ABSTRACT
OBJECTIVES: To develop and validate clinical risk prediction tools for neonatal abstinence syndrome (NAS). STUDY DESIGN: We developed prediction models for NAS based on a set of 30 demographic and antenatal exposure covariates collected during pregnancy. Data (outpatient prescription, vital, and administrative records), were obtained from enrollees in the Tennessee Medicaid Program from 2009 to 2014. Models were created using logistic regression and backward selection based on improvement in the Akaike information criterion, and internally validated using bootstrap cross-validation. RESULTS: A total of 218 020 maternal and infant dyads met inclusion criteria, of whom 3208 infants were diagnosed with NAS. The general population model included age, hepatitis C virus infection, days of opioid used by type, number of cigarettes used daily, and the following medications used in the last 30 day of pregnancy: bupropion, antinausea medicines, benzodiazepines, antipsychotics, and gabapentin. Infant characteristics included birthweight, small for gestational age, and infant sex. A high-risk model used a smaller number of predictive variables. Both models discriminated well with an area under the curve of 0.89 and were well-calibrated for low-risk infants. CONCLUSIONS: We developed 2 predictive models for NAS based on demographics and antenatal exposure during the last 30 days of pregnancy that were able to risk stratify infants at risk of developing the syndrome.
Subject(s)
Neonatal Abstinence Syndrome/diagnosis , Risk Assessment/methods , Adult , Analgesics/administration & dosage , Analgesics/adverse effects , Antiemetics/administration & dosage , Antiemetics/adverse effects , Antipsychotic Agents/administration & dosage , Antipsychotic Agents/adverse effects , Benzodiazepines/administration & dosage , Benzodiazepines/adverse effects , Bupropion/administration & dosage , Bupropion/adverse effects , Female , Gabapentin/administration & dosage , Gabapentin/adverse effects , Hepatitis C/epidemiology , Humans , Infant, Low Birth Weight , Infant, Newborn , Infant, Small for Gestational Age , Male , Maternal Age , Maternal Exposure/adverse effects , Maternal-Fetal Exchange , Opiate Substitution Treatment , Opioid-Related Disorders/drug therapy , Pregnancy , Retrospective Studies , Sex Distribution , Smoking/epidemiology , Smoking Cessation Agents/administration & dosage , Smoking Cessation Agents/adverse effects , Young AdultABSTRACT
Ilex paraguariensis (maté) is one of the best sources of chlorogenic acids (CGA) in nature. When leaves are toasted, some isomers are partly transformed into 1,5-γ-quinolactones (CGL). Both CGA and CGL are important contributors to the brew's flavor and are thought to contribute to human health. In this study, we quantified 9 CGA, 2 CGL, and caffeic acid in 20 samples of dried green and toasted maté that are commercially available in Brazil. Total CGA content in green maté varied from 8.7 to 13.2 g/100 g, dry weight (dw). Caffeic acid content varied from 10.8 to 13.5 mg/100 g dw, respectively. Content in toasted maté varied from 1.5 to 4.6 g/100 g and from 1.5 to 7.2 mg/100 g dw, respectively. Overall, caffeoylquinic acid isomers (CQA) were the most abundant CGA in both green and toasted maté, followed by dicaffeoylquinic acids (diCQA) and feruloylquinic acids (FQA). These classes accounted for 58.5%, 40.0%, and 1.5% of CGA, respectively, in green maté and 76.3%, 20.7%, and 3.0%, respectively, in toasted maté. Average contents of 3-caffeoylquinolactone (3-CQL) and 4-caffeoylquinolactone (4-CQL) in commercial toasted samples were 101.5 mg/100 g and 61.8 mg/100 g dw, respectively. These results show that, despite overall losses during the toasting process, CGA concentrations are still substantial in toasted leaves, compared to other food sources of CGA and phenolic compounds in general. In addition to evaluating commercial samples, investigation of changes in CGA profile and formation of 1,5-γ-quinolactones was performed in experimental maté toasting.