Tobacco smoke exposure, the lower airways microbiome and outcomes of ventilated children.

BackgroundTobacco smoke exposure increases the risk and severity of lower respiratory tract infections in children, yet the mechanisms remain unclear. We hypothesized that tobacco smoke exposure would modify the lower airway microbiome.MethodsSecondary analysis of a multicenter cohort of 362 children between ages 31 days and 18 years mechanically ventilated for >72 h. Tracheal aspirates from 298 patients, collected within 24 h of intubation, were evaluated via 16 S ribosomal RNA sequencing. Smoke exposure was determined by creatinine corrected urine cotinine levels ≥30 µg/g.ResultsPatients had a median age of 16 (IQR 568) months. The most common admission diagnosis was lower respiratory tract infection (53%). Seventy-four (20%) patients were smoke exposed and exhibited decreased richness and Shannon diversity. Smoke exposed children had higher relative abundances of Serratia spp., Moraxella spp., Haemophilus spp., and Staphylococcus aureus. Differences were most notable in patients with bacterial and viral respiratory infections. There were no differences in development of acute respiratory distress syndrome, days of mechanical ventilation, ventilator free days at 28 days, length of stay, or mortality.ConclusionAmong critically ill children requiring prolonged mechanical ventilation, tobacco smoke exposure is associated with decreased richness and Shannon diversity and change in microbial communities.ImpactTobacco smoke exposure is associated with changes in the lower airways microbiome but is not associated with clinical outcomes among critically ill pediatric patients requiring prolonged mechanical ventilation. This study is among the first to evaluate the impact of tobacco smoke exposure on the lower airway microbiome in children. This research helps elucidate the relationship between tobacco smoke exposure and the lower airway microbiome and may provide a possible mechanism by which tobacco smoke exposure increases the risk for poor outcomes in children

Risk Factors for Multisystem Inflammatory Syndrome in Children: A Case-Control Investigation

Background: In a 2020 pilot case-control study using medical records, we reported that non-Hispanic Black children were more likely to develop multisystem inflammatory syndrome in children (MIS-C) after adjustment for sociodemographic factors and underlying medical conditions. Using structured interviews, we investigated patient, household, and community factors underlying MIS-C likelihood. Methods: MIS-C case patients hospitalized in 2021 across 14 US pediatric hospitals were matched by age and site to outpatient controls testing positive for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) within 3 months of the admission date. Caregiver interviews queried race/ethnicity, medical history, and household and potential community exposures 1 month before MIS-C hospitalization (case-patients) or after SARS-CoV-2 infection (controls). We calculated adjusted odds ratios (aOR) using mixed-effects multivariable logistic regression. Results: Among 275 case patients and 496 controls, race/ethnicity, social vulnerability and patient or family history of autoimmune/rheumatologic disease were not associated with MIS-C. In previously healthy children, MIS-C was associated with a history of hospitalization for an infection [aOR: 4.8; 95% confidence interval (CI): 2.1-11.0]. Household crowding (aOR: 1.7; 95% CI: 1.2-2.6), large event attendance (aOR: 1.7; 95% CI: 1.3-2.1), school attendance with limited masking (aOR: 2.6; 95% CI: 1.1-6.6), public transit use (aOR: 1.8; 95% CI: 1.4-2.4) and co-resident testing positive for SARS-CoV-2 (aOR: 2.2; 95% CI: 1.3-3.7) were associated with increased MIS-C likelihood, with risk increasing with the number of these factors. Conclusions: From caregiver interviews, we clarify household and community exposures associated with MIS-C; however, we did not confirm prior associations between sociodemographic factors and MIS-C

Lower respiratory tract infections in children requiring mechanical ventilation: a multicentre prospective surveillance study incorporating airway metagenomics.

BackgroundLower respiratory tract infections (LRTI) are a leading cause of critical illness and mortality in mechanically ventilated children; however, the pathogenic microbes frequently remain unknown. We combined traditional diagnostics with metagenomic next generation sequencing (mNGS) to evaluate the cause of LRTI in critically ill children.MethodsWe conducted a prospective, multicentre cohort study of critically ill children aged 31 days to 17 years with respiratory failure requiring mechanical ventilation (>72 h) in the USA. By combining bacterial culture and upper respiratory viral PCR testing with mNGS of tracheal aspirate collected from all patients within 24 h of intubation, we determined the prevalence, age distribution, and seasonal variation of viral and bacterial respiratory pathogens detected by either method in children with or without LRTI.FindingsBetween Feb 26, 2015, and Dec 31, 2017, of the 514 enrolled patients, 397 were eligible and included in the study (276 children with LRTI and 121 with no evidence of LRTI). A presumptive microbiological cause was identified in 255 (92%) children with LRTI, with respiratory syncytial virus (127 [46%]), Haemophilus influenzae (70 [25%]), and Moraxella catarrhalis (65 [24%]) being most prevalent. mNGS identified uncommon pathogens including Ureaplasma parvum and Bocavirus. Co-detection of viral and bacterial pathogens occurred in 144 (52%) patients. Incidental carriage of potentially pathogenic microbes occurred in 82 (68%) children without LRTI, with rhinovirus (30 [25%]) being most prevalent. Respiratory syncytial virus (p<0·0001), H influenzae (p=0·0006), and M catarrhalis (p=0·0002) were most common in children younger than 5 years. Viral and bacterial LRTI occurred predominantly during winter months.InterpretationThese findings demonstrate that respiratory syncytial virus, H influenzae, and M catarrhalis contribute disproportionately to severe paediatric LRTI, co-infections are common, and incidental carriage of potentially pathogenic microbes occurs frequently. Further, we provide a framework for future epidemiological and emerging pathogen surveillance studies, highlighting the potential for metagenomics to enhance clinical diagnosis.FundingUS National Institutes of Health and CZ Biohub

Temporal airway microbiome changes related to ventilator-associated pneumonia in children.

We sought to determine whether temporal changes in the lower airway microbiome are associated with ventilator-associated pneumonia (VAP) in children.Using a multicentre prospective study of children aged 31 days to 18 years requiring mechanical ventilation support for >72 h, daily tracheal aspirates were collected and analysed by sequencing of the 16S rRNA gene. VAP was assessed using 2008 Centers for Disease Control and Prevention paediatric criteria. The association between microbial factors and VAP was evaluated using joint longitudinal time-to-event modelling, matched case-control comparisons and unsupervised clustering.Out of 366 eligible subjects, 66 (15%) developed VAP at a median of 5 (interquartile range 3-5) days post intubation. At intubation, there was no difference in total bacterial load (TBL), but Shannon diversity and the relative abundance of Streptococcus, Lactobacillales and Prevotella were lower for VAP subjects versus non-VAP subjects. However, higher TBL on each sequential day was associated with a lower hazard (hazard ratio 0.39, 95% CI 0.23-0.64) for developing VAP, but sequential values of diversity were not associated with VAP. Similar findings were observed from the matched analysis and unsupervised clustering. The most common dominant VAP pathogens included Prevotella species (19%), Pseudomonas aeruginosa (14%) and Streptococcus mitis/pneumoniae (10%). Mycoplasma and Ureaplasma were also identified as dominant organisms in several subjects.In mechanically ventilated children, changes over time in microbial factors were marginally associated with VAP risk, although these changes were not suitable for predicting VAP in individual patients. These findings suggest that focusing exclusively on pathogen burden may not adequately inform VAP diagnosis