyngeal aspirates. The resolution of invalid samples was performed using a preanalytical step. cobas® Liat® can be used on nasopharyngeal aspirates with a preanalytical processing step, with a slightly diminished performances in detecting respiratory syncytial virus but not for influenza.

Toward rapid infectious disease diagnosis with advances in surface-enhanced Raman spectroscopy

In a pandemic era, rapid infectious disease diagnosis is essential. Surface-enhanced Raman spectroscopy (SERS) promises sensitive and specific diagnosis including rapid point-of-care detection and drug susceptibility testing. SERS utilizes inelastic light scattering arising from the interaction of incident photons with molecular vibrations, enhanced by orders of magnitude with resonant metallic or dielectric nanostructures. While SERS provides a spectral fingerprint of the sample, clinical translation is lagged due to challenges in consistency of spectral enhancement, complexity in spectral interpretation, insufficient specificity and sensitivity, and inefficient workflow from patient sample collection to spectral acquisition. Here, we highlight the recent, complementary advances that address these shortcomings, including (1) design of label-free SERS substrates and data processing algorithms that improve spectral signal and interpretability, essential for broad pathogen screening assays; (2) development of new capture and affinity agents, such as aptamers and polymers, critical for determining the presence or absence of particular pathogens; and (3) microfluidic and bioprinting platforms for efficient clinical sample processing. We also describe the development of low-cost, point-of-care, optical SERS hardware. Our paper focuses on SERS for viral and bacterial detection, in hopes of accelerating infectious disease diagnosis, monitoring, and vaccine development. With advances in SERS substrates, machine learning, and microfluidics and bioprinting, the specificity, sensitivity, and speed of SERS can be readily translated from laboratory bench to patient bedside, accelerating point-of-care diagnosis, personalized medicine, and precision health.

[Virological diagnosis of lower respiratory tract infections]

INTRODUCTION

The etiological diagnosis of bronchopulmonary infections cannot be assessed with clinical, radiological and epidemiological data alone. Viruses have been demonstrated to cause a large proportion of these infections, both in children and adults.

BACKGROUND

The diagnosis of viral bronchopulmonary infections is based on the analysis of secretions, collected from the lower respiratory tract when possible, by techniques that detect either influenza and respiratory syncytial viruses, or a large panel of viruses that can be responsible for respiratory disease. The latter, called multiplex PCR assays, allow a syndromic approach to respiratory infection. Their high cost for the laboratory raises the question of their place in the management of patients in terms of antibiotic economy and isolation. In the absence of clear recommendations, the strategy and equipment are very unevenly distributed in France.

OUTLOOK

Medico-economic analyses need to be performed in France to evaluate the place of these tests in the management of patients. The evaluation of the role of the different viruses often detected in co-infection, especially in children, also deserves the attention of virologists and clinicians.

CONCLUSIONS

The availability of new diagnostic technologies, the recent emergence of SARS-CoV-2, together with the availability of new antiviral drugs are likely to impact future recommendations for the management of viral bronchopulmonary infections.

Impact of Rapid Influenza Molecular Testing on Management in Pediatric Acute Care Settings

OBJECTIVES

To measure the impact of rapid influenza real-time qualitative reverse transcriptase polymerase chain reaction (RT-PCR) on patient management in busy pediatric emergency department (ED) and urgent care clinic settings.

STUDY DESIGN

We developed a brief, elective survey that clinicians completed when an influenza RT-PCR order was placed in the ED or urgent care clinic between February 18, 2019, and March 13, 2019. We captured the clinical suspicion for influenza, intended management plans, and actual management plans once influenza RT-PCR results were available.

RESULTS

We evaluated 339 encounters, of which 164 (48.4%) had a positive influenza RT-PCR. Clinical suspicion for influenza was a nonsignificant predictor for influenza PT-PCR positivity (P = .126). After rapid influenza RT-PCR results were available, clinicians changed their original plans in 44.5% of influenza RT-PCR positive vs 92.6% of influenza RT-PCR negative cases (P < .0001). Change in plans for antiviral use was observed in 26% of influenza positive vs 77% of influenza negative cases (P < .0001). A total of 135 antiviral prescriptions were avoided in patients with negative influenza RT-PCR.

