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Scientists develop accurate, non-invasive tool to predict asthma in children

Scientists have built a non-invasive tool to predict the occurrence of asthma in children to detect and prevent it at an early stage.

The prediction of childhood asthma has been an obstacle for healthcare professionals and medical experts. An American study published in the Journal of Allergy and Clinical Immunology tackles this medical concern by introducing an innovative solution for determining the risk of asthma in children.

Titled the Pediatric Asthma Risk Score (PARS), this prediction tool enables medical experts to detect the likelihood of asthma and effectively implement the preventative measures necessary earlier on. The study also compares their innovation to the traditionally used asthma prediction method Asthma Predictive Index (API) in terms of ease of use and accuracy of results.

The study used data from 762 children who had participated in the Cincinnati Childhood Allergy and Air Pollution Study. They were born between 2001 and 2003 and had parents who have previously experienced allergy symptoms. An allergy examination was performed for each child once a year to determine the development of asthma. The examinations took into consideration 15 possible food or airborne allergens. Detection of asthma was defined by the parent reporting symptoms such as a blocked throat and chest or breathing difficulty. The child should also showcase a positive result for the methacholine test or airway reversibility to be diagnosed with asthma.

New method is significantly more accurate than the traditional method

The authors of the study reported that preventative methods are most effective in children with a lower to moderate chance of being diagnosed with asthma. While PARS matched the accuracy of the traditionally used API in detecting high-risk levels of asthma, it was significantly more accurate in identifying low-to-medium risk levels of asthma in individuals. In contrast, API detected only 47% of the children with asthma that PARS was able to detect. The following factors were identified by PARS in the process of predicting asthma in children: parental asthma, wheezing, eczema, race, and sensitization to the aforementioned allergens.

New method is less invasive and easier to use

The lead author further explained that API is effective in determining children who are most likely to not be diagnosed with asthma, however, PARS provides increased accuracy in terms of children who are likely to face the respiratory condition. The low invasiveness of PARS also offers increased ease of use and fewer risks for medical professionals and patients of asthma. This enables PARS to be easily implemented in hospitals, clinics, and research studies. A more accurate prediction method emphasizes the transition from curative treatment to preventative care encouraging improved global health for future generations.


Read about the 10 things you may not know about asthma here. 

Written by Shrishti Ahuja, HBSc

References:

  1. Myers, J. M., Schauberger, E., He, H., Martin, L. J., Kroner, J., Hill, G. M., . . . Hershey, G. K. (2018). A Pediatric Asthma Risk Score to better predict asthma development in young children. Journal of Allergy and Clinical Immunology. doi:10.1016/j.jaci.2018.09.037
  2. Scientists create most accurate tool yet developed to predict asthma in young children. Retrieved January 07, 2019, from https://www.eurekalert.org/pub_releases/2018-12/cchm-scm121018.php
Shrishti Ahuja BSc
Shrishti Ahuja BSc
Shrishti is currently working towards her HBSc degree in Medical Science and English Literature from Western University. She enjoys taking on challenging opportunities that allow her to communicate complex scientific concepts to a variety of audiences. Along with the Medical News Bulletin, she is actively involved in the orientation program at her university, is part of a dance team, and enjoys travelling.
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