Resumo

CARDOSO, Bárbara Kong et al. Analysis of a predictive model for the diagnosis of allergic drug reactions based on the medical history. Rev Port Imunoalergologia [online]. 2020, vol.28, n.1, pp.11-17. ISSN 0871-9721.  https://doi.org/10.32932/rpia.2020.03.028.

Background: Allergic drug reactions represent an important public health problem associated with a significant mortality and morbidity. The allergy workup in this situation is expensive and time consuming. A predictive model using medical history would allow us to assess the risk of a positive result and might simplify the diagnostic process. Aims: To assess the performance of the Hierro Santorino predictive model in patients from our Immunoallergology department investigated for drug allergy. Methods: We included in our study patients referred to our department for drug allergy whose investigation was concluded between January 2017 and June 2018. We collected clinical data identified as the predictive factors in the mentioned model, as well as the results from the allergy work up. The Hierro Santorino model was then applied to our population and its performance was evaluated. Results: We analyzed 159 cases corresponding to 143 patients, 54 (37.8%) females, mean age of 42.1 ± 25.4 years. In 108 cases there was only 1 drug involved. In 39% of the cases a beta-lactam was the suspected drug, in 31% a nonsteroidal anti-inflammatory drug (NSAID) and in 29.6% other drug classes were suspected. In 18.2% of the cases the final diagnosis was positive for drug allergy, in 15.7% “NSAID intolerance” was established, 5% of the patients had “angiotensin-converting-enzyme inhibitor intolerance” and in 54.1% drug allergy was excluded. As the model under study was applied the mean probability of drug allergy was 73.3% (26.6% to 91.7%) in the allergic group and 68.7% (8.4% to 96.4%) in the non-allergic group. There was no cut-off value with capacity to discriminate between the outcomes. Conclusions: The model tested in our population revealed a poor performance suggesting that predictive models still need improving to be used as a tool in the allergy workup.

Palavras-chave : Allergic drug reaction; drug hypersensitivity; allergy workup; predictive models; decision-making algorithm.

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