An Algorithm to Detect Adverse Drug Reactions in the Neonatal Intensive Care Unit

Authors


Corresponding Author:

Wei Du, PhD, Division of Clinical Pharmacology & Toxicology, Department of Pediatrics, Wayne State University, Children—s Hospital of Michigan, 3901 Beaubien, 3N47, Detroit, MI 48201, USA Email: duw@med.wayne.edu

Abstract

Critically ill newborns in neonatal intensive care units (NICUs) are at greater risk of developing adverse drug reactions (ADRs). Differentiation of ADRs from reactions associated with organ dysfunction/immaturity is difficult. Current ADR algorithm scoring was established arbitrarily without validation in infants. The study objective was to develop a valid and reliable algorithm to identify ADRs in the NICU. Algorithm development began with a 24-item questionnaire for data collection on 100 previously suspected ADRs. Five pediatric pharmacologists independently rated cases as definite, probable, possible, and unlikely ADRs. Consensus “gold standard” was reached via teleconference. Logistic regression and iterative C programs were used to derive the scoring system. For validation, 50 prospectively collected ADR cases were assessed by 3 clinicians using the new algorithm and the Naranjo algorithm. Weighted kappa and intraclass correlation coefficient (ICC) were used to compare validity and reliability of algorithms. The new algorithm consists of 13 items. Kappa and ICC of the new algorithm were 0.76 and 0.62 versus 0.31 and 0.43 for the Naranjo algorithm. The new algorithm developed using actual patient data is more valid and reliable than the Naranjo algorithm for identifying ADRs in the NICU population. Because of the relatively small and nonrandom samples, further refinement and additional testing are needed.

Ancillary