Clinical Presentation and Severity of SARS-CoV-2 Infection Compared to Respiratory Syncytial Virus and Other Viral Respiratory Infections in Children Less Than Two Years of Age

SARS-CoV-2 and RSV bronchiolitis outcomes

BACKGROUND

Severe acute respiratory syndrome related coronavirus (SARS-CoV-2) bronchiolitis has arisen with the SARS-CoV-2 pandemic. There is a paucity of literature on SARS-CoV-2 bronchiolitis.

OBJECTIVE

The purpose of our paper was to review and compare outcomes in bronchiolitis due to severe acute respiratory syndrome related coronavirus 2 (SARS- CoV-2) and Respiratory Syncytial Virus (RSV). We also performed a subgroup analysis of two disrupted RSV seasons during the pandemic.

METHODS

This was a retrospective study from a US TriNetX database from March 1, 2020-January 1, 2023. Propensity matching was utilized for confounders.

RESULTS

There was a total of 3,592 patients (1,796 in each group) after propensity matching. There was an increased risk of oxygen saturation ≤95 % (RR=1.50 95 % CI 1.58-1.94, p = 0.002) and ICU admission (RR=1.44 95 % CI 1.06-1.94, p = 0.02) in those with SARS- CoV-2 but not for oxygen saturation ≤90 % (RR=1.03 95 %CI 0.75-1.42, p = 0.85) or intubation (RR=0.73 95 % CI 0.35-1.47, p = 0.37). There was a decreased risk of a patient with SARS- CoV-2 bronchiolitis being hospitalized (RR=0.65 95 % CI 0.57-0.74, p < 0.0001), respiratory rate ≥60 (RR=0.64 95 % CI 0.48-0.88, p < 0.001) or ≥70 (RR=0.64 95 % CI 0.43-0.96, p = 0.03) when compared to RSV bronchiolitis. Specifically examining SARS- CoV-2 versus RSV bronchiolitis during the delayed RSV seasons, during the first season both infections were not severe, but during the second RSV bronchiolitis season, patients infected with RSV had less risk of ICU admission compared to those infected with SARS- CoV-2.

CONCLUSION

SARS- CoV-2 bronchiolitis patients appeared to have more severe outcomes since the risk of ICU admission was higher for these patients. Also, during the second delayed RSV season, SARS- CoV-2 bronchiolitis was more severe than RSV bronchiolitis.

Epidemiological and Genetic Characteristics of Respiratory Viral Coinfections with Different Variants of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2)

This study aimed to determine the incidence and etiological, seasonal, and genetic characteristics of respiratory viral coinfections involving severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Between October 2020 and January 2024, nasopharyngeal samples were collected from 2277 SARS-CoV-2-positive patients. Two multiplex approaches were used to detect and sequence SARS-CoV-2, influenza A/B viruses, and other seasonal respiratory viruses: multiplex real-time polymerase chain reaction (PCR) and multiplex next-generation sequencing. Coinfections of SARS-CoV-2 with other respiratory viruses were detected in 164 (7.2%) patients. The most common co-infecting virus was respiratory syncytial virus (RSV) (38 cases, 1.7%), followed by bocavirus (BoV) (1.2%) and rhinovirus (RV) (1.1%). Patients ≤ 16 years of age had the highest rate (15%) of mixed infections. Whole-genome sequencing produced 19 complete genomes of seasonal respiratory viral co-pathogens, which were subjected to phylogenetic and amino acid analyses. The detected influenza viruses were classified into the genetic groups 6B.1A.5a.2a and 6B.1A.5a.2a.1 for A(H1N1)pdm09, 3C.2a1b.2a.2a.1 and 3C.2a.2b for A(H3N2), and V1A.3a.2 for the B/Victoria lineage. The RSV-B sequences belonged to the genetic group GB5.0.5a, with HAdV-C belonging to type 1, BoV to genotype VP1, and PIV3 to lineage 1a(i). Multiple amino acid substitutions were identified, including at the antibody-binding sites. This study provides insights into respiratory viral coinfections involving SARS-CoV-2 and reinforces the importance of genetic characterization of co-pathogens in the development of therapeutic and preventive strategies.

Longitudinal Cardiac Evaluation of Children with Multisystem Inflammatory Syndrome (MIS-C) Following COVID-19 by Conventional and Speckle-Tracking Echocardiography

Multisystem inflammatory syndrome in children (MIS-C), is a rare but severe, hyperinflammatory complication of COVID-19, in which cardiovascular abnormalities are frequently detected. In this prospective study, we describe the echocardiographic findings in patients with MIS-C, with the use of conventional Echocardiography and Speckle-Tracking Echocardiography (STE) with Left Ventricular (LV) Global Longitudinal Strain (GLS) analysis, in the acute and follow-up phase. In total, 25 MIS-C patients [64% females, mean (± SD) age: 8.3 (± 3.72) years] were included. In the acute phase, median (IQR) Troponin and NT-proBNP and mean heart rate, were 8.07 (14.52) pg/mL, 2875.00 (7713.00) pg/mL, and 102.87 (± 22.96) bpm, respectively. Median (IQR) LV Ejection Fraction (LVEF) was 66 (8)% and LVEF impairment was detected in 2/25 (8%) patients. On follow-up (mean time interval:9.50 ± 4.59 months), heart rate was significantly lower, with a mean value of 90.00 (± 14.56) bpm (p-value = 0.017). Median (IQR) LVEF was 66.00 (6.70)% (p-value = 0.345) and all 25 participants had normal LVEF. In 14/25 patients, additional LV-GLS analysis was performed. During the acute phase, mean LV-GLS was - 18.02 (± 4.40)%. LV-GLS was abnormal in 6/14 patients (42.9%) and among them, only one patient had reduced LVEF. On follow-up (median (IQR) time interval:6.93 (3.66) months), mean LV-GLS was -20.31 (± 1.91)% (p-value = 0.07) and in 1/14 patient (7.1%), the LV-GLS impairment persisted. In conclusion, in the acute and follow-up phase, we detected abnormal LV-GLS values in some patients, in the presence of normal LVEF, indicating that STE-GLS is a valuable tool for identifying subclinical myocardial injury in MIS-C.

