Evaluation of Risk Scores to Predict Pediatric Severe Asthma Exacerbations

Predicting pediatric severe asthma exacerbations: an administrative claims-based predictive model

OBJECTIVE

Previous machine learning approaches fail to consider race and ethnicity and social determinants of health (SDOH) to predict childhood asthma exacerbations. A predictive model for asthma exacerbations in children is developed to explore the importance of race and ethnicity, rural-urban commuting area (RUCA) codes, the Child Opportunity Index (COI), and other ICD-10 SDOH in predicting asthma outcomes.

METHODS

Insurance and coverage claims data from the Arkansas All-Payer Claims Database were used to capture risk factors. We identified a cohort of 22,631 children with asthma aged 5-18 years with 2 years of continuous Medicaid enrollment and at least one asthma diagnosis in 2018. The goal was to predict asthma-related hospitalizations and asthma-related emergency department (ED) visits in 2019. The analytic sample was 59% age 5-11 years, 39% White, 33% Black, and 6% Hispanic. Conditional random forest models were used to train the model.

RESULTS

The model yielded an area under the curve (AUC) of 72%, sensitivity of 55% and specificity of 78% in the OOB samples and AUC of 73%, sensitivity of 58% and specificity of 77% in the training samples. Consistent with previous literature, asthma-related hospitalization or ED visits in the previous year (2018) were the two most important variables in predicting hospital or ED use in the following year (2019), followed by the total number of reliever and controller medications.

CONCLUSIONS

Predictive models for asthma-related exacerbation achieved moderate accuracy, but race and ethnicity, ICD-10 SDOH, RUCA codes, and COI measures were not important in improving model accuracy.

Prediction of Asthma Exacerbations in Children

Asthma exacerbations are common in asthmatic children, even among those with good disease control. Asthma attacks result in the children and their parents missing school and work days; limit the patient's social and physical activities; and lead to emergency department visits, hospital admissions, or even fatal events. Thus, the prompt identification of asthmatic children at risk for exacerbation is crucial, as it may allow for proactive measures that could prevent these episodes. Children prone to asthma exacerbation are a heterogeneous group; various demographic factors such as younger age, ethnic group, low family income, clinical parameters (history of an exacerbation in the past 12 months, poor asthma control, poor adherence to treatment, comorbidities), Th2 inflammation, and environmental exposures (pollutants, stress, viral and bacterial pathogens) determine the risk of a future exacerbation and should be carefully considered. This paper aims to review the existing evidence regarding the predictors of asthma exacerbations in children and offer practical monitoring guidance for promptly recognizing patients at risk.

Effectiveness of a Vendor Predictive Model for the Risk of Pediatric Asthma Exacerbation: A Difference-in-Differences Analysis

BACKGROUND

Asthma is a common cause of morbidity and mortality in children. Predictive models may help providers tailor asthma therapies to an individual's exacerbation risk. The effectiveness of asthma risk scores on provider behavior and pediatric asthma outcomes remains unknown.

OBJECTIVE

Determine the impact of an electronic health record (EHR) vendor-released model on outcomes for children with asthma.

METHODS

The Epic Systems Risk of Pediatric Asthma Exacerbation model was implemented on February 24, 2021, for volunteer pediatric allergy and pulmonology providers as a noninterruptive risk score visible in the patient schedule view. Asthma hospitalizations, emergency department (ED) visits, or oral steroid courses within 90 days of the index visit were compared from February 24, 2019, to February 23, 2022, using a difference-in-differences design with a control group of visits to providers in the same departments. Volunteer providers were interviewed to identify barriers and facilitators to model use.

RESULTS

In the intervention group, asthma hospitalizations within 90 days decreased from 1.4% (54/3,842) to 0.7% (14/2,165) after implementation with no significant change in the control group (0.9% [171/19,865] preimplementation to 1.0% [105/10,743] post). ED visits in the intervention group decreased from 5.8% (222/3,842) to 5.5% (118/2,164) but increased from 5.5% (1,099/19,865) to 6.8% (727/10,743) in the control group. The adjusted difference-in-differences estimators for hospitalization, ED visit, and oral steroid outcomes were -0.9% (95% confidence interval [CI]: -1.6 to -0.3), -2.4% (-3.9 to -0.8), and -1.9% (-4.3 to 0.5). In qualitative analysis, providers understood the purpose of the model and felt it was useful to flag high exacerbation risk. Trust in the model was calibrated against providers' own clinical judgement.

CONCLUSION

This EHR vendor model implementation was associated with a significant decrease in asthma hospitalization and ED visits within 90 days of pediatric allergy and pulmonology clinic visits, but not oral steroid courses.

