Research Recap: May 23 - June 3
A biweekly overview of recent studies published by Institute investigators and their collaborators spans a wide variety of topics, including:
Using machine learning for the prediction of disease progression in COPD; Reducing the financial burden of asthma care using telemedicine; Adherence to healthy infant feeding practices to reduce risk of childhood obesity; and Racial and ethnic inequities in pediatric emergency medicine.
For all faculty publications, see our Publications page. For up-to-date media coverage and research findings, visit In the Media, and follow us on Twitter. To search for a subject matter expert, visit our Investigator Directory.
Researchers test machine learning model to identify smokers at increased risk for rapid COPD progression
The heterogeneous nature of COPD complicates the identification of the predictors of disease progression. A group of investigators including Sharon Lutz aimed to improve the prediction of disease progression in COPD by using machine learning and incorporating a rich dataset of phenotypic features using data from the Genetic Epidemiology of COPD (COPDGene) study. Results, published in Chronic Obstructive Pulmonary Diseases, found that predicting the change in forced expiratory volume in 1 second (FEV1) over time is more challenging than simply predicting the future absolute FEV1 level. Researchers report that the supervised random forest (RF) model performed slightly better than the linear regression (LR) model in their analysis. Investigators conclude that RF along with deep phenotyping predicts FEV1 progression with reasonable accuracy, though there is significant room for improvement in future models. This prediction model facilitates the identification of smokers at increased risk for rapid disease progression, which may be useful in the selection of patient populations for targeted clinical trials.
Institute Investigator(s): Sharon Lutz
Weighing the pros and cons of leveraging telemedicine to reduce the financial burden of asthma care
One of the most compelling arguments for telemedicine is its potential to increase healthcare access by making care more affordable for patients and families, including those affected by asthma. This goal is critically important in the U.S. where the high cost of asthma care is associated with nonadherence to preventive care regimens and suboptimal health outcomes. In a clinical commentary review by a group of investigators including Ann Wu and senior author Alison Galbraith published in the Journal of Allergy and Clinical Immunology in Practice, authors draw from the literature and their own research to identify opportunities for and challenges to leveraging telemedicine to reduce the financial burden of asthma care. While telemedicine can meaningfully reduce costs while still offering high-quality care, it can reduce access to support services and material resources, such as medication samples. These findings underscore the need for careful care coordination and communication in telemedicine. Authors conclude by discussing a structured communication approach designed to support cost conversations, increase care coordination, and help families reduce asthma care cost burden.
Institute Investigator(s): Alison Galbraith, Ann Chen Wu
Targeting multiple infant feeding practices as a more effective approach to reduce the risk of childhood obesity
Childhood obesity is an epidemic that disproportionately affects racial and ethnic minoritized populations from an early age and prevention efforts in infancy prior to the development of obesity is critical to mitigating disparities. While studies have largely examined individual infant feeding practices, adherence to cumulative infant feeding practices to prevent overnutrition and obesity remains understudied. A group of researchers led by Allison Wu and including Marie-France Hivert and Izzuddin Aris studied healthy infant feeding practices among 308 mother-infant pairs including exclusive breastmilk, satiety cues, complementary food introduction, sugary beverage intake, and bottle use in bed. Results, published in the Journal of Pediatric Gastroenterology and Nutrition, found that adherence to higher cumulative healthy infant feeding practices from birth to 12 months was associated with a lower BMI z-score at 2 years. Results suggest that adherence to healthy infant feeding practices may reduce the risk of excessive adiposity in early childhood and that targeting multiple infant feeding practices may be a more effective way to prevent childhood adiposity.
Institute Investigator(s): Izzuddin Aris, Marie-France Hivert, Allison Wu
Cross-sectional analysis of diagnostic imaging rates in the United State reveals persistent racial and ethnic inequities
Lower rates of diagnostic imaging have been observed among Black children compared with White children in pediatric emergency departments. Although the racial composition of the pediatric population served by each hospital differs, it is unclear whether this is associated with overall imaging rates at the hospital level, and in particular how it may be associated with the difference in imaging rates between Black and White children at a given hospital. A group of investigators including Alon Peltz conducted a cross-sectional analysis of patient visits at 38 children’s hospitals using data from the Pediatric Health Information System to examine the association between the diversity of the pediatric population seen at each pediatric ED and variation in diagnostic imaging. Results, published in JAMA Network Open, found that hospitals with a higher percentage of pediatric patients from minoritized groups had larger differences in imaging between non-Hispanic Black and non-Hispanic White patients, with non-Hispanic White patients consistently more likely to receive diagnostic imaging. Authors emphasize that these findings underscore the urgent need for interventions at the hospital level to improve equity in imaging in pediatric emergency medicine.
Institute Investigator(s): Alon Peltz
INVESTIGATORSIzzuddin Aris, Alison Galbraith, Marie-France Hivert, Sharon Lutz, Alon Peltz, Allison Wu, Ann Chen Wu