Usefulness of an Artificial Neural Network in the Prediction of ß-Lactam Allergy.

BACKGROUND: An accurate diagnosis of ß-lactam (BL) allergy improves the use of antibiotics, increases patients' safety, and reduces costs to health systems. Nevertheless, it requires skin and drug provocation tests, which are time-consuming and put the patient at risk. Furthermore, allergy testing is not available in circumstances such as the urgent need for antibiotic therapy. OBJECTIVE: To evaluate the usefulness of an artificial neural network (ANN) in the prediction of hypersensitivity to BLs, and compare it with logistic regression (LR) analysis. METHODS: In a single-center study, 656 patients evaluated for BL allergy between 1994 and 2000 were retrospectively analyzed, and the data were used to construct an ANN. The ANN predictive capabilities were compared with LR and then prospectively evaluated in 615 patients who underwent BL evaluation between 2011 and 2017. RESULTS: A total of 1271 patients were evaluated. All patients had a definite diagnosis as allergic or nonallergic to BL. The prospective sample showed a lower percentage of patients with allergy than the retrospective sample (20.7% vs 25.8%; P = .018). In the retrospective and prospective series, the ANN reached a sensitivity of 89.5% and 81.1%, a specificity of 86.1% and 97.9%, a positive predictive value of 82.1% and 91.1%, and a negative predictive value of 92.1% and 95.2%, respectively. The ANN's performance was far superior to that of the LR, whose best performance reached a sensitivity of 31.9% and a specificity of 98.8%. CONCLUSIONS: This ANN demonstrated a superior performance than the LR in predicting BL hypersensitivity without misdiagnosing severe allergic reactions. The ANN could be a helpful tool to classify the reaction risk, particularly in the identification of low-risk patients, in which an open challenge could be done to delabel patients.

Analysis of the Costs Associated With the Elective Evaluation of Patients Labelled as Allergic to Beta-Lactams or Nonsteroidal Antiinflamatory Agents.

Introduction: Being labelled as allergic to different drugs results in patients receiving other treatments, which are more toxic, less effective and more expensive. We aimed to analyze different studies of the costs of drug hypersensitivity assessment. Methods: A bibliographic search on studies regarding this issue was performed, including the available scientific evidence up to June 2020. We searched three databases with terms related to costs and allergy testing in drug hypersensitivity reactions. Results: Our search revealed 1,430 publications, of which 20 met the inclusion criteria. In the manuscript, prospective studies evaluating the costs of the evaluation of patients with suspected allergy to beta-lactams or non-steroidal anti-inflammatory drugs are analyzed. Also, comment is made on the costs associated with incorrect labeling as non-steroidal anti-inflammatory drug or penicillin hypersensitivity. Conclusions: Taking all costs into account, the study of drug hypersensitivity is not expensive, particularly considering the economic and clinical consequences of labeling a patient with hypersensitivity to drugs.