Predicting Severe Asthma Exacerbations in Children

Impact of congenital heart disease on mortality and other associated outcomes in children hospitalised for acute asthma exacerbation

BACKGROUND

Acute asthma exacerbation is one of the most common reasons for paediatric emergency room visits and hospital admissions in the United States of America.

OBJECTIVE

To assess the impact of CHD on outcomes of children hospitalised for acute asthma exacerbation.

METHODS

Children primarily admitted for acute asthma exacerbation were sampled from 2006, 2009, 2012, and 2016 kid inpatient database of the Healthcare Cost and Utilization Project using ICD codes. The disease outcomes were compared between those with and without CHD using multivariate logistic regressions in Stata version 17.

RESULTS

There were a total of 639,280 acute asthma exacerbation admissions, of which 5,907 (0.92%) had CHD. The mortality rate was 0.079% for patients without CHD and 0.72% for those with co-existing CHD. Children with CHD had higher odds of mortality (5.51, CI 3.40-8.93, p < 0.001), acute respiratory failure (2.84, CI 2.53-3.20; p < 0.001), need for invasive mechanical ventilation (4.58, CI 3.80-5.52; p < 0.001), acute kidney injury (adjusted odds ratio 3.03, CI 3.03-7.44; p < 0.001), and in-hospital cardiac arrest (adjusted odds ratio 4.52, CI 2.49-8.19; p < 0.001) when compared with those without CHD. The adjusted mean length of hospital stays (CI 2.91-3.91; p < 0.001) and hospital charges (95% CI $31060-$47747) among children with acute asthma exacerbation and CHD were significantly higher than in those without CHD.

CONCLUSION AND SIGNIFICANCE

CHD is an independent predictor of mortality, more severe disease course, and higher hospital resource utilisation. Strategies that improve CHD care will likely improve the overall health outcomes of children with CHD hospitalised for acute asthma exacerbation.

Machine Learning Approaches to Predict Asthma Exacerbations: A Narrative Review

The implementation of artificial intelligence (AI) and machine learning (ML) techniques in healthcare has garnered significant attention in recent years, especially as a result of their potential to revolutionize personalized medicine. Despite advances in the treatment and management of asthma, a significant proportion of patients continue to suffer acute exacerbations, irrespective of disease severity and therapeutic regimen. The situation is further complicated by the constellation of factors that influence disease activity in a patient with asthma, such as medical history, biomarker phenotype, pulmonary function, level of healthcare access, treatment compliance, comorbidities, personal habits, and environmental conditions. A growing body of work has demonstrated the potential for AI and ML to accurately predict asthma exacerbations while also capturing the entirety of the patient experience. However, application in the clinical setting remains mostly unexplored, and important questions on the strengths and limitations of this technology remain. This review presents an overview of the rapidly evolving landscape of AI and ML integration into asthma management by providing a snapshot of the existing scientific evidence and proposing potential avenues for future applications.

Effects of treatment with corticosteroids on human rhinovirus-induced asthma exacerbations in pediatric inpatients: a prospective observational study

BACKGROUND

Human rhinoviruses (HRVs) infection is a common cause of exacerbations in pediatric patients with asthma. However, the effects of corticosteroids on HRV-induced exacerbations in pediatric asthma are unknown. We conducted a prospective observational study to determine the viral pathogens in school-age pediatric inpatients with asthma exacerbations. We assessed the effects of maintenance inhaled corticosteroids (ICS) on the detection rates of HRV species and treatment periods of systemic corticosteroids during exacerbations on pulmonary lung function after exacerbations.

METHODS

Nasopharyngeal samples and clinical information were collected from 59 patients with asthma exacerbations between April 2018 and March 2020. Pulmonary function tests were carried out 3 months after exacerbations in 18 HRV-positive patients. Changes in forced expiratory volume in 1 second (FEV1)% predicted from baseline in a stable state were compared according to the treatment periods of systemic corticosteroids.

RESULTS

Fifty-four samples collected from hospitalized patients were analyzed, and viral pathogens were identified in 45 patients (83.3%) using multiplex PCR assay. HRV-A, -B, and -C were detected in 16 (29.6%), one (1.9%), and 16 (29.6%) patients, respectively. The detection rates of HRV-C were lower in the ICS-treated group compared with those in the ICS-untreated group (p = 0.01), whereas maintenance ICS treatment did not affect the detection rate for viral pathogens in total and HRV-A. Changes in FEV1% predicted in patients treated with systemic corticosteroids for 6-8 days (n = 10; median, 4.90%) were higher than those in patients treated for 3-5 days (n = 8; median, - 10.25%) (p = 0.0085).

CONCLUSIONS

Maintenance ICS reduced the detection rates of HRV (mainly HRV-C) in school-age inpatients with asthma exacerbations, and the treatment periods of systemic corticosteroids during exacerbations affected lung function after HRV-induced exacerbations. The protective effects of corticosteroids on virus-induced asthma exacerbations may be dependent upon the types of viral pathogen.

Composite predictive models for asthma exacerbations or asthma deterioration in pediatric asthmatic patients: A systematic review of the literature

A variety of factors have shown to be useful in predicting which children are at high risk for future asthma exacerbations, some of them combined into composite predictive models. The objective of the present review was to systematically identify all the available published composite predictive models developed for predicting which children are at high risk for future asthma exacerbations or asthma deterioration. A systematic search of the literature was performed to identify studies in which a composite predictive model developed for predicting which children are at high risk for future asthma exacerbations or asthma deterioration was described. Methodological quality assessment was performed using accepted criteria for prediction rules and prognostic models. A total of 18 articles, describing a total of 17 composite predictive models were identified and included in the review. The number of predictors included in the models ranged from 2-149. Upon analyzing the content of the models, use of healthcare services for asthma and prescribed or dispensed asthma medications were the most frequently used items (in 8/17, 47.0% of the models). Seven (41.2%) models fulfilled all the quality criteria considered in our evaluation. The identified models may help clinicians dealing with asthmatic children to identify which children are at a higher risk for future asthma exacerbations or asthma deterioration, therefore targeting and/or reinforcing specific interventions for these children in an attempt to prevent exacerbations or deterioration of the disease.

Effects of Ambient Air Pollutants on Hospital Admissions among Children Due to Asthma and Wheezing-Associated Lower Respiratory Infections in Mysore, India: A Time Series Study

Air pollutants are known to trigger asthma and wheezing-associated lower respiratory infections in children, but evidence regarding their effect on hospital admissions in India is limited. We conducted a time-series study over a period of five years to assess the role of ambient air pollutants in daily asthma-related hospital admissions in children in Mysore, India. Daily asthma and wheeze (associated with lower respiratory infections) admissions were modelled using a generalised additive model (GAM) to examine the non-linear effects and generalised linear models (GLM) for linear effects, if any. Models were adjusted by day of the week and lag days, with smooth terms for time, maximum temperature, and relative humidity, and they were stratified by sex and age group. Of the 362 children admitted, more than 50% were boys, and the mean age was 5.34 years (±4.66). The GAMs showed non-linear associations between NO2, PM2.5, and NH3. For example, a 10 µgm-3 (or 10%) increase in NO2 increased admissions by 2.42. These non-linear effects were more pronounced in boys. A linear effect was detected for PM10 with a relative risk (95% CI) of 1.028, 1.013, and 1.043 with admission. Further research is needed to explore whether these findings can be replicated in different cities in India. Air pollution needs to be controlled, and policies that focus on lower cut-off levels for vulnerable populations are necessary.

Measurement of adherence to inhaled corticosteroids by self-report and electronic medication monitoring

OBJECTIVE

Poor adherence to daily inhaled corticosteroids (ICS) is an important factor contributing to asthma morbidity. Assessing adherence in clinical settings using self-reported adherence often overestimates actual adherence. Electronic monitoring devices (EMDs) are objective means of assessing adherence, but are not routinely used in practice. Here, we aimed to establish adherence rates to ICS using EMDs in an inner-city, minority population in the Bronx, NY, and to compare two methods of self-reported adherence with EMD-measured adherence.

METHODS

Patients with physician-confirmed persistent asthma and daily ICS prescription were recruited. Self-reported adherence to ICS was measured by parental report for children and self-report for adults and the Medication Adherence Report Scale for Asthma (MARS-A). Two weeks after enrollment, EMD data were accessed for analysis. Daily adherence was calculated based on the number of puffs actuated per day as captured by EMD divided by the prescribed number of puffs.