The association between PM2.5 concentration and the severity of acute asthmatic exacerbation in hospitalized children: A retrospective study in Chongqing, China

BACKGROUND

Ambient PM2.5 is associated with asthma exacerbation. The association between the concentration of PM2.5 and the severity of asthma exacerbation has yet to be thoroughly clarified. The study aims to explore the association between the piror 30 days average concentration of PM2.5 and the severity of acute asthma exacerbation in hospitalized children.

METHODS

A total of 269 children with acute exacerbation of asthma were enrolled and divided into three groups according to the PM2.5 exposure concentrations: group 1 (PM2.5: <37.5 μg/m3 ), group 2 (PM2.5: 37.5-75 μg/m3 ), group 3 (PM2.5: ≥75 μg/m3 ), respectively. The ordered logistic regression modeling was conducted to explore the influence of daily PM2.5 concentration on the clinical severity of children's asthma exacerbation. Multiple linear regression was conducted to explore the association between the concentration of PM2.5 and the length of stay in the hospital (LOS). We also conducted a receiver operating characteristic (ROC) curve analysis to explore the cutoff value of PM2.5 to predict the children's asthma exacerbation.

RESULTS

There was no statistical difference among the three groups of children in gender, age, body mass index, ethnicity, the first diagnosis of asthma, allergic history, passive smoke exposure, or family history of asthma. There was a statistically significant difference in many hospitalization characteristics (p < 0.05) among the three groups of children. Significant differences were found in terms of accessory muscles of respiration (p = 0.005), respiratory failure (p = 0.012), low respiratory tract infectious (p = 0.020), and the severity of asthma exacerbation (p < 0.001) among the three groups. PM2.5 concentration was primarily positively correlated to neutrophile inflammation. The ordered multivariate logistic regression model showed that higher PM2.5 concentrations were significantly associated with greater odds of more severe asthma exacerbation in one and two-pollutant models. The adjusted odds ratio of severe asthma exacerbation was 1.029 (1.009, 1.049) in the one-pollutant model. The most significant odds ratio of severe asthma exacerbation was 1.050 (1.027, 1.073) when controlling NO2 in the two-pollutant models. Multiple linear regression showed that PM2.5 concentration was significantly associated with longer LOS in both one-pollutant and two-pollutant models. By performing ROC analysis, the average daily concentration of 44.5 µg/m3 of PM2.5 (AUC = 0.622, p = 0.002) provided the best performance to predict severe asthma of children exacerbation with a sensitivity of 59.2% and a specificity of 63.8%.

CONCLUSION

The increased prior 30 days average concentration of PM2.5 was associated with greater asthma exacerbation severity and longer length of stay in the hospital of children with asthma exacerbation.

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.

Long-term effects of vitamin D on exacerbation rate, health care utilization and lung function in children with asthma

Background

Asthma exacerbations lead to unplanned health care utilization and reduced lung function in children. Sufficient vitamin D level has been found to have a short-term protective effect against asthma exacerbation in children. However, it is unclear whether this effect remains in the long term. We evaluated the long-term effects of vitamin D levels on the occurrence of asthma exacerbations, emergency department visits or hospitalizations, and lung function among children with asthma, and further investigated the temporal trends of the effects.

Methods

In this retrospective cohort study, children with asthma who were admitted to the Children's Hospital of Chongqing Medical University from 2017 to 2021 were enrolled. Negative binomial, Poisson, or logistic regression model was used for the multivariable analysis, adjusting for age, sex, body mass index z-score, and severity of asthma exacerbation.

Results

Of the 370 children with asthma, 87.8% had vitamin D level less than or equal to 30 ng/mL. After adjustment for confounding factors, higher baseline vitamin D levels in asthma children were significantly associated with reduced occurrence of asthma exacerbations during the first [odds ratio 0.842, 95% confidence interval (CI): 0.805-0.881; P<0.001], second (odds ratio 0.848, 95% CI: 0.793-0.907; P<0.001) and third years (odds ratio 0.865, 95% CI: 0.811-0.922; P<0.001) of follow-up. Higher vitamin D levels in asthmatic children were also strongly associated with a reduced number of emergency department visits or hospitalizations during the first (odds ratio 0.880, 95% CI: 0.842-0.920; P<0.001), second (odds ratio 0.885, 95% CI: 0.832-0.941; P<0.001), and third years (odds ratio 0.922, 95% CI: 0.851-0.998; P=0.044) of follow-up. In addition, the vitamin D levels in asthmatic children were found to be negatively associated with the odds of large airway dysfunction (odds ratio 0.865, 95% CI: 0.771-0.970; P=0.013) and small airway dysfunction (odds ratio 0.922, 95% CI: 0.855-0.996; P=0.038) during the first year of follow-up.

Conclusions

Sufficient vitamin D level is associated with lower risk of asthma exacerbations and health care utilization over a 3-year period, and improved lung function over 1 year. The protective effects of vitamin D on asthmatic children decreased over time.