Presentations and Outcomes Among Infants ≤90 Days With and Without SARS-CoV-2

OBJECTIVES

To compare symptoms and outcomes among infants aged ≤90 days tested for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in a broad, international sample of emergency departments (EDs).

METHODS

This was a secondary analysis of infants aged 0 to 90 days with suspected SARS-CoV-2 infections tested using molecular approaches and with 14-day follow-up. The parent studies were conducted at 41 EDs in 10 countries (the global Pediatric Emergency Research Network; March 2020-June 2021) and 14 EDs across Canada (Pediatric Emergency Research Canada network; August 2020-February 2022). Symptom profiles included presence and number of presenting symptoms. Clinical outcomes included hospitalization, ICU admission, and severe outcomes (a composite of intensive interventions, severe organ impairment, or death).

RESULTS

Among 1048 infants tested for SARS-CoV-2, 1007 (96.1%) were symptomatic at presentation and 432 (41.2%) were SARS-CoV-2-positive. A systemic symptom (any of the following: Apnea, drowsiness, irritability, or lethargy) was most common and present in 646 (61.6%) infants, regardless of SARS-CoV-2 status. Although fever and upper respiratory symptoms were more common among SARS-CoV-2-positive infants, dehydration, gastrointestinal, skin, and oral symptoms, and the overall number of presenting symptoms did not differ between groups. Infants with SARS-CoV-2 infections were less likely to be hospitalized (32.9% vs 44.8%; difference -11.9% [95% confidence interval (CI) -17.9% to -6.0%]), require intensive care (1.4% vs 5.0%; difference -3.6% [95% CI -5.7% to -1.6%]), and experience severe outcomes (1.4% vs 5.4%; difference -4.0% [95% CI -6.1% to -1.9%]).

CONCLUSIONS

SARS-CoV-2 infections may be difficult to differentiate from similar illnesses among the youngest infants but are generally milder. SARS-CoV-2 testing can help inform clinical management.

Epidemiology and clinical features of respiratory syncytial virus (RSV) infection in hospitalized children during the COVID-19 pandemic in Gorgan, Iran

Background and Aims

Respiratory syncytial virus (RSV) is a leading cause of acute respiratory infection in infants and young children. Given the altered circulation patterns of respiratory viruses during the coronavirus disease pandemic-2019 (COVID-19), the study aimed to evaluate epidemiology and clinical features of RSV infections in hospitalized children during the COVID-19 pandemic in Gorgan, northeastern Iran. Molecular epidemiology studies on respiratory viral infections are necessary to monitor circulating viruses, disease severity, and clinical symptoms, in addition to early warning of new outbreaks.

Methods

Overall, 411 respiratory swab samples from hospitalized children from October 2021 to March 2022 were collected at Taleghani Children's Hospital, Gorgan, Iran. The incidence of RSV, as well as the circulating subgroups and genotypes, were investigated and confirmed using PCR methods. Additionally, all samples tested for severe acute respiratory syndrome-associated coronavirus 2 (SARS-CoV-2) and influenza, and demographic and clinical data were analyzed using SPSS software.

Results

The share of RSV, SARS-CoV-2, and influenza among hospitalized children with acute lower respiratory infections (ALRI) were 27%, 16.5%, and 4.1%, respectively. The RSV subgroup A (genotype ON1) was dominant over subgroup B (genotype BA9), with more severe clinical symptoms. Compared with the prepandemic era there were high numbers of hospitalized SARS-CoV-2 positive children and low numbers of other respiratory viruses. Despite this, the prevalence of ALRI-related RSV-disease among hospitalized children in our specialized pediatric center was higher than COVID-19 disease in the same cohort.

Conclusions

Studying the epidemiology of respiratory viruses and determining the circulating strains can contribute to effective infection control and treatment strategies.

Rapid Triage of Children with Suspected COVID-19 Using Laboratory-Based Machine-Learning Algorithms

In order to limit the spread of the novel betacoronavirus (SARS-CoV-2), it is necessary to detect positive cases as soon as possible and isolate them. For this purpose, machine-learning algorithms, as a field of artificial intelligence, have been recognized as a promising tool. The aim of this study was to assess the utility of the most common machine-learning algorithms in the rapid triage of children with suspected COVID-19 using easily accessible and inexpensive laboratory parameters. A cross-sectional study was conducted on 566 children treated for respiratory diseases: 280 children with PCR-confirmed SARS-CoV-2 infection and 286 children with respiratory symptoms who were SARS-CoV-2 PCR-negative (control group). Six machine-learning algorithms, based on the blood laboratory data, were tested: random forest, support vector machine, linear discriminant analysis, artificial neural network, k-nearest neighbors, and decision tree. The training set was validated through stratified cross-validation, while the performance of each algorithm was confirmed by an independent test set. Random forest and support vector machine models demonstrated the highest accuracy of 85% and 82.1%, respectively. The models demonstrated better sensitivity than specificity and better negative predictive value than positive predictive value. The F1 score was higher for the random forest than for the support vector machine model, 85.2% and 82.3%, respectively. This study might have significant clinical applications, helping healthcare providers identify children with COVID-19 in the early stage, prior to PCR and/or antigen testing. Additionally, machine-learning algorithms could improve overall testing efficiency with no extra costs for the healthcare facility.