CONCLUSIONS

Implementation of a rapid and accurate influenza RT-PCR in the acute care setting is important to systematically diagnose influenza in children and improve outpatient management decisions, because clinical suspicion for influenza is inaccurate. A negative influenza RT-PCR decreases unnecessary antiviral use and has the potential for significant cost savings.

COVID-19 Pandemic and Upcoming Influenza Season-Does an Expert's Computed Tomography Assessment Differentially Identify COVID-19, Influenza and Pneumonias of Other Origin?

(1) Background: Time-consuming SARS-CoV-2 RT-PCR suffers from limited sensitivity in early infection stages whereas fast available chest CT can already raise COVID-19 suspicion. Nevertheless, radiologists' performance to differentiate COVID-19, especially from influenza pneumonia, is not sufficiently characterized. (2) Methods: A total of 201 pneumonia CTs were identified and divided into subgroups based on RT-PCR: 78 COVID-19 CTs, 65 influenza CTs and 62 Non-COVID-19-Non-influenza (NCNI) CTs. Three radiology experts (blinded from RT-PCR results) raised pathogen-specific suspicion (separately for COVID-19, influenza, bacterial pneumonia and fungal pneumonia) according to the following reading scores: 0-not typical/1-possible/2-highly suspected. Diagnostic performances were calculated with RT-PCR as a reference standard. Dependencies of radiologists' pathogen suspicion scores were characterized by Pearson's Chi2 Test for Independence. (3) Results: Depending on whether the intermediate reading score 1 was considered as positive or negative, radiologists correctly classified 83-85% (vs. NCNI)/79-82% (vs. influenza) of COVID-19 cases (sensitivity up to 94%). Contrarily, radiologists correctly classified only 52-56% (vs. NCNI)/50-60% (vs. COVID-19) of influenza cases. The COVID-19 scoring was more specific than the influenza scoring compared with suspected bacterial or fungal infection. (4) Conclusions: High-accuracy COVID-19 detection by CT might expedite patient management even during the upcoming influenza season.

COVID-19 or non-COVID viral pneumonia: How to differentiate based on the radiologic findings?

Influenza viruses were responsible for most adult viral pneumonia. Presently, coronavirus disease 2019 (COVID-19) has evolved into serious global pandemic. COVID-19 outbreak is expected to persist in months to come that will be synchronous with the influenza season. The management, prognosis, and protection for these two viral pneumonias differ considerably and differentiating between them has a high impact on the patient outcome. Reverse transcriptase polymerase chain reaction is highly specific but has suboptimal sensitivity. Chest computed tomography (CT) has a high sensitivity for detection of pulmonary disease manifestations and can play a key-role in diagnosing COVID-19. We reviewed 47 studies and delineated CT findings of COVID-19 and influenza pneumonia. The differences observed in the chest CT scan can be helpful in differentiation. For instance, ground glass opacities (GGOs), as the most frequent imaging finding in both diseases, can differ in the pattern of distribution. Peripheral and posterior distribution, multilobular distribution, pure or clear margin GGOs were more commonly reported in COVID-19, whereas central or peri-bronchovascular GGOs and pure consolidations were more seen in influenza A (H1N1). In review of other imaging findings, further differences were noticed. Subpleural curvilinear lines, sugar melted sign, intra-lesional vascular enlargement, reverse halo sign, and fibrotic bands were more reported in COVID-19 than H1N1, while air space nodule, tree-in-bud, bronchiectasia, pleural effusion, and cavitation were more seen in H1N1. This delineation, when combined with clinical manifestations and laboratory results may help to differentiate these two viral infections.

The experience of point-of-care testing for influenza in Scotland in 2017/18 and 2018/19 – no gain without pain

Background

During the 2017/18 and 2018/19 influenza seasons, molecular amplification-based point-of-care tests (mPOCT) were introduced in Scotland to aid triaging respiratory patients for hospital admission, yet communication of results to national surveillance was unaccounted for.

