Machine Learning Tool Helps Paediatricians Identify Children at Risk of Persistent Asthma
Key Takeaways:
- A machine learning tool that reads data already held in a child’s electronic health record helped paediatricians more accurately judge which young children are at risk of persistent asthma.
- In a pilot randomised trial using standardised clinical cases, clinicians using the tool reached an average accuracy of 83%, compared with 61% for standard assessment alone.
- The tool is designed to support clinical judgement rather than replace it, and requires no additional tests or questionnaires.
Support for a difficult clinical judgement
A machine learning tool that analyses information already captured in a child’s electronic health record (EHR) has helped paediatricians assess asthma risk more accurately in standardised clinical case scenarios, according to a pilot randomised clinical trial led by a researcher at the Regenstrief Institute. The study was published in the journal Scientific Reports.
The trial evaluated a machine learning-enabled clinical decision support tool known as the Passive Digital Marker. The tool draws on routinely collected EHR data to classify young children as having either a high or a low risk of going on to develop persistent asthma.
Why early asthma risk is hard to predict
Asthma is one of the most common long-term conditions of childhood, yet predicting which young children who have wheezing or other respiratory symptoms will later develop persistent asthma remains difficult. Some children outgrow their early symptoms, while others need ongoing treatment. That uncertainty makes early risk assessment an important, but genuinely challenging, part of paediatric care.
“This tool doesn’t replace a pediatrician’s clinical judgment,” said Arthur H. Owora, PhD, Regenstrief Institute research scientist and lead author of the study. “It helps bring together years of clinical information that’s already in the electronic health record, giving clinicians another source of information when making decisions about a child’s asthma risk.”
How the Passive Digital Marker works
Unlike many prediction tools, the Passive Digital Marker requires no extra testing and asks families to complete no additional questionnaires. Instead, it analyses information that has already been documented in the child’s EHR, including respiratory symptoms, allergies, medication history, respiratory infections and family history. It then presents clinicians with a straightforward high-risk or low-risk assessment.
This approach is intended to save clinicians’ time and reduce the burden on families, since it relies on data that has been gathered over the course of a child’s routine care rather than requiring anything new at the point of decision.
What the trial found
Paediatricians using the tool correctly predicted future asthma more often than those relying on standard assessment alone, achieving an average accuracy of 83% compared with 61%. The improvement was largely driven by better identification of children who went on to develop persistent asthma – the group that is most important to recognise early and hardest to spot.
The researchers stress that the tool is meant to support clinical decision-making, not to supplant it. Its value lies in helping clinicians quickly synthesise years of patient information into a single, easy-to-interpret risk assessment that sits alongside their own expertise. That distinction – between having an AI tool to hand and knowing how to weigh what it tells you – is becoming central to how clinicians are expected to work with these systems.
Limitations and next steps
Because the study used standardised patient cases rather than real-world clinical encounters, further research is needed to establish whether the tool improves outcomes for children in everyday paediatric practice. The pilot demonstrates promise in a controlled setting, but real-world validation is the necessary next stage before wider adoption.
CCH insight
Tools like the Passive Digital Marker are only ever as good as a clinician’s ability to judge when to lean on them and when to look again. That skill – evaluating an AI tool, recognising where it can mislead, and putting sensible governance around its use – is exactly what our short course AI Essentials for GPs: Tools, Ethics and Everyday Applications is designed to build. It’s a 3.5-hour, fully online CPD course led by Prof. Mike Bewick and Dr Dipesh Naik. [Explore the course →]
Funding and authorship
The study was supported in part by the National Institutes of Health under grant K01HL166436. In addition to Owora, it was co-authored by Bowen Jiang, M.S., and Yash Shah, M.S., of the Division of Pediatric Pulmonology, Allergy/Immunology and Sleep Medicine, Department of Pediatrics, Riley Hospital for Children, Indiana University School of Medicine.
Source: Regenstrief Institute
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GLP-1 Weight-Loss Medications Linked to Fewer Severe Asthma Attacks in Adolescents with Excess Weight
Key Takeaways:
- Adolescents with excess weight and asthma who were prescribed GLP-1 medications experienced around half as many asthma-related emergency room visits over one year compared with peers not taking these drugs.
