To investigate the temporal trend in the national incidence of bronchiolitis hospitalizations, their characteristics, inpatient resource use, and hospital cost from 2000 through 2016.
We performed a ...serial, cross-sectional analysis of nationally representative samples (the 2000, 2003, 2006, 2009, 2012, and 2016 Kids' Inpatient Databases) of children (age <2 years) hospitalized for bronchiolitis. We identified all children hospitalized with bronchiolitis by using
466.1 and
J21. Complex chronic conditions were defined by the pediatric complex chronic conditions classification by using inpatient data. The primary outcomes were the incidence of bronchiolitis hospitalizations, mechanical ventilation use, and hospital direct cost. We examined the trends accounting for sampling weights.
From 2000 to 2016, the incidence of bronchiolitis hospitalization decreased from 17.9 to 13.5 per 1000 person-years in US children (25% decrease;
< .001). In contrast, the proportion of bronchiolitis hospitalizations among overall hospitalizations increased from 16% to 18% (
< .001). There was an increase in the proportion of children with a complex chronic condition (6%-13%; 117% increase), hospitalization to children's hospital (15%-29%; 93% increase), and mechanical ventilation use (2%-5%; 184% increase; all
< .001). Likewise, the hospital cost increased from $449 million to $734 million (63% increase) nationally (with an increase in geometric mean of cost per hospitalization from $3267 to $4086; 25% increase;
< .001 adjusted for inflation) from 2003 to 2016.
From 2000 through 2016, the incidence of bronchiolitis hospitalizations among US children declined. In contrast, mechanical ventilation use and nationwide hospital direct cost substantially increased.
Berry and Mansbach discuss the study by Lassalle et al on the association of proton pump inhibitors (PPI) use with the risk of serious infection (ie, infection requiring hospitalization) in young ...children. Using the French National Health Insurance registry of all pregnancies and births from 2010 to 2018, data were ascertained for children prescribed 1 or more gastrointestinal medications: PPIs, histamine 2 receptor antagonists, and antacids/alginate. Although GER (or other gastric-acid related disorders) was the presumed indication for these medication exposures, information on preceding symptoms was not assessed. They comment that it is time to limit PPI use in infants and children, especially when they are otherwise healthy and until further investigation distinguishes who has the most favorable risk-benefit ratio. To address this knowledge gap, they suggest collecting primary data about the effects of PPI use in infants and children, including changes in the composition and function of infant gut microbiome.
Respiratory syncytial virus (RSV) bronchiolitis is not only the leading cause of hospitalization in U.S. infants, but also a major risk factor for asthma development. While emerging evidence suggests ...clinical heterogeneity within RSV bronchiolitis, little is known about its biologically-distinct endotypes. Here, we integrated clinical, virus, airway microbiome (species-level), transcriptome, and metabolome data of 221 infants hospitalized with RSV bronchiolitis in a multicentre prospective cohort study. We identified four biologically- and clinically-meaningful endotypes: A) clinical
microbiome
inflammation
, B) clinical
microbiome
inflammation
, C) clinical
microbiome
inflammation
, and D) clinical
microbiome
inflammation
. Particularly, compared with endotype A infants, endotype B infants-who are characterized by a high proportion of IgE sensitization and rhinovirus coinfection, S. pneumoniae/M. catarrhalis codominance, and high IFN-α and -γ response-had a significantly higher risk for developing asthma (9% vs. 38%; OR, 6.00: 95%CI, 2.08-21.9; P = 0.002). Our findings provide an evidence base for the early identification of high-risk children during a critical period of airway development.
A better understanding of bronchiolitis heterogeneity might help clarify its relationship with the development of recurrent wheezing and asthma.
We sought to identify severe bronchiolitis profiles ...using a clustering approach and to investigate for the first time their association with allergy/inflammatory biomarkers, nasopharyngeal microbiota, and development of recurrent wheezing by age 3 years.
We analyzed data from a prospective, 17-center US cohort study of 921 infants (age <1 year) hospitalized with bronchiolitis (2011-2014 winters) with posthospitalization follow-up. Severe bronchiolitis profiles at baseline (hospitalization) were determined by using latent class analysis based on clinical factors and viral etiology. Blood biomarkers and nasopharyngeal microbiota profiles were determined by using samples collected within 24 hours of hospitalization. Recurrent wheezing by age 3 years was defined based on parental report of breathing problem episodes after discharge.
Three severe bronchiolitis profiles were identified: profile A (15%), which was characterized by a history of breathing problems/eczema during infancy and non–respiratory syncytial virus (mostly rhinovirus) infection; profile B (49%), which has the largest probability of respiratory syncytial virus infection and resembled classic respiratory syncytial virus-induced bronchiolitis; and profile C (36%), which was composed of the most severely ill group. Profile A infants had higher eosinophil counts, higher cathelicidin levels, and increased proportions of Haemophilus-dominant or Moraxella-dominant microbiota profiles. Compared with profile B, we observed significantly increased risk of recurrent wheezing in children with profile A (hazard ratio, 2.64; 95% CI, 1.90-3.68) and, to a lesser extent, with profile C (hazard ratio, 1.51; 95% CI, 1.14-2.01).
