Title

A Prediction Model for Positive Infant Meconium and Urine Drug Tests.

Document Type

Article

Publication Date

7-2022

Identifier

DOI: 10.1055/s-0040-1721688

Abstract

Objective: This study aimed to determine the factors associated with positive infant drug screen and create a shortened screen and a prediction model.

Study design: This is a retrospective cohort study of all infants who were tested for drugs of abuse from May 2012 through May 2014. The primary outcome was positive infant urine or meconium drug test. Multivariable logistic regression was used to identify independent risk factors. A combined screen was created, and test characteristics were analyzed.

Results: Among the 3,861 live births, a total of 804 infants underwent drug tests. Variables associated with having a positive infant test were (1) positive maternal urine test, (2) substance use during pregnancy, (3) ≤ one prenatal visit, and (4) remote substance abuse; each p-value was less than 0.0001. A model with an indicator for having at least one of these four predictors had a sensitivity of 94% and a specificity of 69%. Application of this screen to our population would have decreased drug testing by 57%. No infants had a positive urine drug test when their mother's urine drug test was negative.

Conclusion: This simplified screen can guide clinical decision making for determining which infants should undergo drug testing. Infant urine drug tests may not be needed when a maternal drug test result is negative.

Key points: · Many common drug screening criteria are not predictive.. · Four criteria predicted positive infant drug tests.. · No infant urine drug test is needed if the mother tests negative..

Journal Title

American journal of perinatology

Volume

39

Issue

10

First Page

1104

Last Page

1111

MeSH Keywords

Female; Humans; Infant, Newborn; Mass Screening; Meconium; Pregnancy; Retrospective Studies; Substance Abuse Detection; Substance-Related Disorders

Keywords

Mass Screening; Meconium; Pregnancy; Retrospective Studies; Substance Abuse Detection; Substance-Related Disorders

Library Record

Share

COinS