RESULTS

41 children and 40 adults participated. Median EMD-measured ICS adherence was 41% (children) and 43% (adults). This was significantly lower than the median self-reported adherence (100% for children, p < 0.001; 100% for adults, p < 0.001). MARS-A score in children did not correlate with EMD adherence data (p = 0.18), while in adults, this correlation tended to be more consistent (p = 0.07).

CONCLUSIONS

Adherence to daily ICS as measured using EMD is low in this population. In both adults and children, self-reported adherence was a poor indicator of true adherence. Further efforts using objective measures of medication adherence for patients with high asthma morbidity may be warranted to guide therapeutic decisions.

Airway transcriptome networks identify susceptibility to frequent asthma exacerbations in children

BACKGROUND

Frequent asthma exacerbators, defined as those experiencing more than 1 hospitalization in a year for an asthma exacerbation, represent an important subgroup of individuals with asthma. However, this group remains poorly defined and understudied in children.

OBJECTIVE

Our aim was to determine the molecular mechanisms underlying asthma pathogenesis and exacerbation frequency.

METHODS

We performed RNA sequencing of upper airway cells from both frequent and nonfrequent exacerbators enrolled in the Ohio Pediatric Asthma Repository.

RESULTS

Through molecular network analysis, we found that nonfrequent exacerbators display an increase in modules enriched for immune system processes, including type 2 inflammation and response to infection. In contrast, frequent exacerbators showed expression of modules enriched for nervous system processes, such as synaptic formation and axonal outgrowth.

CONCLUSION

These data suggest that the upper airway of frequent exacerbators undergoes peripheral nervous system remodeling, representing a novel mechanism underlying pediatric asthma exacerbation.

The Role of Vitamins in the Pathogenesis of Asthma

Vitamins play a crucial role in the proper functioning of organisms. Disturbances of their levels, seen as deficiency or excess, enhance the development of various diseases, including those of the cardiovascular, immune, or respiratory systems. The present paper aims to summarize the role of vitamins in one of the most common diseases of the respiratory system, asthma. This narrative review describes the influence of vitamins on asthma and its main symptoms such as bronchial hyperreactivity, airway inflammation, oxidative stress, and airway remodeling, as well as the correlation between vitamin intake and levels and the risk of asthma in both pre- and postnatal life.

Initial emergency department vital signs may predict PICU admission in pediatric patients presenting with asthma exacerbation

OBJECTIVE

Severe asthma exacerbations account for a large share of asthma morbidity, mortality, and costs. Here, we aim to identify early predictive factors associated with pediatric intensive care unit (PICU) admission.

METHODS

We performed a retrospective observational study of 5,185 emergency department (ED) encounters at a large children's hospital, including 86 (1.7%) resulting in PICU admission between 10/1/2015 and 8/7/2018 with ICD9/ICD10 codes for "asthma," "bronchospasm," or "wheezing." Vital signs and demographic information were obtained from electronic health record data and analyzed for each encounter. Predictive factors were identified using adjusted regression models, and our primary outcome was PICU admission.

RESULTS

Higher mean heart rates (HRs) and respiratory rates (RRs), and lower SpO2 within the first hour of ED presentation were independently associated with PICU admission. Odds of PICU admission increased 70% for each 10 beats/min higher HR, 125% for each 10 breaths/min higher RR, and 34% for each 5% lower SpO2. A binary predictive index using 1-h vitals yielded OR 13.4 (95% CI 8.1-22.1) for PICU admission, area under receiver operator characteristic (AUROC) curve 0.84 and overall accuracy of 80.1%. Results were largely unchanged (AUROC 0.84-0.88) after adjusting for surrogates of asthma severity and initial ED management. In combination with a secondary standardized clinical asthma distress score, positive predictive value increased by sevenfold (6.1%-46%).

CONCLUSIONS

A predictive index using HR, RR, and SpO2 within the first hour of ED presentation accurately predicted PICU admission in this cohort. Automated vital signs trend analysis may help identify vulnerable patients quickly upon presentation.

The upper-airway microbiome as a biomarker of asthma exacerbations despite inhaled corticosteroid treatment

BACKGROUND

The response to inhaled corticosteroids (ICS) in asthma is affected by the interplay of several factors. Among these, the role of the upper-airway microbiome has been scarcely investigated. We aimed to evaluate the association between the salivary, pharyngeal, and nasal microbiome with asthma exacerbations despite receipt of ICS.

METHODS

Samples from 250 asthma patients from the Genomics and Metagenomics of Asthma Severity (GEMAS) study treated with ICS were analyzed. Control/case subjects were defined by the absence/presence of asthma exacerbations in the past 6 months despite being treated with ICS. The bacterial microbiota was profiled by sequencing the V3-V4 region of the 16S rRNA gene. Differences between groups were assessed by PERMANOVA and regression models adjusted for potential confounders. A false discovery rate (FDR) of 5% was used to correct for multiple comparisons. Classification models of asthma exacerbations despite ICS treatment were built with machine learning approaches based on clinical, genetic, and microbiome data.

RESULTS

In nasal and saliva samples, case subjects had lower bacterial diversity (Richness, Shannon, and Faith indices) than control subjects (.007 ≤ P ≤ .037). Asthma exacerbations accounted for 8% to 9% of the interindividual variation of the salivary and nasal microbiomes (.003 ≤ P ≤ .046). Three, 4, and 11 bacterial genera from the salivary, pharyngeal, and nasal microbiomes were differentially abundant between groups (4.09 × 10^-12 ≤ FDR ≤ 0.047). Integrating clinical, genetic, and microbiome data showed good discrimination for the development of asthma exacerbations despite receipt of ICS (AUC_training: 0.82 and AUC_validation: 0.77).

CONCLUSION

The diversity and composition of the upper-airway microbiome are associated with asthma exacerbations despite ICS treatment. The salivary microbiome has a potential application as a biomarker of asthma exacerbations despite receipt of ICS.

Asthma Hospital Admission and Readmission Spikes, Advancing Accurate Classification to Advance Understanding of Causes

Background: An important component of asthma care is understanding potential causes of high asthma admissions (HAADs) or readmissions (HARDs) with potential of risk mitigation. Crucial to this research is accurately distinguishing these events from background seasonal changes and time trends. To date, classification methods have been based on ad hoc and untested definitions which may hamper understanding causes of HAADs and HARDs due to misclassification. The aim of this article is to introduce an easily applied robust statistical approach, with high classification accuracy in other settings—the Seasonal Hybrid Extreme Studentized Deviate (S-H-ESD) method. Methods: We demonstrate S-H-ESD on a time series between 1996 and 2009 of all daily paediatric asthma hospital admissions in Victoria, Australia. Results: S-H-ESD clearly identified HAADs and HARDs without applying ad hoc classification definitions, while appropriately accounting for seasonality and time trend. Importantly, it was done with statistical testing, providing evidence in support of their identification. Conclusion: S-H-ESD is useful and statistically appropriate for accurate classification of HAADs and HARDS. It obviates ad hoc approaches and presents as a means of systemizing their accurate classification and detection. This will strengthen synthesis and efficacy of research toward understanding causes of HAADs and HARDs for their risk mitigation.

Psychologist's Unique Role in Improving Quality of Life of Children with Chronic Lung Diseases and Their Families

Pediatric chronic lung diseases burden their patients and families with heavy treatment loads, frequent extensive clinic visits to multiple providers, frequent emergency department visits and hospitalizations, and contribute to significant psychosocial issues with caregiver's burnout. The purpose of this chapter is to outline the psychosocial impact of the major pediatric chronic lung diseases and the unique role of the psychologist in relieving this burden. These include severe asthma, cystic fibrosis, bronchopulmonary dysplasia, and dependence on home mechanical ventilation.

Size-segregated particle number concentrations and outpatient-department visits for pediatric respiratory diseases in Shanghai, China

BACKGROUND

Few studies have simultaneously explored which size of particles has the greatest impact on the risk for pediatric asthma, bronchitis and upper respiratory tract infections (URTIs).

OBJECTIVES

To investigate the short-term association between size-segregated particle number concentrations (PNCs) and outpatient-department visits (ODVs) for major pediatric respiratory diseases.

