Prediction model for nonopiate-induced neonatal abstinence syndrome.

Abstract

Neonatal abstinence syndrome (NAS) induced by opiate use is common worldwide. While psychiatric drugs are a more common cause of NAS in Japan, infants of mothers taking psychiatric medications do not always develop NAS. The purpose of this study was to develop a practical model for predicting the onset of nonopiate-induced NAS using variables available at birth. In this diagnostic study, prediction models were developed using multivariable logistic regression with retrospective data collected at our hospital between 2010 and 2019. NAS diagnosis was based on the Isobe score, and maternal medications were converted to dose equivalents. A total of 164 maternal and infant dyads met the inclusion criteria; 91 were included in the analysis, of whom 29 infants (32%) were diagnosed with NAS. Final models were created with and without the drug indices. The model without the drug indices consisted of neonatal head circumference in z-score and Apgar score at 5 minutes < 9, and the model with the drug indices included these, as well as antipsychotics and hypnotics indices. The C-statistics were 0.747 (95% CI: 0.638-0.856), and 0.795 (95% CI: 0.683-0.907), respectively, indicating good predictive accuracy of NAS onset for the models. This study developed models that predicted nonopiate-induced NAS with good accuracy, which may be further improved through the use of drug indices.