Evidence map›Paper›PMID 42477106›Full record

ArticleJournal of perinatology : official journal of the California Perinatal Association2026

Development and external validation of the NEO-READY model to predict date of discharge among premature neonatal intensive care patients.

Hannah Lonsdale, Kevin Patel, Henry Domenico, Ryan S Moore, Allison B McCoy, Benjamin French, S Trent Rosenbloom, Daniel W Byrne, Robert E Freundlich, Mhd Wael Alrifai

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Article in Journal of perinatology : official journal of the California Perinatal Association, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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.

2 · The registry

The trial behind it

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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

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No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

10 authors.

Hannah LonsdaleDepartment of Anesthesiology, Vanderbilt University Medical Center, Nashville, TN, USA. hannah.lonsdale@vumc.org.ORCID http://orcid.org/0000-0001-9953-8844
Kevin PatelDepartment of Neonatal and Newborn Medicine, Kaiser Permanente Roseville Medical Center, Roseville, CA, USA.
Henry DomenicoDepartment of Biostatistics, Vanderbilt University, Nashville, TN, USA.
Ryan S MooreDepartment of Biostatistics, Vanderbilt University, Nashville, TN, USA.
Allison B McCoyDepartment of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA.
Benjamin FrenchDepartment of Biostatistics, Vanderbilt University, Nashville, TN, USA.
S Trent RosenbloomDepartment of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA.
Daniel W ByrneWhiting School of Engineering and the Department of Biostatistics, Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD, USA.
Robert E FreundlichDepartments of Anesthesiology and Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA.
Mhd Wael AlrifaiDepartments of Pediatrics and Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA.ORCID http://orcid.org/0000-0003-0761-4905

Funding

Reducing Reintubation Risk in High-Risk Cardiac Surgery Patients with High-Flow Nasal Cannula -the "I-CAN" studyK23HL148640 · NHLBI · VANDERBILT UNIVERSITY MEDICAL CENTER · PI FREUNDLICH, ROBERT EDWARD · 2020 to 2024
$867k
U.S. Department of Health & Human Services | National Institutes of Health (NIH) 5T32GM108554U.S. Department of Health & Human Services | National Institutes of Health (NIH) K23HL148640
6 · The paper itself

Abstract

objectiveTo develop a parsimonious, interpretable, and accurate model for predicting discharge for premature infants in the NICU-a model suitable for prospective evaluation and integration into clinical workflows. STUDY

designUsing routinely available electronic health record data, we developed and validated NEOnatal Reliable Estimation of Approaching Discharge in Young Infants (NEO-READY), a daily-updating model that predicts the likelihood of discharge within 5 days for premature infants.

resultsData from 702 infants were used to develop the model, and data from 201 infants were used for temporal external validation. The model included 13 predictors and two interaction terms and demonstrated excellent discrimination across development (AUC = 0.88, 95% CI 0.87-0.90) and validation (0.90, 0.88-0.91) cohorts.

conclusionThis work represents step 1 toward our long-term goal: integrating the NEO-READY model into clinical workflows as part of a comprehensive strategy to improve discharge preparedness, reduce discharge delays, and optimize NICU resources.

Identifiers

PMID42477106

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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.