Diagnostic Approximation to Delabeling Beta-Lactam Allergic Patients

Abstract

Beta-lactam antibiotics constitute first-choice drugs for bacterial infections, although the high rate of hypersensitivity reactions constitutes a worldwide health problem. The public health implications of beta-lactam (BL) allergy are enormous as the self-reported penicillin allergy has been associated with antimicrobial resistance, increased cost to health systems, intensive care admission, and death. Therefore, an accurate and rapid diagnosis is crucial. The diagnostic work-up is mainly based on the performance of an accurate clinical history, skin tests, drug provocation tests and, in some cases, in vitro tests. In recent years, there has been a growing interest on the role of computerized clinical decision support systems to stratify the risk for performing classical diagnostic work-up and in the design of mathematical diagnostic algorithms based on clinical history predictors that would permit the avoidance of high-risk procedures such as skin and drug provocation tests. A precise diagnosis of BL allergy will allow defining phenotypes and endotypes. Nowadays, clinical guidelines that use data from the clinical history are not able to delabel patients, although they can be useful in an urgent situation. True delabeling is still based on the performance of in vivo tests, although differences on the pattern of BL consumption cause differences in the diagnostic approach among different countries.