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Published on: August 7, 2017
The asthma predictive index as a surrogate diagnostic tool in preschoolers: Analysis of a longitudinal birth cohort
Jose A Castro-Rodriguez1, Erick Forno2, Oslando Padilla3
1Division of Pediatrics, School of Medicine, Pontificia Universidad Católica de Chile, Santiago, Chile.
Insights
The Asthma Predictive Index (API) shows promise as a diagnostic tool for identifying asthma in preschoolers. This study found API+ was associated with a significantly higher likelihood of asthma diagnosis in young children.
Area of Science:
- Pediatric Pulmonology
- Allergy and Immunology
- Epidemiology
Background:
- Diagnosing asthma in preschool children is challenging, hindering timely intervention.
- Early asthma identification is crucial for preventing long-term lung damage and improving health outcomes.
Purpose of the Study:
- To evaluate the Asthma Predictive Index (API) as a potential surrogate for diagnosing asthma in preschoolers.
- To assess the diagnostic accuracy of the API in a young cohort.
Main Methods:
- A longitudinal birth cohort study followed 339 pregnant women and their offspring for 30 months.
- The API was calculated at 30 months and compared with physician-diagnosed asthma, with adjustments for various covariates.
Main Results:
- Among 307 children, 14.3% were API+. Factors like maternal BMI and respiratory infections were associated with API+.
- API+ demonstrated a significant association with asthma diagnosis (adjusted OR=5.7), with high specificity (92%) and NPV (88%).
Conclusions:
- The Asthma Predictive Index (API) shows potential as a diagnostic tool, not just a prognostic one, for asthma in toddlers and preschoolers.
- This study provides initial evidence supporting the API's utility in clinical diagnosis for early childhood asthma.
Abstract:
Diagnosing asthma in preschool children remains an unsolved challenge, at a time when early identification would allow for better education and treatment to prevent morbidity and lung function deterioration.
Objective:
To evaluate if the asthma predictive index (API) can be used as surrogate for asthma diagnosis in preschoolers.
Methods:
Birth cohort of 339 pregnant women enrolled at delivery and their offspring, who were followed for atopy, wheezing, and other respiratory illnesses through 30 months of age. The API was determined at 30 months of age by the researchers; and examined its association with physician-diagnosed asthma during the first 30 months, made independently by the primary care physician not involved in the study.
Results:
Among 307 offspring with complete follow-up, 44 (14.3%) were API+. Maternal body mass index, maternal education, past oral contraceptive use, birthweight, placenta weight, age of daycare at 12 m, gastroesophageal reflux disease at 12 m, acute otitis media at 18 m, bronchiolitis, croup and pneumonia, cord blood adiponectin were all associated with API+. In the multivariable analysis, API+ was associated with almost sixfold odds of asthma diagnosis (adjusted OR = 5.7, 95% CI [2.6-12.3]), after adjusting for the relevant covariates above including respiratory infections like bronchiolitis and pneumonia. The API sensitivity was 48%, specificity 92%, 61% PPV, 88% NPV, 6.4 LR+, 0.56 LR-, 0.84 diagnosis accuracy. The adjusted odds for asthma was 11.4.
Conclusions:
This longitudinal birth cohort suggests, for first time, that API (a structured definition for asthma), could be used as a diagnostic tool, not only as a prognostic tool, in toddlers and preschoolers.
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