METHODS

Daily counts of pediatric ODVs for asthma, bronchitis and URTIs were obtained from 66 hospitals in Shanghai, China, from 2016 to 2018. Pollutant effects were estimated using Poisson generalized additive models combined with polynomial distributed lag models. We also fitted co-pollutant cumulative effects models included six criteria air pollutants and conducted stratifying analyses by gender, age, season and geographic distances.

RESULTS

We identified a total of 430,103 patients with asthma, 1,547,013 patients with bronchitis, and 2,155,738 patients with URTIs from the hospitals. Effect estimates increased with decreasing particle size. Ultrafine particle (UFP) and PNCs of 0.10-0.40 µm particles (PNC_0.10-0.40) were associated with increased ODVs for asthma, bronchitis and URTIs at cumulative lags up to 3d. Associations tended to appear stable after adjusting for criteria air pollutants. At the cumulative lag 0-2d, each interquartile range increase in UFP was associated with increased ODVs due to asthma (relative risk 1.21, 95% CI: 1.07, 1.38), bronchitis (1.20, 95% CI: 1.07, 1.34) and URTI (1.17, 95% CI: 1.06, 1.30), whereas the associations for PNC_0.10-0.40 remained significant but attenuated in magnitude.

CONCLUSIONS

UFP may be a leading contributor to the adverse respiratory effects of particulate air pollution and the effects increased with decreasing particle size.

A Meta-Analysis on Vitamin D Supplementation and Asthma Treatment

Background

Vitamin D, as an immunomodulator, may be related to the therapeutic effect of asthma patients, but the research in this area is still controversial. The aim of this meta-analysis was to analyze the role of vitamin D supplementation in the treatment of asthma patients.

Materials and Methods

Randomized Controlled Trials (RCTs) of vitamin D supplementation in asthma were searched in PubMed, EMBASE, and the Cochrane library. Primary outcomes were forced expiratory volume in one second (FEV1), asthma exacerbations, Asthma Control Test scores (ACT scores), and fractional exhaled nitric oxide (FENO).

Results

A total of 10 RCTs were included, including 1,349 patients. Vitamin D supplementation didn't affect the ACT scores (SMD = 0.04, 95% CI = -0.13 to 0.21, P = 0.87), FEV1 (SMD = 0.04, 95% CI = -0.35 to 0.43, P < 0.01) and FENO (SMD = -0.01, 95% CI = -0.22 to 0.20, P = 0.27), but reduced the rate of asthma exacerbations (RR = 0.69, 95% CI = 0.41 to 0.88, P < 0.01), especially in subgroups of children (RR = 0.46, 95% CI = 0.30 to 0.70, P = 0.83) and follow up time less than 6 months (RR = 0.45, 95% CI = 0.32 to 0.63, P = 0.95). Additionally, though there was only one study included in the subgroup, it significantly enhanced FEV1 at the last visit for patients whose FEV1 baseline value was less than 70% (SMD = 0.94, 95% CI = 0.47 to 1.41).

Conclusion

Vitamin D supplementation can reduce asthma exacerbations, especially in children, and within 6 months of follow up time. In addition, vitamin D has a positive effect on improving FEV1 of patients whose FEV1 baseline value is less than 70%, but more RCTs are still needed to support this conclusion.

Systematic Review Registration

[https://inplasy.com], identifier [10.37766/inplasy20 22.6.0049].

Severe asthma in children: Description of a large multidisciplinary clinical cohort

BACKGROUND

Children with severe asthma have substantial morbidity and healthcare utilization. Pediatric severe asthma is a heterogeneous disease, and a multidisciplinary approach can improve the diagnosis and management of these children.

METHODS

We reviewed the electronic health records for patients seen in the Severe Asthma Clinic (SAC) at UPMC Children's Hospital of Pittsburgh between August 2012 and October 2019.

RESULTS

Of the 110 patients in whom we extracted data, 46% were female, 48% were Black/African American, and 41% had ≥1 admission to the pediatric intensive care unit (PICU) for asthma. Compared to patients without a PICU admission, those with ≥1 PICU admission were more likely to be non-White (64.4% vs. 41.5%, p = 0.031) and more atopic (eosinophil count geometric mean = 673 vs. 319 cells/mm3 , p = 0.002; total IgE geometric mean = 754 vs. 303 KU/L, p = 0.003), and to have lower pre-bronchodilator FEV1 (58.6% [±18.1%] vs. 69.9% [±18.7%], p = 0.002) and elevated FeNO (60% vs. 22%, p = 0.02). In this cohort, 84% of patients were prescribed high-dose ICS/LABA and 36% were on biologics. Following enrollment in the SAC, severe exacerbations decreased from 3.2/year to 2.2/year (p < 0.0001); compared to the year before joining the SAC, in the following year the group had 106 fewer severe exacerbations.

CONCLUSIONS

This large cohort of children with severe asthma had a high level of morbidity and healthcare utilization. Patients with a history of PICU admissions for asthma were more likely to be nonwhite and highly atopic, and to have lower lung function. Our data support a positive impact of a multidisciplinary clinic on patients with severe childhood asthma.

Multi-ancestry genome-wide association study of asthma exacerbations

BACKGROUND

Asthma exacerbations are a serious public health concern due to high healthcare resource utilization, work/school productivity loss, impact on quality of life, and risk of mortality. The genetic basis of asthma exacerbations has been studied in several populations, but no prior study has performed a multi-ancestry meta-analysis of genome-wide association studies (meta-GWAS) for this trait. We aimed to identify common genetic loci associated with asthma exacerbations across diverse populations and to assess their functional role in regulating DNA methylation and gene expression.

METHODS

A meta-GWAS of asthma exacerbations in 4989 Europeans, 2181 Hispanics/Latinos, 1250 Singaporean Chinese, and 972 African Americans analyzed 9.6 million genetic variants. Suggestively associated variants (p ≤ 5 × 10-5 ) were assessed for replication in 36,477 European and 1078 non-European asthma patients. Functional effects on DNA methylation were assessed in 595 Hispanic/Latino and African American asthma patients and in publicly available databases. The effect on gene expression was evaluated in silico.

RESULTS

One hundred and twenty-six independent variants were suggestively associated with asthma exacerbations in the discovery phase. Two variants independently replicated: rs12091010 located at vascular cell adhesion molecule-1/exostosin like glycosyltransferase-2 (VCAM1/EXTL2) (discovery: odds ratio (ORT allele ) = 0.82, p = 9.05 × 10-6 and replication: ORT allele  = 0.89, p = 5.35 × 10-3 ) and rs943126 from pantothenate kinase 1 (PANK1) (discovery: ORC allele  = 0.85, p = 3.10 × 10-5 and replication: ORC allele  = 0.89, p = 1.30 × 10-2 ). Both variants regulate gene expression of genes where they locate and DNA methylation levels of nearby genes in whole blood.

CONCLUSIONS

This multi-ancestry study revealed novel suggestive regulatory loci for asthma exacerbations located in genomic regions participating in inflammation and host defense.

Environmental effects on acute exacerbations of respiratory diseases: A real-world big data study

BACKGROUND

The effects of weather periods, race/ethnicity, and sex on environmental triggers for respiratory exacerbations are not well understood. This study linked the OneFlorida network (~15 million patients) with an external exposome database to analyze environmental triggers for asthma, bronchitis, and COPD exacerbations while accounting for seasonality, sex, and race/ethnicity.

METHODS

This is a case-crossover study of OneFlorida database from 2012 to 2017 examining associations of asthma, bronchitis, and COPD exacerbations with exposures to heat index, PM 2.5 and O 3. We spatiotemporally linked exposures using patients' residential addresses to generate average exposures during hazard and control periods, with each case serving as its own control. We considered age, sex, race/ethnicity, and neighborhood deprivation index as potential effect modifiers in conditional logistic regression models.

