Evidence map›Paper›PMID 40506467›Full record

ArticleNPJ genomic medicine2025

MPSE identifies newborns for whole genome sequencing within 48 h of NICU admission.

Bennet Peterson, Edwin F Juarez, Barry Moore, Edgar Javier Hernandez, Erwin Frise, Jianrong Li, Yves Lussier, Martin Tristani-Firouzi, Martin G Reese, Sabrina Malone Jenkins and 3 more

Abstract read
In one paragraph

Article in NPJ genomic medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

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

  1. Pooled it
  2. 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

13 authors.

Bennet PetersonDepartment of Biomedical Informatics, University of Utah, Salt Lake City, UT, USA.
Edwin F JuarezRady Children's Institute for Genomic Medicine, San Diego, CA, USA.
Barry MooreDepartment of Human Genetics, Utah Center for Genetic Discovery, University of Utah, Salt Lake City, UT, USA.
Edgar Javier HernandezDepartment of Biomedical Informatics, University of Utah, Salt Lake City, UT, USA.
Erwin FriseFabric Genomics Inc., Oakland, CA, USA.
Jianrong LiDepartment of Biomedical Informatics, University of Utah, Salt Lake City, UT, USA.
Yves LussierDepartment of Biomedical Informatics, University of Utah, Salt Lake City, UT, USA.
Martin Tristani-FirouziDivision of Pediatric Cardiology, University of Utah School of Medicine, Salt Lake City, UT, USA.
Martin G ReeseFabric Genomics Inc., Oakland, CA, USA.
Sabrina Malone JenkinsDivision of Neonatology, Department of Pediatrics, University of Utah School of Medicine, Salt Lake City, UT, USA.
Stephen F KingsmoreRady Children's Institute for Genomic Medicine, San Diego, CA, USA.
Matthew N BainbridgeRady Children's Institute for Genomic Medicine, San Diego, CA, USA.
Mark YandellDepartment of Human Genetics, Utah Center for Genetic Discovery, University of Utah, Salt Lake City, UT, USA. myandell@genetics.utah.edu.

Funding

Scripps Translational Science InstituteUL1TR002550 · NCATS · SCRIPPS RESEARCH INSTITUTE, THE · PI TOPOL, ERIC JEFFREY · 2018 to 2022
$28.9M
UNIVERSITY OF UTAH MEDICAL INFORMATICS TRAININGT15LM007124 · NLM · UTAH STATE HIGHER EDUCATION SYSTEM--UNIVERSITY OF UTAH · PI Karen Louise Eilbeck · 1997 to 2026
$22.0M
Addressing the research-practice gap in the implementation of rapid whole genome sequencing in the NICUK08HG013111 · NHGRI · UTAH STATE HIGHER EDUCATION SYSTEM--UNIVERSITY OF UTAH · PI Sabrina Malone Jenkins · 2023 to 2026
$1.1M
From genomics to natural language processing: A protected environment for research computing in the health scienceS10OD021644 · OD · UNIVERSITY OF UTAH · PI CHEATHAM, THOMAS E. · 2017 to 2017
$494k
NCATS NIH HHS UL1 TR002550NHGRI NIH HHS K08 HG013111NIH HHS S10 OD021644NLM NIH HHS T15 LM007124
6 · The paper itself

Abstract

Identifying critically ill newborns who will benefit from whole genome sequencing (WGS) is difficult and time-consuming due to complex eligibility criteria and evolving clinical features. The Mendelian Phenotype Search Engine (MPSE) automates the prioritization of neonatal intensive care unit (NICU) patients for WGS. Using clinical data from 2885 NICU patients, we evaluated the utility of different machine learning (ML) classifiers, clinical natural language processing (CNLP) tools, and types of Electronic Health Record (EHR) data to identify sick newborns with genetic diseases. Our results show that MPSE can identify children most likely to benefit from WGS within the first 48 h after NICU admission, a critical window for maximally impactful care. Moreover, MPSE provided stable, robust means to identify these children using many combinations of classifiers, CNLP tools, and input data types-meaning MPSE can be used by diverse health systems despite differences in EHR contents and IT support.

Identifiers

PMID40506467
PMCPMC12162843

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.