A new index to identify risk of multi-trigger wheezing in infants with first episode of wheezing

Does machine learning have a role in the prediction of asthma in children?

Asthma is the most common chronic lung disease in childhood. There has been a significant worldwide effort to develop tools/methods to identify children's risk for asthma as early as possible for preventative and early management strategies. Unfortunately, most childhood asthma prediction tools using conventional statistical models have modest accuracy, sensitivity, and positive predictive value. Machine learning is an approach that may improve on conventional models by finding patterns and trends from large and complex datasets. Thus far, few studies have utilized machine learning to predict asthma in children. This review aims to critically assess these studies, describe their limitations, and discuss future directions to move from proof-of-concept to clinical application.

Airway microbiome, host immune response and recurrent wheezing in infants with severe respiratory syncytial virus bronchiolitis

BACKGROUND

Early interactions between respiratory viruses and microbiota might modulate host immune responses and subsequently contribute to later development of recurrent wheezing and asthma in childhood. We aimed to study the possible association between respiratory microbiome, host immune response, and the development of recurrent wheezing in infants with severe respiratory syncytial virus (RSV) bronchiolitis.

METHODS

Seventy-four infants who were hospitalized at Beijing Children's Hospital during an initial episode of severe RSV bronchiolitis at 6 months of age or less were included and followed up until the age of 3 years. Sputum samples were collected, and their microbiota profiles, LPS, and cytokines were analyzed by 16S rRNA-based sequencing, ELISA, and multiplex immunoassay, respectively.

RESULTS

Twenty-six (35.1%) infants developed recurrent wheezing by the age of 3 years, and 48 (64.9%) did not. The relative abundance of Haemophilus, Moraxella, and Klebsiella was higher in infants who later developed recurrent wheezing than in those who did not (LDA score >3.5). Airway levels of LPS (P = .003), CXCL8 (P = .004), CCL5 (P = .029), IL-6 (P = .004), and IL-13 (P < .001) were significantly higher in infants who later developed recurrent wheezing than in those who did not. Moreover, high airway abundance of Haemophilus was associated with CXCL8 (r = 0.246, P = .037) level, and that of Moraxella was associated with IL-6 level (r = 0.236, P = .046) and IL-10 level (r = 0.266, P = .024).

CONCLUSION

Our study suggests that higher abundance of Haemophilus and Moraxella in airway microbiome might modulate airway inflammation during severe RSV bronchiolitis in infancy, potentially contributing to the development of subsequent recurrent wheezing in later childhood.

Targeted Education Across Clinical Settings Improves Adherence to Evidence-Based Interventions for Bronchiolitis

Bronchiolitis remains a leading cause of hospitalization of infants. Despite evidence-based recommendations, wide variation in practice remains. A pre-post educational intervention was implemented to improve adherence to bronchiolitis guidelines in emergency and inpatient settings. Among children meeting inclusion criteria (136 pre-intervention, 185 post-intervention), emergency department (ED) bronchodilator use decreased by 64% (P < .001). Steroid use decreased by 71% (P = .002). There was no difference in viral testing, antibiotic use, or chest radiograph acquisition. No differences were seen in the inpatient setting. There was no difference in rate of intensive care unit transfer or length of stay. Post-intervention, children were less likely to receive a bronchodilator in the ED (odds ratio [OR] = 0.15, P < .001). Children with a family history of asthma were more likely to receive a bronchodilator in the ED (OR = 4.25, P < .001). Targeted education across settings contributed to reducing bronchodilator use in the ED. Family history appeared to influence medical decision making.

A systematic review of predictive models for asthma development in children

BACKGROUND

Asthma is the most common pediatric chronic disease affecting 9.6 % of American children. Delay in asthma diagnosis is prevalent, resulting in suboptimal asthma management. To help avoid delay in asthma diagnosis and advance asthma prevention research, researchers have proposed various models to predict asthma development in children. This paper reviews these models.

METHODS

A systematic review was conducted through searching in PubMed, EMBASE, CINAHL, Scopus, the Cochrane Library, the ACM Digital Library, IEEE Xplore, and OpenGrey up to June 3, 2015. The literature on predictive models for asthma development in children was retrieved, with search results limited to human subjects and children (birth to 18 years). Two independent reviewers screened the literature, performed data extraction, and assessed article quality.

RESULTS

The literature search returned 13,101 references in total. After manual review, 32 of these references were determined to be relevant and are discussed in the paper. We identify several limitations of existing predictive models for asthma development in children, and provide preliminary thoughts on how to address these limitations.

CONCLUSIONS

Existing predictive models for asthma development in children have inadequate accuracy. Efforts to improve these models' performance are needed, but are limited by a lack of a gold standard for asthma development in children.

From bronchiolitis guideline to practice: A critical care perspective

Acute viral bronchiolitis is a leading cause of admission to pediatric intensive care units, but research on the care of these critically ill infants has been limited. Pathology of viral bronchiolitis revealed respiratory obstruction due to intraluminal debris and edema of the airways and vasculature. This and clinical evidence suggest that airway clearance interventions such as hypertonic saline nebulizers and pulmonary toilet devices may be of benefit, particularly in situations of atelectasis associated with bronchiolitis. Research to distinguish an underlying asthma predisposition in wheezing infants with viral bronchiolitis may one day lead to guidance on when to trial bronchodilator therapy. Considering the paucity of critical care research in pediatric viral bronchiolitis, intensive care practitioners must substantially rely on individualization of therapies based on bedside clinical assessments. However, with the introduction of new diagnostic and respiratory technologies, our ability to support critically ill infants with acute viral bronchiolitis will continue to advance.

Early childhood wheezers: identifying asthma in later life

Wheeze in young children is common, and asthma is the most common noncommunicable disease in children. Prevalence studies of recurrent asthma-like symptoms in children under the age of 5 years have reported that one third of children in the US and Europe are affected, and rates and severity appear to be higher in developing countries. Over the last few decades, significant research efforts have focused on identification of risk factors and predictors of wheeze and on tools to identify which children who wheeze will progress to develop asthma. We reviewed the phenotypes of childhood wheezing, genetic risk factors, environmental factors, testing/predictive indices, and primary prevention. While it is generally agreed that a complex interaction of environmental exposure and genetic susceptibility contributes to the development of asthma, limitations in predictive tools and tests restrict our ability to provide families with guidance as to whether their child with wheeze will ultimately develop asthma. Additional research is needed to clarify childhood wheeze phenotypes, to develop tools to determine which children will develop asthma, and to determine how and when to intervene. If these areas can be addressed, it would help reduce this large burden on children, families, and society.