RESULTS

A total of 1,148,506 exacerbations among 533,446 patients were included. Across all three conditions, hotter heat indices conferred increasing exacerbation odds, except during November to March, where the opposite was seen. There were significant differences when stratified by race/ethnicity (e.g., for asthma in April, May, and October, heat index quartile 4, odds were 1.49 (95% confidence interval (CI) 1.42-1.57) for Non-Hispanic Blacks and 2.04 (95% CI 1.92-2.17) for Hispanics compared to 1.27 (95% CI 1.19-1.36) for Non-Hispanic Whites). Pediatric patients' odds of asthma and bronchitis exacerbations were significantly lower than adults in certain circumstances (e.g., for asthma during June - September, pediatric odds 0.71 (95% CI 0.68-0.74) and adult odds 0.82 (95% CI 0.79-0.85) for the highest quartile of PM 2.5).

CONCLUSION

This study of acute exacerbations of asthma, bronchitis, and COPD found exacerbation risk after exposure to heat index, PM 2.5 and O 3 varies by weather period, age, and race/ethnicity. Future work can build upon these results to alert vulnerable populations to exacerbation triggers.

The Role of Comorbidities in Difficult-to-Control Asthma in Adults and Children

Assessment of asthma comorbidities, conditions that adversely affect the pathobiology of asthma or impair its response to therapies, is a fundamental step in the evaluation and management of patients with difficult-to-treat asthma. Identifying and effectively treating asthma comorbidities, such as obesity, obstructive sleep apnea, and chronic sinusitis with nasal polyps, may improve asthma control and reduce exacerbations. In addition, identifying comorbid T2 inflammatory conditions may help guide optimal selection of biologic therapies. Here, we describe common comorbid conditions found in adult and pediatric difficult-to-control asthma, discuss evidence for the association with asthma morbidity and treatment benefit, and provide information on how and when to assess comorbidities.

Asthma in paediatric intensive care in England residents: observational study

Despite high prevalence of asthma in children in the UK, there were no prior report on asthma admissions in paediatric intensive care units (PICU). We investigated the epidemiology and healthcare resource utilisation in children with asthma presenting to PICUs in England. PICANet, a UK national PICU database, was queried for asthma as the primary reason for admission, of children resident in England from April 2006 until March 2013. There were 2195 admissions to PICU for a median stay of 1.4 days. 59% were males and 51% aged 0–4 years. The fourth and fifth most deprived quintiles represented 61% (1329) admissions and 73% (11) of the 15 deaths. Deaths were most frequent in 10–14 years age (n = 11, 73%), with no deaths in less than 5 years age. 38% of admissions (828/2193) received invasive ventilation, which was more frequent with increasing deprivation (13% (108/828) in least deprived to 31% (260/828) in most deprived) and with decreasing age (0–4-year-olds: 49%, 409/828). This first multi-centre PICU study in England found that children from more deprived neighbourhoods represented the majority of asthma admissions, invasive ventilation and deaths in PICU. Children experiencing socioeconomic deprivation could benefit from enhanced asthma support in the community.

Management of Children with Acute Asthma Attack: A RAND/UCLA Appropriateness Approach

Bronchial asthma is the most frequent chronic disease in children and affects up to 20% of the pediatric population, depending on the geographical area. Asthma symptoms vary over time and in intensity, and acute asthma attack can resolve spontaneously or in response to therapy. The aim of this project was to define the care pathway for pediatric patients who come to the primary care pediatrician or Emergency Room with acute asthmatic access. The project was developed in the awareness that for the management of these patients, broad coordination of interventions in the pre-hospital phase and the promotion of timely and appropriate assistance modalities with the involvement of all health professionals involved are important. Through the application of the RAND method, which obliges to discuss the statements derived from the guidelines, there was a clear increase in the concordance in the behavior on the management of acute asthma between primary care pediatricians and hospital pediatricians. The RAND method was found to be useful for the selection of good practices forming the basis of an evidence-based approach, and the results obtained form the basis for further interventions that allow optimizing the care of the child with acute asthma attack at the family and pediatric level. An important point of union between the primary care pediatrician and the specialist hospital pediatrician was the need to share spirometric data, also including the use of new technologies such as teleconsultation. Monitoring the progress of asthma through spirometry could allow the pediatrician in the area to intervene early by modifying the maintenance therapy and help the patient to achieve good control of the disease.

Severe acute asthma at the pediatric intensive care unit: can we link the clinical phenotypes to immunological endotypes?

INTRODUCTION

The clinical phenotype of severe acute asthma at the pediatric intensive care unit (PICU) is highly heterogeneous. However, current treatment is still based on a 'one-size-fits-all approach'.

AREAS COVERED

We aim to give a comprehensive description of the clinical characteristics of pediatric patients with severe acute asthma admitted to the PICU and available immunological biomarkers, providing the first steps toward precision medicine for this patient population. A literature search was performed using PubMed for relevant studies on severe acute (pediatric) asthma.

EXPERT OPINION

Omics technologies should be used to investigate the relationship between cellular molecules and pathways, and their clinical phenotypes. Inflammatory phenotypes might guide bedside decisions regarding the use of corticosteroids, neutrophil modifiers and/or type of beta-agonist. A next step toward precision medicine should be inclusion of these patients in clinical trials on biologics.

Evaluation of Risk Scores to Predict Pediatric Severe Asthma Exacerbations

BACKGROUND

Asthma exacerbations commonly lead to unplanned health care utilization and are costly. Early identification of children at increased risk of asthma exacerbations would allow a proactive management approach.

OBJECTIVE

We evaluated common asthma risk factors to predict the probability of exacerbation for individual children aged 0-21 years using data from the electronic medical record (EMR).

METHODS

We analyzed longitudinal EMR data for over 3000 participants with asthma seen at Cincinnati Children's Hospital Medical Center over a 7-year period. The study population was divided into 3 age groups: 0-4, 5-11, and 12-21 years. Each age group was divided into a derivation cohort and a validation cohort, which were used to build a risk score model. We predicted risk of exacerbation in the next 12 months, validated the scores by risk stratum, and developed a clinical tool to determine the risk level based on this model.

RESULTS

Risk model results were confirmed with validation cohorts by calendar year and age groups. Race, allergic sensitization, and smoke exposure were each important risk factors in the 0-4 age group. Abnormal spirometry and obesity were more sensitive predictors of exacerbation in children >12 years. For each age group, a higher expanded score was associated with a higher predicted probability of an asthma exacerbation in the subsequent year.

CONCLUSION

This asthma exacerbation prediction model, and the associated clinical tool, may assist clinicians in identifying children at high risk for exacerbation that may benefit from more aggressive management and targeted risk mitigation.

The Relationship Between Vitamin D and Asthma Exacerbation

Asthma is a chronic airway inflammatory condition that affects millions of people worldwide. It presents with reversible bronchoconstriction that makes it difficult for patients to breathe. Asthma flare-ups have several triggers, but the symptoms are similar, including wheezing, coughing, shortness of breath, and chest tightness. Severe asthma exacerbation is described as symptomatic asthma that is unresponsive to inhaled asthma medications and is only responsive to steroids in oral or intravenous forms. Asthma-related deaths occur during episodes of asthma exacerbation. Vitamin D is a steroid-derived vitamin produced by the body and found in some foods. Administration of doses of vitamin D can also help maintain an adequate level of the vitamin. Vitamin D plays a vital role in regulating the level of calcium in the body and bone remodeling processes. It also has an immunomodulatory effect on innate and adaptive immunity within the body and that partially explains its links to inflammation-induced epithelial changes seen in asthma. We conducted this literature review by selecting articles from PubMed and Cumulated Index to Nursing and Allied Health Literature (CINAHL) Plus databases to investigate the relationship between vitamin D level and asthma exacerbation. From the studies, we found that asthmatic patients have low vitamin D levels during an asthma exacerbation. However, supplementing vitamin D may not reduce the rates of asthma exacerbation except in adult asthmatic patients with low levels of vitamin D.

Evaluation of efficiency and safety of oral corticosteroid therapy in children patients with exacerbations of asthma: A protocol for systematic review and meta-analysis

BACKGROUND

Asthma is the most frequently occurring obstructive airway disease, it inflicts the highest morbidity among children. Among the paediatric populace, severe exacerbations of asthma are a common reason behind patient consultations and hospitalizations. Oral corticosteroids are a primary component in the treatment of asthma exacerbations; however, there is controversy regarding how corticosteroids functions.

