The asthma predictive index as a surrogate diagnostic tool in preschoolers: Analysis of a longitudinal birth cohort

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.