Background: Artificial Intelligence (AI) technologies could potentially change many aspects of clinical practice. While Allergen Immunotherapy (AIT) can change the course of allergic diseases providing relief of symptoms that extend for many years after treatment completion, it can also bring uncertainty to patients, who turn to readily available resources such as ChatGPT-4 to address these doubts. The aim of this study was to use validated tools to evaluate the information provided by ChatGPT-4 regarding AIT in terms of quality, reliability and readability. Methods: In accordance with AIT clinical guidelines, 24 questions were selected and introduced in ChatGPT-4. Answers were evaluated by a panel of allergists, using validated tools DISCERN, JAMA Benchmark and Flesch Reading Ease Score and Grade Level. Results: Questions were sorted into 6 categories. ChatGPT provided bad quality information according to DISCERN medians scores in the “Definition”, “Standardization and Efficacy”, and “Safety and Adverse Reactions” categories. It provided insufficient information according to JAMA Benchmark across all categories. Finally, ChatGPT-4 answers required a “college graduate” level of education to be understood as they were very difficult to read. Conclusions: ChatGPT-4 exhibits potential as a valuable complement to healthcare; however, it requires further refinement. The information it provides should be approached with caution regarding its quality, as significant details may be omitted or may not be fully comprehensible. Artificial intelligence models continue to evolve, and medical professionals should participate in this process, given that AI impacts various aspects of life, including health, to ensure the availability of optimal information.

Introduction Previous evidence has shown that FeNO and EO are cost-effective relative to standard of care in guiding the management of children with persistent asthma. There is some doubt as if there are differences between these two biomarkers in terms of costs and benefits. Clarifying this doubt would allow to prioritize in the design of clinical practice guidelines. The study aimed to compare in terms of costs and benefits these biomarkers in patients with asthma between 4 and 18 years of age.3 Methods A Markov model was used to estimate the cost-utility of asthma management using FeNO and EO in patients between 4 and 18 years of age. Transition probabilities, cost and utilities were estimated from previously published local studies, while relative risks were obtained from the systematic review of published randomized clinical trials. The analysis was carried out from a societal perspective. Results FeNO was associated with lower cost (US$ 1333 CI 95% US$ 1331-1335 vs US$ 1452 CI 95% US$ 1449-1454) and highest QALY (0.93 CI 95% 0.93-0.94 vs 0.92 CI 95% 0.91-0.92) than EO. In the sensitivity analyses, our base‐case results were robust to variations of all assumptions and parameters. Conclusion Our study demonstrates that FeNO-guided treatment is better than EO because it offers a greater number of years of life with a lower cost per patient. This evidence should encourage the adoption of any of these techniques to objectively guide the management of children with asthma in routine clinical practice in low resource settings.