METHODS

The present review will conduct a search on MEDLINE, EMBASE, Cochrane Library, China National Knowledge Infrastructure, and Chinese BioMedical Literature. The search will cover the databases from their beginning to May 2021. The search aims to identify all the randomized controlled studies on oral corticosteroids in treating children with asthma exacerbations. Two independent authors will choose studies, perform data extraction, and use an appropriate tool to assess the bias risk in the selected articles. Moreover, a sensitivity analysis will be performed to assess the robustness of the results. The RevMan (version 5.3) software will be employed to perform data synthesis and statistical analysis.

RESULTS

This study will examine the efficiency and safeness of oral corticosteroid therapy to treat children with asthma exacerbations by pooling the results of individual studies.

CONCLUSION

The findings of this study will provide vigorous evidence to judge whether oral corticosteroid therapy is an efficiency strategy to treat patients with asthmatic exacerbations.

OSF REGISTRATION NUMBER

May 20, 2021.osf.io/3ghjt. (https://osf.io/3ghjt/).

Paediatrics: how to manage acute asthma exacerbations

Background

Asthma is the most common chronic disease of childhood and a major source of childhood health burden worldwide. These burdens are particularly marked when children experience characteristic ‘symptom flare-ups’ or acute asthma exacerbations (AAEs). AAE are associated with significant health and economic impacts, including acute Emergency Department visits, occasional hospitalizations, and rarely, death. To treat children with AAE, several medications have been studied and used.

Methods

We conducted a narrative review of the literature with the primary objective of understanding the evidence of their efficacy. We present this efficacy evidence in the context of a general stepwise management pathway for paediatric AAEs. This framework is developed from the combined recommendations of eight established (inter)national paediatric guidelines.

Discussion

Management of paediatric AAE centres around four major care goals: (1) immediate and objective assessment of AAE severity; (2) prompt and effective medical interventions to decrease respiratory distress and improve oxygenation; (3) appropriate disposition of patient; and (4) safe discharge plans. Several medications are currently recommended with varying efficacies, including heliox, systemic corticosteroids, first-line bronchodilators (salbutamol/albuterol), adjunctive bronchodilators (ipratropium bromide, magnesium sulfate) and second-line bronchodilators (aminophylline, i.v. salbutamol, i.v. terbutaline, epinephrine, ketamine). Care of children with AAE is further enhanced using clinical severity scoring, pathway-driven care and after-event discharge planning.

Conclusions

AAEs in children are primarily managed by medications supported by a growing body of literature. Continued efforts to study the efficacy of second-line bronchodilators, integrate AAE management with long-term asthma control and provide fair/equitable care are required.

Precision Medicine for Paediatric Severe Asthma: Current Status and Future Direction

Asthma is a heterogeneous disease, characterised by different phenotypes and endotypes. Precision medicine in asthma refers to the implementation of a targeted therapy for each individual child, based on the identification of treatable traits, including environmental, immunological and genetic factors. Severe asthma in children is associated with increased hospitalisation rates, a lower quality of life, increased healthcare costs and an increased mortality. In the era of new molecular biologics treatments, it is essential to improve deep phenotyping of children with severe asthma in order to deliver the most effective treatment to each individual child. In this review, we discuss the personalised approach to the assessment and management of severe asthma. We explore the indications and use of the currently licensed biologics, as well as the potential of other emerging treatments.

Using Computational Methods to Improve Integrated Disease Management for Asthma and Chronic Obstructive Pulmonary Disease: Protocol for a Secondary Analysis

Background

Asthma and chronic obstructive pulmonary disease (COPD) impose a heavy burden on health care. Approximately one-fourth of patients with asthma and patients with COPD are prone to exacerbations, which can be greatly reduced by preventive care via integrated disease management that has a limited service capacity. To do this well, a predictive model for proneness to exacerbation is required, but no such model exists. It would be suboptimal to build such models using the current model building approach for asthma and COPD, which has 2 gaps due to rarely factoring in temporal features showing early health changes and general directions. First, existing models for other asthma and COPD outcomes rarely use more advanced temporal features, such as the slope of the number of days to albuterol refill, and are inaccurate. Second, existing models seldom show the reason a patient is deemed high risk and the potential interventions to reduce the risk, making already occupied clinicians expend more time on chart review and overlook suitable interventions. Regular automatic explanation methods cannot deal with temporal data and address this issue well.

Objective

To enable more patients with asthma and patients with COPD to obtain suitable and timely care to avoid exacerbations, we aim to implement comprehensible computational methods to accurately predict proneness to exacerbation and recommend customized interventions.

Methods

We will use temporal features to accurately predict proneness to exacerbation, automatically find modifiable temporal risk factors for every high-risk patient, and assess the impact of actionable warnings on clinicians’ decisions to use integrated disease management to prevent proneness to exacerbation.

Results

We have obtained most of the clinical and administrative data of patients with asthma from 3 prominent American health care systems. We are retrieving other clinical and administrative data, mostly of patients with COPD, needed for the study. We intend to complete the study in 6 years.

Conclusions

Our results will help make asthma and COPD care more proactive, effective, and efficient, improving outcomes and saving resources.

International Registered Report Identifier (IRRID)

PRR1-10.2196/27065

A genome-wide association study of severe asthma exacerbations in Latino children and adolescents

Severe asthma exacerbations are a major cause of school absences and healthcare costs in children, particularly those in high-risk racial/ethnic groups.To identify susceptibility genes for severe asthma exacerbations in Latino children and adolescents, we conducted a meta-analysis of genome-wide association studies (GWAS) in 4010 Latino youth with asthma in four independent cohorts, including 1693 Puerto Ricans, 1019 Costa Ricans, 640 Mexicans, 256 Brazilians and 402 members of other Latino subgroups. We then conducted methylation quantitative trait locus, expression quantitative trait locus and expression quantitative trait methylation analyses to assess whether the top single nucleotide polymorphism (SNP) in the meta-analysis is linked to DNA methylation and gene expression in nasal (airway) epithelium in separate cohorts of Puerto Rican and Dutch children and adolescents.In the meta-analysis of GWAS, an SNP in FLJ22447 (rs2253681) was significantly associated with 1.55 increased odds of severe asthma exacerbation (95% CI 1.34-1.79, p=6.3×10-9). This SNP was significantly associated with DNA methylation of a CpG site (cg25024579) at the FLJ22447 locus, which was in turn associated with increased expression of KCNJ2-AS1 in nasal airway epithelium from Puerto Rican children and adolescents (β=0.10, p=2.18×10-7).SNP rs2253681 was significantly associated with both DNA methylation of a cis-CpG in FLJ22447 and severe asthma exacerbations in Latino youth. This may be partly explained by changes in airway epithelial expression of a gene recently implicated in atopic asthma in Puerto Rican children and adolescents (KCNJ2-AS1).

Territory-wide Study on Hospital Admissions for Asthma exacerbation in COVID-19 Pandemic

Rationale: Patients with asthma were advised to avoid coronavirus disease (COVID-19) and comply with medication during the COVID-19 pandemic. Respiratory tract infection is a common cause of asthma exacerbations. There has not been evidence suggesting the link between COVID-19 and asthma exacerbation, especially in places with dramatic responses in infection control with universal masking and aggressive social distancing.

Objectives: To assess the number for admissions of asthma exacerbations in January to April 2020 in Hong Kong with reference to admission in the past 5 years.

Methods: Admission records of asthma exacerbations were retrieved from the Clinical Data Analysis and Reporting System. Patients aged 18 years or older with a known history of asthma admitted for asthma exacerbation were included. Log-linear was used to model count, with year and masking used as covariate and further analysis on ambient temperature and length of hospital stays. Fisher’s exact test was used to compare the mortality rate and mechanical ventilation between the periods. Admissions for myocardial infarction, ischemic stroke, and gastric ulcer were included as controls.

Results: The number of admissions for asthma exacerbations significantly decreased by 53.2% (95% confidence interval [CI], 50.4–55.8%) in 2020 compared with monthly average admission in 2015–2019, with a higher magnitude of decrease compared with control diagnoses. Admissions for asthma exacerbations decreased by 2.0% (95% CI, 1.8–2.2%) with every 1°C (1.8°F) increase in temperature and by 0.8% with every 1% increase in masking (95% CI, 0.8–0.9%).

Conclusions: Hospitalization number for asthma exacerbations significantly decreased in early 2020, with similar length of stay. This was observed with concomitant practice of universal masking and social distancing during the COVID-19 pandemic in Hong Kong. We proposed that universal masking and social distancing reduced respiratory viral infection, leading to fewer hospital admissions for asthma exacerbations.

