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Rationale Clinical decision support (CDS) tools leveraging electronic health records (EHRs) have been an approach for addressing challenges in asthma care but remain under-studied through clinical trials. Objectives To assess the effectiveness and efficiency of Asthma-Guidance and Prediction System (A-GPS), an Artificial Intelligence (AI)-assisted CDS tool, in optimizing asthma management through a randomized clinical trial (RCT). Methods This was a single-center pragmatic RCT with a stratified randomization design conducted for one year in the primary care pediatric practice of the Mayo Clinic, MN. Children (<18 years) diagnosed with asthma receiving care at the study site were enrolled along with their 42 primary care providers. Study subjects were stratified into three strata (based on asthma severity, asthma care status, and asthma diagnosis) and were blinded to the assigned groups. Measurements Intervention was a quarterly A-GPS report to clinicians including relevant clinical information for asthma management from EHRs and machine learning-based prediction for risk of asthma exacerbation (AE). Primary endpoint was the occurrence of AE within 1 year and secondary outcomes included time required for clinicians to review EHRs for asthma management. Main results Out of 555 participants invited to the study, 184 consented for the study and were randomized (90 in intervention and 94 in control group). Median age of 184 participants was 8.5 years. While the proportion of children with AE in both groups decreased from the baseline (P = 0.042), there was no difference in AE frequency between the two groups (12% for the intervention group vs. 15% for the control group, Odds Ratio: 0.82; 95%CI 0.374–1.96; P = 0.626) during the study period. For the secondary end points, A-GPS intervention, however, significantly reduced time for reviewing EHRs for asthma management of each participant (median: 3.5 min, IQR: 2–5), compared to usual care without A-GPS (median: 11.3 min, IQR: 6.3–15); p<0.001). Mean health care costs with 95%CI of children during the trial (compared to before the trial) in the intervention group were lower than those in the control group (-$1,036 [-$2177, $44] for the intervention group vs. +$80 [-$841, $1000] for the control group), though there was no significant difference (p = 0.12). Among those who experienced the first AE during the study period (n = 25), those in the intervention group had timelier follow up by the clinical care team compared to those in the control group but no significant difference was found (HR = 1.93; 95% CI: 0.82–1.45, P = 0.10). There was no difference in the proportion of duration when patients had well-controlled asthma during the study period between the intervention and the control groups. Conclusions While A-GPS-based intervention showed similar reduction in AE events to usual care, it might reduce clinicians’ burden for EHRs review resulting in efficient asthma management. A larger RCT is needed for further studying the findings. Trial registration ClinicalTrials.gov Identifier: NCT02865967.

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BACKGROUND Urinary leukotriene E4 (LTE4) is a well-validated marker of the cysteinyl leukotriene pathway, and LTE4 elevation has been described in conditions such as asthma, aspirin sensitivity, and chronic rhinosinusitis (CRS). There have been a number of reports investigating the role of spot urine LTE4 to predict aspirin sensitivity; however, variability in urinary LTE4 may affect the accuracy of this approach. OBJECTIVE Here, we explored the utility of 24-hour urinary LTE4 in 5 clinical diagnoses of allergic rhinitis, asthma, chronic rhinosinusitis with nasal polyps (CRSwNP), CRS without nasal polyps, and aspirin sensitivity. METHODS This was a retrospective review of patients who had 24-hour quantification of urinary LTE4 by a clinically validated liquid chromatography tandem mass spectrometry method and their assigned diagnoses after assessment and clinical care. RESULTS Twenty-four-hour urinary LTE4 elevations were seen in those with asthma and those with CRSwNP but influenced by underlying aspirin sensitivity. Elevation in LTE4 was significant in those with CRSwNP after adjusting for aspirin sensitivity. Allergic rhinitis was not associated with elevated LTE4 excretion. Receiver operator characteristic analysis of 24-hour urinary LTE4 showed that a cutoff value of 166 pg/mg Cr suggested the presence of history of aspirin sensitivity with 89% specificity, whereas a cutoff value of 241 pg/mg Cr discriminated “challenge-confirmed” aspirin-sensitive subjects with 92% specificity. CONCLUSIONS Elevated 24-hour excretion of urinary LTE4 is a reliable and simple test to identify aspirin sensitivity in patients with respiratory diagnoses.

Asthmatics had significantly lower serotype-specific pneumococcal antibody levels than nonasthmatics. House dust mite-induced T-helper 2 (Th2) cytokine immune profile may be related to the association. This may account for an increased risk of IPD in asthmatics and deserves further investigation.