Aim

This retrospective study aims to describe steps taken to capture mPOCT data and assess impact on influenza surveillance.

Methods

Questionnaires determined mPOCT usage in 2017/18 and 2018/19. Searches of the Electronic Communication of Surveillance in Scotland (ECOSS) database were performed and compared with information stored in laboratory information management systems. Effect of incomplete data on surveillance was determined by comparing routine against enhanced data and assessing changes in influenza activity levels determined by the moving epidemic method.

Results

The number of areas employing mPOCT increased over the two seasons (6/14 in 2017/18 and 8/14 in 2018/19). Analysis of a small number of areas (n = 3) showed capture of positive mPOCT results in ECOSS improved between seasons and remained high (> 94%). However, capture of negative results was incomplete. Despite small discrepancies in weekly activity assessments, routine data were able to identify trend, start, peak and end of both influenza seasons.

Conclusion

This study has shown an improvement in capture of data from influenza mPOCT and has highlighted issues that need to be addressed for results to be accurately captured in national surveillance. With the clear benefit to patient management we suggest careful consideration should be given to the connectivity aspects of the technology in order to ensure minimal impact on national surveillance.

Protective mechanical ventilation in suspected influenza infection

INTRODUCTION:

Patients with acute respiratory failure due to influenza require ventilatory support. However, mechanical ventilation itself can exacerbate lung damage and increase mortality.

METHODS:

The aim of this study was to describe a feasible and protective ventilation protocol, with limitation of the tidal volume to ≤6 mL/kg of the predicted weight and a driving pressure ≤15 cmH₂O after application of the alveolar recruitment maneuver and PEEP titration.

RESULTS:

Initial improvement in oxygenation and respiratory mechanics were observed in the four cases submitted to the proposed protocol.

CONCLUSIONS:

Our results indicate that the mechanical ventilation strategy applied could be optimized.

Molecular and Immunological Diagnostic Techniques of Medical Viruses

Viral infections are causing serious problems in human population worldwide. The recent outbreak of coronavirus disease 2019 caused by SARS-CoV-2 is a perfect example how viral infection could pose a great threat to global public health and economic sectors. Therefore, the first step in combating viral pathogens is to get a timely and accurate diagnosis. Early and accurate detection of the viral presence in patient sample is crucial for appropriate treatment, control, and prevention of epidemics. Here, we summarize some of the molecular and immunological diagnostic approaches available for the detection of viral infections of humans. Molecular diagnostic techniques provide rapid viral detection in patient sample. They are also relatively inexpensive and highly sensitive and specific diagnostic methods. Immunological-based techniques have been extensively utilized for the detection and epidemiological studies of human viral infections. They can detect antiviral antibodies or viral antigens in clinical samples. There are several commercially available molecular and immunological diagnostic kits that facilitate the use of these methods in the majority of clinical laboratories worldwide. In developing countries including Ethiopia where most of viral infections are endemic, exposure to improved or new methods is highly limited as these methods are very costly to use and also require technical skills. Since researchers and clinicians in all corners of the globe are working hard, it is hoped that in the near future, they will develop good quality tests that can be accessible in low-income countries.

Cost evaluation of point-of-care testing for community-acquired influenza in adults presenting to the emergency department

BACKGROUND

Rapid molecular point-of-care tests (POCTs) for influenza have potential to produce cost savings in emergency departments (EDs) and acute care settings. To date, published projected savings have been based on estimated costs.

OBJECTIVES

This study aimed to describe the cost implications of a rapid influenza POCT using accurate real-world patient level costing data. 204 adult patients receiving point-of-care (POC) influenza testing in the ED as part of a routine clinical service were identified retrospectively, alongside a control cohort of 104 patients from the same influenza season. Costs for all were calculated at the individual patient level. Cost comparison was performed using an instrumental variable (IV) regression to overcome potential bias within the observational dataset.

RESULTS

Patients who had a POCT on average cost 67 % less than those who did not (average cost reduction: £2066: 95 % CI: £624 and £2665). Moderate to high NEWS score at arrival, presence of ≥1 comorbidity, and age ≥70 years increased overall costs across both groups (p < 0.05).