Potentially avoidable hospitalization for asthma in children and adolescents by migrant status: results from the Italian Network for Longitudinal Metropolitan Studies

Background

Global migration toward Europe is increasing. Providing health assistance to migrants is challenging because numerous barriers limit their accessibility to health services. Migrants may be at a greater risk of developing asthma and receiving lower quality healthcare assistance than non-migrants. We aim to investigate whether immigrants as children and adolescents have higher rates of potentially avoidable hospitalization (PAH) for asthma compared to Italians.

Methods

We performed a retrospective longitudinal study using six cohorts of 2–17-year-old residents in North and Central Italy from 01/01/2001 to 31/12/2014 (N = 1,256,826). We linked asthma hospital discharges to individuals using anonymized keys. We estimated cohort-specific age and calendar-year-adjusted asthma PAH rate ratios (HRRs) and 95% confidence intervals (95%CIs) among immigrants compared to Italians. We applied a two-stage random effect model to estimate asthma PAH meta-analytic rate ratios (MHRRs). We analyzed data by gender and geographical area of origin countries.

Results

Three thousand three hundred four and 471 discharges for asthma PAH occurred among Italians and immigrants, respectively. Compared to Italians, the asthma PAH cohort-specific rate was higher for immigrant males in Bologna (HRR:2.42; 95%CI:1.53–3.81) and Roma (1.22; 1.02–1.45), and for females in Torino (1.56; 1.10–2.20) and Roma (1.82; 1.50–2.20). Asthma PAH MHRRs were higher only among immigrant females (MHRRs:1.48; 95%CI:1.18–1.87). MHRRs by area of origin were 63 to 113% higher among immigrants, except for Central-Eastern Europeans (0.80; 0.65–0.98).

Conclusion

The asthma PAH meta-analytic rate was higher among female children and adolescent immigrants compared to Italians, with heterogeneity among cohorts showing higher cohort-specific PAH also among males, with some differences by origin country. Access to primary care for children and adolescent immigrants should be improved and immigrants should be considered at risk of severe asthma outcomes and consequently targeted by clinicians.

The Genomics and Metagenomics of Asthma Severity (GEMAS) Study: Rationale and Design

Asthma exacerbations are a major contributor to the global disease burden, but no significant predictive biomarkers are known. The Genomics and Metagenomics of Asthma Severity (GEMAS) study aims to assess the role of genomics and the microbiome in severe asthma exacerbations. Here, we present the design of GEMAS and the characteristics of patients recruited from March 2018 to March 2020. Different biological samples and demographic and clinical variables were collected from asthma patients recruited by allergy and pulmonary medicine units in several hospitals from Spain. Cases and controls were defined by the presence/absence of severe asthma exacerbations in the past year (oral corticosteroid use, emergency room visits, and/or asthma-related hospitalizations). A total of 137 cases and 120 controls were recruited. After stratifying by recruitment location (i.e., Canary Islands and Basque Country), cases and controls did not differ for most demographic and clinical variables (p > 0.05). However, cases showed a higher proportion of characteristics inherent to asthma exacerbations (impaired lung function, severe disease, uncontrolled asthma, gastroesophageal reflux, and use of asthma medications) compared to controls (p < 0.05). Similar results were found after stratification by recruitment unit. Thereby, asthma patients enrolled in GEMAS are balanced for potential confounders and have clinical characteristics that support the phenotype definition. GEMAS will improve the knowledge of potential biomarkers of asthma exacerbations.

A genome-wide association study of asthma hospitalizations in adults

BACKGROUND

Little is known about the genetic determinants of severe asthma exacerbations.

OBJECTIVES

We aimed to identify genetic variants associated with asthma hospitalizations.

METHODS

We conducted a genome-wide association study of asthma hospitalizations in 34,167 white British adults with asthma, 1,658 of whom had at least 1 asthma-related hospitalization. This analysis was conducted by using logistic regression under an additive genetic model with adjustment for age, sex, body mass index, smoking status, and the first 5 principal components derived from genotypic data. We then analyzed data from 2 cohorts of Latino children and adolescents for replication and conducted quantitative trait locus and functional annotation analyses.

RESULTS

At the chromosome 6p21.3 locus, the single-nucleotide polymorphism (SNP) rs56151658 (8 kb from the promoter of HLA-DQB1) was most significantly associated with asthma hospitalizations (for test allele A, odds ratio = 1.36 [95% CI = 1.22-1.52]; P = 3.11 × 10^-8); 21 additional SNPs in this locus were associated with asthma hospitalizations at a P value less than 1 × 10^-6. In the replication cohorts, multiple SNPs in strong linkage disequilibrium with rs56151658 were associated with severe asthma exacerbations at a P value of .01 or less in the same direction of association as in the discovery cohort. Three HLA genes (HLA-DQA2, HLA-DRB6, and HLA-DOB) were also shown to mediate the estimated effects of the SNPs associated with asthma hospitalizations through effects on gene expression in lung tissue.

CONCLUSIONS

We identified strong candidate genes for asthma hospitalizations in adults in the region for class II HLA genes through genomic, quantitative trait locus, and summary data-based mendelian randomization analyses.

Asthma attacks in children are always preceded by poor asthma control: myth or maxim?

Some, but not all, asthma exacerbations in children are preceded by poor asthma control https://bit.ly/3muIy6h.

Risk factors for asthma exacerbation among Hajj pilgrims: a case study from DKI Jakarta, Indonesia

BACKGROUND Hajj pilgrims are prone to asthma exacerbation because of the high transmission rate of respiratory infections, severe environmental factors, and high-intensity activities during the Hajj. Well-controlled asthma status and preventive efforts prior to the Hajj could reduce such exacerbations. This research aimed to determine the risk factors of asthma exacerbation during the Hajj to help establish preventive measures. METHODS Participants were evaluated at community health centers (puskesmas) through history taking, physical examination, and spirometry. The risk factors examined included a history of exacerbation one year before the Hajj, obesity, comorbidities (e.g., diabetes mellitus, hypertension, coronary heart disease), lung function, smoking, fitness level, and influenza vaccination. Asthma exacerbation while in Saudi Arabia was determined through direct observations by authors and physicians assigned to Hajj pilgrim groups and analysis of data obtained from questionnaires distributed to the pilgrims before their departure. Odds ratios (OR) were calculated using logistic regression. RESULTS Among 68 pilgrims with asthma, exacerbation occurred in 27 (40%) pilgrims. Risk of asthma exacerbation was significantly increased in the pilgrims with a history of exacerbation one year before the Hajj (OR = 4.27; 95% confidence interval [CI] = 1.156–15.829; p = 0.029) and obesity grade II (OR = 4.02; 95% CI = 1.151–14.097; p = 0.029). Other factors, including smoking, comorbidities, lung function, fitness level, obesity grade I, and influenza vaccination, were not significantly related to exacerbation. CONCLUSIONS Obesity grade II and history of asthma exacerbation one year before the Hajj are strong factors for asthma exacerbation during Hajj pilgrims.

A worldwide charter for all children with asthma

Childhood asthma is a huge global health burden. The spectrum of disease, diagnosis, and management vary depending on where children live in the world and how their community can care for them. Global improvement in diagnosis and management has been unsatisfactory, despite ever more evidence-based guidelines. Guidelines alone are insufficient and need supplementing by government support, changes in policy, access to diagnosis and effective therapy for all children, with research to improve implementation. We propose a worldwide charter for all children with asthma, a roadmap to better education and training which can be adapted for local use. It includes access to effective basic asthma medications. It is not about new expensive medications and biologics as much can be achieved without these. If implemented carefully, the overall cost of care is likely to fall and the global future health and life chance of children with asthma will greatly improve. The key to success will be community involvement together with the local and national development of asthma champions. We call on governments, institutions, and healthcare services to support its implementation.

