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Objectives: Pediatric asthma is a leading cause of emergency department (ED) utilization and hospitalization. Earlier identification of need for hospital-level care could triage patients more efficiently to high- or low-resource ED tracks. Existing tools to predict disposition for pediatric asthma use only clinical data, perform best several hours into the ED stay, and are static or score-based. Machine learning offers a population-specific, dynamic option that allows real-time integration of available nonclinical data at triage. Our objective was to compare the performance of four common machine learning approaches, incorporating clinical data available at the time of triage with information about weather, neighborhood characteristics, and community viral load for early prediction of the need for hospital-level care in pediatric asthma., Methods: Retrospective analysis of patients ages 2 to 18 years seen at two urban pediatric EDs with asthma exacerbation over 4 years. Asthma exacerbation was defined as receiving both albuterol and systemic corticosteroids. We included patient features, measures of illness severity available in triage, weather features, and Centers for Disease Control and Prevention influenza patterns. We tested four models: decision trees, LASSO logistic regression, random forests, and gradient boosting machines. For each model, 80% of the data set was used for training and 20% was used to validate the models. The area under the receiver operating characteristic (AUC) curve was calculated for each model., Results: There were 29,392 patients included in the analyses: mean (±SD) age of 7.0 (±4.2) years, 42% female, 77% non-Hispanic black, and 76% public insurance. The AUCs for each model were: decision tree 0.72 (95% confidence interval [CI] = 0.66-0.77), logistic regression 0.83 (95% CI = 0.82-0.83), random forests 0.82 (95% CI = 0.81-0.83), and gradient boosting machines 0.84 (95% CI = 0.83-0.85). In the lowest decile of risk, only 3% of patients required hospitalization; in the highest decile this rate was 100%. After patient vital signs and acuity, age and weight, followed by socioeconomic status (SES) and weather-related features, were the most important for predicting hospitalization., Conclusions: Three of the four machine learning models performed well with decision trees preforming the worst. The gradient boosting machines model demonstrated a slight advantage over other approaches at predicting need for hospital-level care at the time of triage in pediatric patients presenting with asthma exacerbation. The addition of weight, SES, and weather data improved the performance of this model., (© 2018 by the Society for Academic Emergency Medicine.)

Objectives: A noninvasive method to assess ventilation may aid in management of children with acute asthma. The purpose of this study was to evaluate the association between end-tidal carbon dioxide (EtCO2) values and disease severity among children with acute asthma., Methods: This was a prospective, blinded, observational study of children 3-17 years old treated for acute asthma in a pediatric emergency department (ED). EtCO2 measurements were taken before the initiation of therapy and after each nebulization treatment (maximum of three). Peak expiratory flow rate (PEFR), Pediatric Asthma Severity Score (PASS), oxygen saturation, and disposition were recorded. Treating physicians, unaware of the EtCO2 results, made all treatment decisions, including disposition., Results: One hundred children were enrolled. The mean initial EtCO2 value was 35 mm Hg (95% confidence interval = 34.3 to 36.1 mm Hg). The mean disposition EtCO2 value was 33.3 mm Hg (95% confidence interval = 32.6 to 34.4 mm Hg). PEFR measures were completed on 43 patients and PASS recorded on 100 patients. There was an overall trend toward lower EtCO2 values during treatment (p < 0.01). Sixteen patients were admitted. Initial EtCO2 values were lower among children admitted to the hospital (35.6 mm Hg vs. 32.9 mm Hg; Mann-Whitney U test; p < 0.02). EtCO2 values at disposition did not differ between groups based on PEFR, PASS, or hospital admission., Conclusions: Noninvasive bedside measurement of EtCO2 values among children with acute asthma is feasible. EtCO2 values did not distinguish children with mild disease from those with more severe disease. Further data are needed to clarify the association between EtCO2 values and other indicators of disease severity, particularly in children with more severe disease.

