Evidence map›Paper›PMID 40024274›Full record

ArticlePediatrics2025

Adapting a Risk Prediction Tool for Neonatal Opioid Withdrawal Syndrome.

Thomas J Reese, Andrew D Wiese, Ashley A Leech, Henry J Domenico, Elizabeth A McNeer, Sharon E Davis, Michael E Matheny, Adam Wright, Stephen W Patrick

Abstract read
In one paragraph

Article in Pediatrics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Association between NNNS-II profiles and pharmacological treatment in infants with prenatal opioid exposure.Journal of perinatology : official journal of the California Perinatal Association · 2026
    Article
  3. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Thomas J ReeseDepartment of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee.
Andrew D WieseDepartment of Health Policy, Vanderbilt University Medical Center, Nashville, Tennessee.
Ashley A LeechDepartment of Health Policy, Vanderbilt University Medical Center, Nashville, Tennessee.
Henry J DomenicoDepartment of Biostatistics, Vanderbilt University Medical Center, Nashville, Tennessee.
Elizabeth A McNeerDepartment of Biostatistics, Vanderbilt University Medical Center, Nashville, Tennessee.
Sharon E DavisDepartment of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee.
Michael E MathenyDepartment of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee.
Adam WrightDepartment of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee.
Stephen W PatrickDepartment of Health Policy and Management, Rollins School of Public Health, Atlanta, Georgia.

Funding

Optimal Methods for Estimating Policy Effect Heterogeneity in Opioid Policy ResearchP50DA046351 · NIDA · RAND CORPORATION · PI Evan David Peet · 2018 to 2026
$20.8M
Overall: Eunice Kennedy Shriver Intellectual and Developmental Disabilities Research Center at VanderbiltP50HD103537 · NICHD · VANDERBILT UNIVERSITY MEDICAL CENTER · PI Jeffrey L Neul · 2020 to 2026
$10.3M
Vanderbilt Integrated Center of Excellence in Maternal and Pediatric Precision Therapeutics (VICE-MPRINT)P50HD106446 · NICHD · VANDERBILT UNIVERSITY MEDICAL CENTER · PI PRINCE Joseph KANNANKERIL, Digna R Velez Edwards · 2021 to 2026
$9.7M
Advancing Treatment Outcomes for Pregnant Women with Opioid Use DisorderK01DA050740 · NIDA · VANDERBILT UNIVERSITY MEDICAL CENTER · PI LEECH, ASHLEY A · 2020 to 2024
$860k
Benzodiazepine restrictions and the prevention of overdoses and other harmsK01DA051683 · NIDA · VANDERBILT UNIVERSITY MEDICAL CENTER · PI WIESE, ANDREW DAVID · 2021 to 2024
$688k
AHRQ HHS K08 HS029695NICHD NIH HHS P50 HD103537NICHD NIH HHS P50 HD106446NIDA NIH HHS K01 DA050740NIDA NIH HHS K01 DA051683NIDA NIH HHS P50 DA046351
6 · The paper itself

Abstract

backgroundThe American Academy of Pediatrics recommends up to 7 days of observation for neonatal opioid withdrawal syndrome (NOWS) in infants with chronic opioid exposure. However, many of these infants will not develop NOWS, and infants with seemingly less exposure to opioids may develop severe NOWS that requires in-hospital pharmacotherapy. We adapted and validated a prediction model to help clinicians identify infants at birth who will develop severe NOWS.

methodsThis prognostic study included 33 991 births. Severe NOWS was defined as administration of oral morphine. We applied logistic regression with a least absolute shrinkage selection operator approach to develop a severe NOWS prediction model using 37 predictors. To contrast the model with guideline screening criteria, we conducted a decision curve analysis with chronic opioid exposure defined as the mother receiving a diagnosis for opioid use disorder (OUD) or a prescription for long-acting opioids before delivery.

resultsA total of 108 infants were treated with oral morphine for NOWS, and 1243 infants had chronic opioid exposure. The model was highly discriminative, with an area under the receiver operating curve of 0.959 (95% CI, 0.940-0.976). The strongest predictor was mothers' diagnoses of OUD (adjusted odds ratio, 47.0; 95% CI, 26.7-82.7). The decision curve analysis shows a higher benefit with the model across all levels of risk, compared with using the guideline criteria.

conclusionRisk prediction for severe NOWS at birth may better support clinicians in tailoring nonpharmacologic measures and deciding whether to extend birth hospitalization than screening for chronic opioid exposure alone.

Indexed as

Analgesics, OpioidMorphineNeonatal Abstinence SyndromeOpioid-Related DisordersFemaleHumansInfant, NewbornMalePregnancyPrognosisRisk AssessmentAnalgesics, OpioidMorphine

Identifiers

PMID40024274
PMCPMC12854250

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.