Feature engineering with clinical expert knowledge: A case study assessment of machine learning model complexity and performance

Incorporating expert knowledge at the time machine learning models are trained holds promise for producing models that are easier to interpret. The main objectives of this study were to use a feature engineering approach to incorporate clinical expert knowledge prior to applying machine learning techniques, and to assess the impact of the approach on model complexity and performance. Four machine learning models were trained to predict mortality with a severe asthma case study. Experiments to select fewer input features based on a discriminative score showed low to moderate precision for discovering clinically meaningful triplets, indicating that discriminative score alone cannot replace clinical input. When compared to baseline machine learning models, we found a decrease in model complexity with use of fewer features informed by discriminative score and filtering of laboratory features with clinical input. We also found a small difference in performance for the mortality prediction task when comparing baseline ML models to models that used filtered features. Encoding demographic and triplet information in ML models with filtered features appeared to show performance improvements from the baseline. These findings indicated that the use of filtered features may reduce model complexity, and with little impact on performance.

Addressing the risk domain in the long-term management of pediatric asthma

There is growing concern regarding the long-term outcomes of early and poorly controlled childhood asthma, either of which can potentially lead to the development of severe asthma in adults and irrecoverable loss of lung function leading to chronic obstructive pulmonary disease. These outcomes of inadequately controlled asthma should prompt a change in practice to better and/or earlier identify children at risk of adverse respiratory outcomes of asthma, to monitor disease progression, and to design intervention strategies that could either prevent or reverse asthma progression in children. The careful follow-up of spirometry over time-in the form of lung function trajectories, the application of biomarkers to assist in the diagnosis of early asthma and medication selection for these patients, as well as methods to identify patients at risk of asthma attacks-can be used to develop individualized management strategies for children with asthma. It is now time for asthma specialists to communicate this information to patients, parents, and primary care physicians and to incorporate them into routine clinical assessments of children with asthma. In time, these concepts of risk management and prevention can be refined to provide a more comprehensive approach to asthma care so as to prevent adverse respiratory outcomes from poorly controlled childhood asthma.

Efficacy and safety of inhalation budesonide in the treatment of pediatric asthma in the emergency department: a systematic review and meta-analysis

BACKGROUND

This study was aimed to evaluate the beneficial role of inhalation budesonide(BUD) in improving the pulmonary functions, and reducing the hospital admission rate, worsening of asthma and commonly encountered adverse events in pediatric asthma.

METHODS

The electronic search was performed using PubMed, Scopus, CENTRAL (Cochrane Central Register of Controlled Trials) and Google scholar databases to identify the randomized control trials(RCTs).

RESULTS

21 RCTs involving 12,787 subjects were included. The meta-analysis revealed that the BUD has reduced the hospitalization rate (Mantel-Haenszel (M-H), random effects odd ratio (RE-OR) of 0.34, p = 0.003, I² = 75%), and worsening of asthma (M-H, RE-OR 0.38, p = 0.001, I² = 73%); significantly improved the pulmonary functions such as FEV1 (Inverse variance (IV): 1.05, p < 0.0001, I² = 94%), PEFR (IV: 1.40, p < 0.0001, I² = 87%), morning PEF (IV: 1.04, p < 0.0001, I² = 91%), and evening PEF (IV: 1.29, p < 0.0001, I² = 92%) compared to control. Further, the incidences of adverse events like Pharyngitis (M-H, RE-OR 0.88, at 95% CI, p = 0.69, I² = 0%), Sinusitis (M-H, RE-OR 0.78, p = 0.79, I² = 0%), Respiratory infections (M-H, RE-OR 0.96, p = 0.46, I² = 0%), Otitis media (M-H, RE-OR 0.82, p = 0.32, I² = 12%) and Fever (M-H, RE-OR 0.78, p = 0.64, I² = 0%) were almost same between BUD and control.

CONCLUSION

The outcomes of the meta-analysis suggest that high-dose inhalation BUD could benefit the pediatric patients in minimizing the worsening of asthma and hospitalization rate, along with improving the pulmonary functions, with negligible adverse drug reactions.

Developing a Model to Predict Hospital Encounters for Asthma in Asthmatic Patients: Secondary Analysis

Background

As a major chronic disease, asthma causes many emergency department (ED) visits and hospitalizations each year. Predictive modeling is a key technology to prospectively identify high-risk asthmatic patients and enroll them in care management for preventive care to reduce future hospital encounters, including inpatient stays and ED visits. However, existing models for predicting hospital encounters in asthmatic patients are inaccurate. Usually, they miss over half of the patients who will incur future hospital encounters and incorrectly classify many others who will not. This makes it difficult to match the limited resources of care management to the patients who will incur future hospital encounters, increasing health care costs and degrading patient outcomes.

Objective

The goal of this study was to develop a more accurate model for predicting hospital encounters in asthmatic patients.

Methods

Secondary analysis of 334,564 data instances from Intermountain Healthcare from 2005 to 2018 was conducted to build a machine learning classification model to predict the hospital encounters for asthma in the following year in asthmatic patients. The patient cohort included all asthmatic patients who resided in Utah or Idaho and visited Intermountain Healthcare facilities during 2005 to 2018. A total of 235 candidate features were considered for model building.

Results

The model achieved an area under the receiver operating characteristic curve of 0.859 (95% CI 0.846-0.871). When the cutoff threshold for conducting binary classification was set at the top 10.00% (1926/19,256) of asthmatic patients with the highest predicted risk, the model reached an accuracy of 90.31% (17,391/19,256; 95% CI 89.86-90.70), a sensitivity of 53.7% (436/812; 95% CI 50.12-57.18), and a specificity of 91.93% (16,955/18,444; 95% CI 91.54-92.31). To steer future research on this topic, we pinpointed several potential improvements to our model.

Conclusions

Our model improves the state of the art for predicting hospital encounters for asthma in asthmatic patients. After further refinement, the model could be integrated into a decision support tool to guide asthma care management allocation.

International Registered Report Identifier (IRRID)

RR2-10.2196/resprot.5039

Associated Factors for Asthma Severity in Korean Children: A Korean Childhood Asthma Study

Purpose

Childhood asthma has a considerable social impact and economic burden, especially in severe asthma. This study aimed to identify the proportion of childhood asthma severity and to evaluate associated factors for greater asthma severity.

Methods

This study was performed on 667 children aged 5–15 years with asthma from the nationwide 19 hospitals in the Korean childhood Asthma Study (KAS). Asthma was classified as mild intermittent, mild persistent, and moderate/severe persistent groups according to the National Asthma Education and Prevention Program recommendations. Multinomial logistic regression models were used to identify the associated factors for greater asthma severity.

Results

Mild persistent asthma was most prevalent (39.0%), followed by mild intermittent (37.6%), moderate persistent (22.8%), and severe persistent asthma (0.6%). Onset later than 6 years of age (adjusted odds ratio [aOR], 1.69 for mild persistent asthma; aOR, 1.92 for moderate/severe persistent asthma) tended to increase asthma severity. Exposure to environmental tobacco smoke (aOR, 1.53 for mild persistent asthma; aOR, 1.85 for moderate/severe persistent asthma), and current dog ownership with sensitization to dog dander (aOR, 5.86 for mild persistent asthma; aOR, 6.90 for moderate/severe persistent asthma) showed increasing trends with greater asthma severity. Lower maternal education levels (aOR, 2.32) and no usage of an air purifier in exposure to high levels of outdoor air pollution (aOR, 1.76) were associated with moderate/severe persistent asthma.

Conclusions

Modification of identified environmental factors associated with greater asthma severity might help better control childhood asthma, thereby reducing the disease burden due to childhood asthma.

Bronchodilator Dose Responsiveness in Children and Adolescents: Clinical Features and Association with Future Asthma Exacerbations

BACKGROUND

Bronchodilator reversibility measures are often associated with poor asthma outcomes in children. Whether bronchodilator dose responsiveness is similarly useful in children is unclear.

OBJECTIVE

We hypothesized that children and adolescents requiring higher doses of bronchodilator to achieve maximal bronchodilation would have unique risk factors and increased risk of future exacerbation.

METHODS

Children (6-11 years, N = 299) and adolescents (12-21 years, N = 331) with confirmed asthma underwent clinical phenotyping procedures and a test of maximal bronchodilation with escalating doses of albuterol sulfate up to 720 mcg. Outcome measures were assessed at 12 months and included exacerbations treated with systemic corticosteroids, emergency department (ED) visits, and hospitalizations for asthma.