CONCLUSIONS

Savings from POC testing can be attributed to more targeted treatments, fewer admissions and reduced lengths of stay. The IV regression results are supported by a second method (ordinary least square against baseline characteristics). They are also in line with existing work that use estimated costs but indicate greater savings than predicted previously. In conclusion, POC influenza testing in the emergency department produces significant cost savings, this is demonstrated here through an analysis using individual real-world patient level costing data.

Performance and ease of use of a molecular point-of-care test for influenza A/B and RSV in patients presenting to primary care

Annual influenza epidemics cause substantial morbidity and mortality, and the majority of patients with influenza-like illness present to primary care. Point-of-care influenza tests could support treatment decisions. It is critical to establish analytic performance of these platforms in real-life patient samples before uptake can be considered. We aimed to assess the analytical performance and ease of use of the cobas® Liat® PCR POCT in detecting influenza A/B and RSV in samples collected from patients with influenza-like illness in primary care. Sensitivity and specificity of the cobas® Liat® POCT are calculated in comparison with a commercial laboratory-based PCR test (Fast-Track Respiratory Pathogens 21 Plus kit (Fast-Track Diagnostics)). Samples with discordant results were analysed additionally by the RespiFinder 2Smart (PathoFinder) using an Extended Gold Standard (EGS). Acceptability was scored on a five-point Likert scale as well as a failure mode analysis of the cobas® Liat® POCT was performed. Nasal and oropharyngeal swabs were obtained from 140 children and nasopharyngeal swabs from 604 adults (744 patients). The cobas® Liat® POCT had a sensitivity and specificity of 100% (95% CI 99–100%) and 98.1% (95%CI 96.3–99%) for influenza A, 100% (95% CI 97.7–100%) and 99.7% (95%CI 98.7–99.9%) for influenza B and 100% (95% CI 87.1–100%) and 99.4% (95%CI 98.6–99.8%) for RSV, respectively. According to trained lab technicians, the cobas® Liat® POCT was considered easy-to-use, with a fast turn-around-time. Cobas® Liat® POCT is a promising decentralised test platform for influenza A/B and RSV in primary care as it provides fairly rapid results with excellent analytic performance. Point-of-care influenza tests could support treatment decisions in primary care. Cobas® Liat® POCT is a promising decentralised test platform for influenza A/B and RSV in primary care as it provides fairly rapid results with excellent analytic performance.

Artificial Intelligence Empowers Radiologists to Differentiate Pneumonia Induced by COVID-19 versus Influenza Viruses

Background

Given the current pandemic, differentiation between pneumonia induced by COVID-19 or influenza viruses is of utmost clinical significance in the patients' management. For this purpose, this study was conducted to develop sensitive artificial intelligence (AI) models to assist radiologists to decisively differentiate pneumonia due to COVID-19 versus influenza viruses.

Methods

Cross sectional chest CT images (N=12744) from well-evaluated cases of pneumonias induced by COVID-19 or H1N1 Influenza viruses, and normal individuals were collected. We examined the computer tomographic (CT) chest images from 137 individuals. Various pre-trained convolutional neural network models, such as ResNet-50, InceptionV3, Wide ResNet, SqueezNet, VGG 16 and VGG 19 were fine-tuned on our datasets. The datasets were used for training (60%), validation (20%), and testing (20%) of the final models. Also, the predictive power and means of precision and recall were determined for each model.

Results

Fine-tuned ResNet-50 model differentiated the pneumonia due to COVID-19 or H1N1 influenza virus with accuracies of 96.7% and 92%, respectively This model outperformed all others, i.e., InceptionV3, Wide ResNet, SqueezNet, VGG 16 and VGG 19.

Conclusion

Fine-tuned and pre-trained image classifying models of AI enable radiologists to reliably differentiate the pneumonia induced by COVID-19 versus H1N1 influenza virus. For this purpose, ResNet-50 followed by InceptionV3 models proved more promising than other AI models. Also in the supplements, we share the source codes and our fine-tuned models for use by researchers and clinicians globally toward the critical task of image differentiation of patients infected with COVID-19 versus H1N1 Influenza viruses.