Causality assessment of adverse drug reactions in neonates: a comparative study between Naranjo's algorithm and Du's tool.

Abstract

Algorithms for causality assessment of adverse drug reactions (ADRs) in a neonatal intensive care unit (NICU) are important in the management of adverse events, however, it is inconclusive which tool best suits pharmacovigilance in neonates. To compare the performance of the algorithms of Du and Naranjo in determining causality in cases of ADRs in neonates in a NICU. This observational and prospective study was conducted in a NICU of a Brazilian maternity school between January 2019 and December 2020. Independently, three clinical pharmacists used the algorithms of Naranjo and Du in 79 cases of ADRs in 57 neonates. The algorithms were evaluated for inter-rater and inter-tool agreement using Cohen's kappa coefficient (k). The Du algorithm showed greater ability to identify definite ADRs (≈ 60%), but had low reproducibility (overall k = 0.108; 95% CI 0.064-0.149). In contrast, the Naranjo algorithm showed a lower proportion of definite ADRs (< 4%), but had good reproducibility (overall k = 0.402; 95% CI 0.379-0.429). The tools showed no significant correlation regarding ADR causality classification (overall k = - 0.031; 95% CI - 0.049 to 0.065). Although the Du algorithm has a lower reproducibility compared to the Naranjo, this tool showed good sensitivity for classifying ADRs as definite, proving to be a more suitable tool for neonatal clinical routine.