RESULTS

A total of 6.7% of children and 9.3% of adolescents had poor bronchodilator dose responsiveness, defined as attainment of maximal forced expiratory volume in 1 second with 720 mcg albuterol. Risk factors included type 2 inflammation, prior exacerbations, and greater asthma severity; historical pneumonia and tobacco exposure were also risk factors in children. Children and adolescents with poor bronchodilator dose responsiveness did not have increased current symptoms or impaired quality of life, but had approximately 2-fold increased odds of exacerbation or ED visit and approximately 3-fold increased odds of hospitalization by 12 months, independent of airflow obstruction.

CONCLUSIONS

Bronchodilator dose responsiveness may be useful for phenotyping and may be of utility in practice and future studies focused on asthma outcomes or quantification of treatment responses. In children and adolescents, this phenotype of poor bronchodilator responsiveness may be associated with periods of relatively stable disease yet marked airway constriction in response to triggers, including tobacco smoke, respiratory infections/pneumonia, and aeroallergens.

Respiratory pathogens and clinical outcomes in children with an asthma exacerbation: A systematic review

BACKGROUND

In asthmatic children, respiratory pathogens are identified in 60%-80% of asthma exacerbations, contributing to a significant burden of illness. The role of pathogens in the clinical evolution of exacerbations is unknown.

OBJECTIVE

We systematically reviewed the association between the presence of pathogens and clinical outcomes in children with an asthma exacerbation.

METHOD

PubMed, EMBASE, BIOSIS, and the Cochrane Central Register of Controlled Trials were searched up to October 2016 for studies reporting on respiratory pathogen exposure and clinical outcome. The Risk of Bias in Non-Randomized Studies of Interventions tool was used for quality assessment.

RESULTS

Twenty-eight observational studies (N = 4,224 children) reported on 112 different associations between exposure to any pathogen (n = 45), human rhinovirus (HRV; n = 34), atypical bacteria (n = 21), specific virus (n = 11), or bacteria (n = 1) and outcomes of exacerbation severity (n = 26), health care use (n = 38), treatment response (n = 19), and morbidity (n = 29). Restricting the analysis only to comparisons with a low to moderate risk of bias, we observed an association between HRV and higher exacerbation severity on presentation (regression p = .016) and between the presence of any pathogen and emergency department treatment failure (odds ratio [OR] = 1.57; 95% CI 1.04% to 2.37%). High-quality evidence for effect on morbidity or health care use is lacking.

CONCLUSIONS

Further research on the role of pathogen-treatment interaction and outcomes is required to inform the need for point-of-care, real-time testing for pathogens. Studies with a sufficiently large sample size that address selection bias, correctly adjust for confounding, and rigorously report core patient-centred outcomes are necessary to improve knowledge.

Development and validation of an asthma exacerbation prediction model using electronic health record (EHR) data

Objective: Asthma exacerbations are associated with significant morbidity, mortality, and cost. Accurately identifying asthma patients at risk for exacerbation is essential. We sought to develop a risk prediction tool based on routinely collected data from electronic health records (EHRs).Methods: From a repository of EHRs data, we extracted structured data for gender, race, ethnicity, smoking status, use of asthma medications, environmental allergy testing BMI status, and Asthma Control Test scores (ACT). A subgroup of this population of patients with asthma that had available prescription fill data was identified, which formed the primary population for analysis. Asthma exacerbation was defined as asthma-related hospitalization, urgent/emergent visit or oral steroid use over a 12-month period. Univariable and multivariable statistical analysis was completed to identify factors associated with exacerbation. We developed and tested a risk prediction model based on the multivariable analysis.Results: We identified 37,675 patients with asthma. Of those, 1,787 patients with asthma and fill data were identified, and 979 (54.8%) of them experienced an exacerbation. In the multivariable analysis, smoking (OR = 1.69, CI: 1.08-2.64), allergy testing (OR = 2.40, CI: 1.54-3.73), obesity (OR = 1.66, CI: 1.29-2.12), and ACT score reflecting uncontrolled asthma (OR = 1.66, CI: 1.10-2.29) were associated with increased risk of exacerbation. The area-under-the-curve (AUC) of our model in a combined derivation and validation cohort was 0.67.Conclusion: Despite use of rigorous methodology, we were unable to produce a predictive model with an acceptable degree of accuracy and AUC to be clinically useful.

Using Temporal Features to Provide Data-Driven Clinical Early Warnings for Chronic Obstructive Pulmonary Disease and Asthma Care Management: Protocol for a Secondary Analysis

Background

Both chronic obstructive pulmonary disease (COPD) and asthma incur heavy health care burdens. To support tailored preventive care for these 2 diseases, predictive modeling is widely used to give warnings and to identify patients for care management. However, 3 gaps exist in current modeling methods owing to rarely factoring in temporal aspects showing trends and early health change: (1) existing models seldom use temporal features and often give late warnings, making care reactive. A health risk is often found at a relatively late stage of declining health, when the risk of a poor outcome is high and resolving the issue is difficult and costly. A typical model predicts patient outcomes in the next 12 months. This often does not warn early enough. If a patient will actually be hospitalized for COPD next week, intervening now could be too late to avoid the hospitalization. If temporal features were used, this patient could potentially be identified a few weeks earlier to institute preventive therapy; (2) existing models often miss many temporal features with high predictive power and have low accuracy. This makes care management enroll many patients not needing it and overlook over half of the patients needing it the most; (3) existing models often give no information on why a patient is at high risk nor about possible interventions to mitigate risk, causing busy care managers to spend more time reviewing charts and to miss suited interventions. Typical automatic explanation methods cannot handle longitudinal attributes and fully address these issues.

Objective

To fill these gaps so that more COPD and asthma patients will receive more appropriate and timely care, we will develop comprehensible data-driven methods to provide accurate early warnings of poor outcomes and to suggest tailored interventions, making care more proactive, efficient, and effective.

Methods

By conducting a secondary data analysis and surveys, the study will: (1) use temporal features to provide accurate early warnings of poor outcomes and assess the potential impact on prediction accuracy, risk warning timeliness, and outcomes; (2) automatically identify actionable temporal risk factors for each patient at high risk for future hospital use and assess the impact on prediction accuracy and outcomes; and (3) assess the impact of actionable information on clinicians’ acceptance of early warnings and on perceived care plan quality.

Results

We are obtaining clinical and administrative datasets from 3 leading health care systems’ enterprise data warehouses. We plan to start data analysis in 2020 and finish our study in 2025.

Conclusions

Techniques to be developed in this study can boost risk warning timeliness, model accuracy, and generalizability; improve patient finding for preventive care; help form tailored care plans; advance machine learning for many clinical applications; and be generalized for many other chronic diseases.

International Registered Report Identifier (IRRID)

PRR1-10.2196/13783

Exploring the Utility of Noninvasive Type 2 Inflammatory Markers for Prediction of Severe Asthma Exacerbations in Children and Adolescents

BACKGROUND

Noninvasive markers of type 2 inflammation are needed to identify children and adolescents who might benefit from personalized biologic therapy.

OBJECTIVE

We hypothesized that blood eosinophil counts would predict 1 or more acute visits for asthma and that prediction could be improved with the addition of a second, noninvasive type 2 inflammatory biomarker.

METHODS

Children and adolescents 5 to 21 years (N = 589) with an asthma exacerbation necessitating systemic corticosteroid treatment in the previous year completed a characterization visit and telephone calls at 6 and 12 months. The primary outcome was an acute visit for asthma with receipt of systemic corticosteroids. Acute visits were verified by medical record review. Exploratory outcomes included time to first acute visit and hospitalization.

RESULTS

Acute visits occurred in 106 (35.5%) children and 72 (24.8%) adolescents. Elevated blood eosinophils were associated with increased odds and shorter time to first acute visit, but optimal cut-points differed by age (≥150 vs ≥300 cells/μL for children vs adolescents, respectively). The addition of a second marker of type 2 inflammation did not improve prediction in children, but increased the odds and hazard of an acute visit up to 16.2% and 11.9%, respectively, in adolescents. Similar trends were noted for hospitalizations.

CONCLUSIONS

Blood eosinophils and other noninvasive markers of type 2 inflammation may be useful in the clinical assessment of children and adolescents with asthma. However, features of type 2 inflammation vary by age. Whether children and adolescents also respond differently to management of type 2 inflammation is unclear and warrants further evaluation.