- Use of GLP-1 therapies was also associated with reduced reliance on steroids and rescue inhalers, suggesting improved asthma control.
- Researchers suggest these medicines may offer a dual benefit, supporting weight management while lowering the risk of asthma exacerbations in this population.
Study suggests dual benefit for weight and asthma control
Severe asthma attacks among adolescents with excess weight may be significantly reduced with the use of newer weight-loss medications such as Ozempic and Zepbound, according to a new observational study.
The research found that emergency room visits for asthma were cut by more than half among teenagers who were prescribed a glucagon-like peptide-1 (GLP-1) receptor agonist. The findings were reported on 29 December in JAMA Network Open.
“Our findings suggest a potential dual benefit for this population, where a single class of medication could address both weight management and lower risk for asthma exacerbation, thereby potentially reducing the burden of two common and interconnected chronic conditions,” the researchers concluded.
The study was led by Dr Lin‑Shien Fu, chief of paediatric nephrology and immunology at Taichung Veterans General Hospital.
How the study was conducted
Researchers followed 1,070 adolescents aged 12 to 18 years who were living with excess weight and had a clinical diagnosis of asthma. Approximately half of the group had been prescribed a GLP-1 medication, while the remainder had not received a weight-loss drug.
GLP-1 receptor agonists mimic the naturally occurring GLP-1 hormone, which plays a role in regulating insulin and blood glucose levels. These medicines also reduce appetite and slow gastric emptying, contributing to weight loss.
Over a 12-month follow-up period, the researchers recorded:
- Eight asthma-related emergency department visits among adolescents taking a GLP-1 medication
- Nineteen asthma-related emergency visits among those not prescribed a weight-loss drug
Reduced need for asthma medications
In addition to fewer emergency visits, adolescents taking GLP-1 medications were less likely to require other treatments for asthma control.
The study found that:
- 21% of adolescents taking a GLP-1 medication required steroid treatment for asthma, compared with 31% of those not taking the drugs
- 32% of adolescents in the GLP-1 group needed a rescue inhaler, compared with 45% in the non-GLP-1 group
These differences suggest an overall reduction in asthma severity and symptom burden among those prescribed GLP-1 therapies.
Weight loss and inflammation may explain the findings
Experts not involved in the research say the observed improvements are likely linked to the degree of weight loss achieved with these newer medications.
Dr Michelle Katzow, medical director of the POWER Kids Weight Management Program and associate professor of paediatrics at Cohen Children’s Medical Center in New York City, commented on the findings in a news release.
“I think it is not surprising and not so new, except for the degree of weight loss that the drug induces is so much bigger in magnitude than we have seen before,” she said.
Dr Katzow explained that excess weight contributes to systemic inflammation, which can worsen asthma symptoms and increase the likelihood of exacerbations.
“The sort of inflammation associated with obesity predisposes somebody to having worse asthma or worse symptoms of asthma,” she said.
“If you can help people lose enough weight by whatever means, then you can improve their asthma severity.”
Implications for adolescents struggling with appetite control
Dr Katzow added that GLP-1 medications may be particularly helpful for adolescents who struggle to adopt healthy behaviours because of persistent hunger.
She noted that this is a common challenge among young people with excess weight.
“And that is true for a lot of kids,” she said. “They are just really hungry and they are thinking about food a lot. Trying to make healthier choices or eat less is really hard to do if you are hungry all the time.”
A cautious but promising signal
While the study does not establish a direct causal relationship, it adds to growing evidence that weight-loss interventions can have meaningful benefits beyond body weight alone. The findings suggest that, for some adolescents living with excess weight and asthma, GLP-1 receptor agonists may help reduce the frequency and severity of asthma exacerbations alongside supporting weight management.
Further research will be needed to confirm these findings and to better understand the long-term safety and clinical role of GLP-1 therapies in paediatric populations.
CCH insight:
The long list of benefits of GLP-1 therapy continues to grow. If obesity increases the risk of asthma, it is not surprising that GLP-1 therapy results in a reduction in hospital visits due to asthma. Further studies are needed to back up these results, and also to see if the same benefits are seen in adults, as well as adolescents.
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