Although longer follow-up is needed, our results might help identify, among children hospitalized for bronchiolitis, subgroups with particularly increased risk of asthma.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Changes in the composition of the microbiome over time are associated with myriad human illnesses. Unfortunately, the lack of analytic techniques has hindered researchers' ability to quantify the ...association between longitudinal microbial composition and time-to-event outcomes. Prior methodological work developed the joint model for longitudinal and time-to-event data to incorporate time-dependent biomarker covariates into the hazard regression approach to disease outcomes. The original implementation of this joint modeling approach employed a linear mixed effects model to represent the time-dependent covariates. However, when the distribution of the time-dependent covariate is non-Gaussian, as is the case with microbial abundances, researchers require different statistical methodology. We present a joint modeling framework that uses a negative binomial mixed effects model to determine longitudinal taxon abundances. We incorporate these modeled microbial abundances into a hazard function with a parameterization that not only accounts for the proportional nature of microbiome data, but also generates biologically interpretable results. Herein we demonstrate the performance improvements of our approach over existing alternatives via simulation as well as a previously published longitudinal dataset studying the microbiome during pregnancy. The results demonstrate that our joint modeling framework for longitudinal microbiome count data provides a powerful methodology to uncover associations between changes in microbial abundances over time and the onset of disease. This method offers the potential to equip researchers with a deeper understanding of the associations between longitudinal microbial composition changes and disease outcomes. This new approach could potentially lead to new diagnostic biomarkers or inform clinical interventions to help prevent or treat disease.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Severe bronchiolitis (ie, bronchiolitis requiring hospitalization) during infancy is a major risk factor for childhood asthma. However, the exact mechanism linking these common conditions remains ...unclear.
This study sought to examine the integrated role of airway microbiome (both taxonomy and function) and host response in asthma development in this high-risk population.
This multicenter prospective cohort study of 244 infants with severe bronchiolitis (median age, 3 months) examined the infants’ nasopharyngeal metatranscriptomes (microbiomes) and transcriptomes (hosts), as well as metabolomes at hospitalization. The longitudinal relationships investigated include (1) major bacterial species (Streptococcus pneumoniae, Haemophilus influenzae, and Moraxella catarrhalis), (2) microbial function, and (3) host response with risks of developing asthma by age 6 years.
First, the abundance of S pneumoniae was associated with greater risks of asthma (P = .01), particularly in infants with nonrhinovirus infection (Pinteraction = .04). Second, of 328 microbial functional pathways that are differentially enriched by asthma development, the top pathways (eg, fatty acid and glycolysis pathways; false discovery rate FDR < 1 × 10−12) were driven by these 3 major species (eg, positive association of S pneumoniae with glycolysis; FDR < 0.001). These microbial functional pathways were validated with the parallel metabolome data. Third, 104 transcriptome pathways were differentially enriched (FDR < .05)—for example, downregulated interferon-α and -γ and upregulated T-cell activation pathways. S pneumoniae was associated with most differentially expressed transcripts (eg, DAGLB; FDR < 0.05).
By applying metatranscriptomic, transcriptomic, and metabolomic approaches to a multicenter cohort of infants with bronchiolitis, this study found an interplay between major bacterial species, their function, and host response in the airway, and their longitudinal relationship with asthma development.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Although bronchiolitis is generally considered a single disease, recent studies suggest heterogeneity. We aimed to identify severe bronchiolitis profiles using a clustering approach.
We analysed data ...from two prospective, multicentre cohorts of children younger than 2 years hospitalised with bronchiolitis, one in the USA (2007-2010 winter seasons, n=2207) and one in Finland (2008-2010 winter seasons, n=408). Severe bronchiolitis profiles were determined by latent class analysis, classifying children based on clinical factors and viral aetiology.
In the US study, four profiles were identified. Profile A (12%) was characterised by history of wheezing and eczema, wheezing at the emergency department (ED) presentation and rhinovirus infection. Profile B (36%) included children with wheezing at the ED presentation, but, in contrast to profile A, most did not have history of wheezing or eczema; this profile had the largest probability of respiratory syncytial virus infection. Profile C (34%) was the most severely ill group, with longer hospital stay and moderate-to-severe retractions. Profile D (17%) had the least severe illness, including non-wheezing children with shorter length of stay. Two of these profiles (A and D) were replicated in the Finnish cohort; a third group ('BC') included Finnish children with characteristics of profiles B and/or C in the US population.
Several distinct clinical profiles (phenotypes) were identified by a clustering approach in two multicentre studies of children hospitalised for bronchiolitis. The observed heterogeneity has important implications for future research on the aetiology, management and long-term outcomes of bronchiolitis, such as future risk of childhood asthma.
To examine temporal trend in the national incidence of bronchiolitis hospitalizations, use of mechanical ventilation, and hospital charges between 2000 and 2009.
We performed a serial, ...cross-sectional analysis of a nationally representative sample of children hospitalized with bronchiolitis. The Kids Inpatient Database was used to identify children <2 years of age with bronchiolitis by International Classification of Diseases, Ninth Revision, Clinical Modification code 466.1. Primary outcome measures were incidence of bronchiolitis hospitalizations, mechanical ventilation (noninvasive or invasive) use, and hospital charges. Temporal trends were evaluated accounting for sampling weights.
The 4 separated years (2000, 2003, 2006, and 2009) of national discharge data included 544 828 weighted discharges with bronchiolitis. Between 2000 and 2009, the incidence of bronchiolitis hospitalization decreased from 17.9 to 14.9 per 1000 person-years among all US children aged <2 years (17% decrease; P(trend) < .001). By contrast, there was an increase in children with high-risk medical conditions (5.9%-7.9%; 34% increase; P(trend) < .001) and use of mechanical ventilation (1.9%-2.3%; 21% increase; P(trend) = .008). Nationwide hospital charges increased from $1.34 billion to $1.73 billion (30% increase; P(trend) < .001); this increase was driven by a rise in the geometric mean of hospital charges per case from $6380 to $8530 (34% increase; P(trend) < .001).
Between 2000 and 2009, we found a significant decline in bronchiolitis hospitalizations among US children. By contrast, use of mechanical ventilation and hospital charges for bronchiolitis significantly increased over this same period.
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