Objectives: To evaluate the reliability, validity, and responsiveness of a new clinical asthma score, the Pediatric Asthma Severity Score (PASS), in children aged 1 through 18 years in an acute clinical setting., Methods: This was a prospective cohort study of children treated for acute asthma at two urban pediatric emergency departments (EDs). A total of 852 patients were enrolled at one site and 369 at the second site. Clinical findings were assessed at the start of the ED visit, after one hour of treatment, and at the time of disposition. Peak expiratory flow rate (PEFR) (for patients aged 6 years and older) and pulse oximetry were also measured., Results: Composite scores including three, four, or five clinical findings were evaluated, and the three-item score (wheezing, prolonged expiration, and work of breathing) was selected as the PASS. Interobserver reliability for the PASS was good to excellent (kappa = 0.72 to 0.83). There was a significant correlation between PASS and PEFR (r = 0.27 to 0.37) and pulse oximetry (r = 0.29 to 0.41) at various time points. The PASS was able to discriminate between those patients who did and did not require hospitalization, with area under the receiver operating characteristic curve of 0.82. Finally, the PASS was shown to be responsive, with a 48% relative increase in score from start to end of treatment and an overall effect size of 0.62, indicating a moderate to large effect., Conclusions: This clinical score, the PASS, based on three clinical findings, is a reliable and valid measure of asthma severity in children and shows both discriminative and responsive properties. The PASS may be a useful tool to assess acute asthma severity for clinical and research purposes.

Objectives: The original objective was to determine whether the use of bilevel positive airway pressure (BiPAP) ventilation would reduce the need for endotracheal intubation, the length of hospital stay, and hospital charges in patients with status asthmaticus. The development of physician treatment bias made patient enrollment difficult. The article subsequently describes the use of Bayesian statistics to explain study results when this bias occurs., Methods: This study was a prospective, randomized controlled clinical trial conducted over a 34.5-month period at an urban university hospital with an emergency department census of 94,000 annual visits. Patients remaining in status asthmaticus after initial standard treatment with inhaled beta-agonists and steroids were randomized to receive BiPAP ventilation plus standard treatment versus standard treatment alone (non-BiPAP), with intubation for either group as needed. Patients with concurrent cardiac or other pulmonary diseases were excluded. The primary outcome measures were endotracheal intubation rate and length of hospital stay. Secondary outcome measures included vital signs (respiratory rate, pulse rate, blood pressure), changes in expiratory peak flow, changes in pulse oximetry values, and hospital charges. Data were analyzed using Fisher's exact test, Mann-Whitney tests, and Bayesian statistics. For patients enrolled in the study more than once, data analysis was performed on the first enrollment only., Results: Nineteen patients were enrolled in the BiPAP group and 16 patients in the non-BiPAP group. Patients were frequently enrolled more than once and the data from the subsequent enrollments were excluded from the analysis. A marked decrease in enrollment, due to physician treatment bias, led to a premature termination of the study. Demographics showed that the groups were similar in age, sex, initial peak flow rate, and arterial blood gas measurements. There was a 7.3% increase (95% CI = -22 to +45) in the intubation rate in the non-BiPAP group (n = 2) compared with that for the BiPAP group (n = 1). No significant difference was seen in length of hospital stay or hospital charges, although there was a favorable trend toward the BiPAP group. Complications encountered in the BiPAP group included one patient with discomfort associated with the nasal BiPAP mask. Bayesian analysis demonstrated that in order for the collected data to be convincing at the 95% confidence level, the prior conviction among treating physicians that BiPAP was a successful treatment modality would have had to be 98.9%., Conclusions: In this study, BiPAP appeared to have no deleterious effects in patients with status asthmaticus, with a trend toward decreased endotracheal intubation rate, decreased length of hospital stay, and decreased hospital charges. Although further study with more patients is needed to determine the clinical and statistical significance of this intervention, ethical concerns regarding withholding BiPAP treatment from the patients in the control group forced a premature termination of the study in the authors' institution.