ArticleJournal of perinatology : official journal of the California Perinatal Association2021
Predicting NICU admissions in near-term and term infants with low illness acuity.
Article in Journal of perinatology : official journal of the California Perinatal Association, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
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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.
The trial behind it
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Who cites it
6 citing papers in PubMed, 12 citations in OpenAlex.
- Routine 36-week scan: prediction of prolonged neonatal intensive care unit admission.Ultrasound in obstetrics & gynecology : the official journal of the International Society of Ultrasound in Obstetrics and Gynecology · 2025Article
- Neonatal unit admission and offspring mental health trajectories across childhood and adolescence: a nationally representative UK cohort study.BMJ paediatrics open · 2025Article
- Predicting Admission to Neonatal Care Unit at Mid-Pregnancy and Delivery Using Data from a General Obstetric Population.Maternal and child health journal · 2024Article
- Who's in the NICU? A population-level analysis.Journal of perinatology : official journal of the California Perinatal Association · 2024Article
- Evaluating Epidemiologic Trends and Variations in NICU Admissions in California, 2008 to 2018.Hospital pediatrics · 2023Article
- Future roles of artificial intelligence in early pain management of newborns.Paediatric & neonatal pain · 2021Review
Corrections and comments
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Authors and funding
6 authors at 4 institutions in 1 country.
Funding
Abstract
objectiveDescribe NICU admission rate variation among hospitals in infants with birthweight ≥2500 g and low illness acuity, and describe factors that predict NICU admission. STUDY
designRetrospective study from the Vizient Clinical Data Base/Resource Manager®. Support vector machine methodology was used to develop statistical models using (1) patient characteristics (2) only the indicator for the inborn hospital and (3) patient characteristics plus indicator for the inborn hospital.
resultsNICU admission rates of 427,449 infants from 154 hospitals ranged from 0 to 28.6%. C-statistics for the patient characteristics model: 0.64 (Confidence Interval (CI) 0.62-0.65), hospital only model: 0.81 (CI, 0.81-0.82), and patient characteristic plus hospital variable model: 0.84 (CI, 0.83-0.84). CONCLUSION/RELEVANCE: There is wide variation in NICU admission rates in infants with low acuity diagnoses. In all cohorts, birth hospital better predicted NICU admission than patient characteristics alone.
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Registered trials
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