Front Pharmacol. 2022 Jul 6;13:937045. doi: 10.3389/fphar.2022.937045. eCollection 2022.
ABSTRACT
Background-Adverse drug reactions (ADRs) are a public health issue, due to their great impact on morbidity, mortality, and economic cost. The use of automatized laboratory alerts could simplify greatly its detection. Objectives-We aimed to evaluate the performance of a laboratory alerts system as a method for detecting ADRs, using hyponatremia and rhabdomyolysis as case studies. Methods-This is a retrospective observational study conducted in 2019 during a 6-month period, including patients hospitalized at the Hospital Universitario de La Princesa. Patients were identified using altered laboratory parameters corresponding to the two signals: “rhabdomyolysis” (creatine phosphokinase >5 times the upper limit of normality (ULN): >1000 U/L for men and >900 U/L for women) and “hyponatremia” (<116 mEq/L) were detected. In cases where ADR was suspected, causality assessment was performed using the algorithm of the Spanish Pharmacovigilance System (SEFV). Results-During the study period, 180 patients were studied for the “rhabdomyolysis” signal, 6 of them were found to have an ADR (3.3%). The sensitivity of the test was 60%, specificity 97%, and positive predictive value 41%. 28 patients were studied for the “hyponatremia” signal, and 11 patients were found to have an ADR (39.3%), with a sensitivity of 76.9%, a specificity of 93.3%, and a positive predictive value of 88.2%. We found no relationship between altered laboratory values and risk of ADR in any of the cases studied. Conclusion-A pharmacovigilance program based on automatized laboratory signals could be an effective method to detect ADR. The study of the “hyponatremia” laboratory alert is more efficient than “rhabdomyolysis”. The evaluation of the hyponatremia alert allows the identification of 12 times more ADRs than the rhabdomyolysis alert, which means less time spent per alert evaluated to identify an ADR.
PMID:35873584 | PMC:PMC9299062 | DOI:10.3389/fphar.2022.937045