Measurement uncertainty of β-lactam antibiotics results: estimation and clinical impact on therapeutic drug monitoring

Abstract

Background: Despite that measurement uncertainty data should facilitate an appropriate interpretation of measured values, there are actually few reported by clinical laboratories. We aimed to estimate the measurement uncertainty of some β-lactam antibiotics (β-LA), and to evaluate the impact of reporting the measurement uncertainty on clinicians' decisions while guiding antibiotic therapy. Methods: Measurement uncertainty of β-LA (aztreonam [ATM], cefepime [FEP], ceftazidime [CAZ], and piperacillin [PIP]) values, obtained by an UHPLC-MS/MS based-method, was estimated using the top-down approach called the single laboratory validation approach (EUROLAB guidelines). Main uncertainty sources considered were related to calibrators' assigned values, the intermediate precision, and the bias. As part of an institutional program, patients with osteoarticular infections are treated with β-LA in continuous infusion and monitored to assure values at least 4 times over the minimal inhibitory concentration (4×MIC). We retrospectively evaluated the impact of two scenarios of laboratory reports on clinicians' expected decisions while monitoring the treatment: reports containing only the β-LA values, or including the β-LA coverage intervals (β-LA values and their expanded measurement uncertainties). Results The relative expanded uncertainties for ATM, FEP, CAZ and PIP were lower than 26.7%, 26.4%, 28.8%, and 25.5%, respectively. Reporting the measurement uncertainty, we identified that clinicians may modify their decision especially in cases where 4×MIC values were within the β-LA coverage intervals. Conclusions: This study provides a simple method to estimate the measurement uncertainty of β-LA values that can be easily applied in clinical laboratories. Further studies should confirm the potential impact of reporting measurement uncertainty on clinicians' decision-making while guiding antibiotic therapy.