Evidence map›Paper›PMID 34671094›Full record

Observational studyPediatric research2022

Newborn screen metabolic panels reflect the impact of common disorders of pregnancy.

Jonathan D Reiss, Alan L Chang, Jonathan A Mayo, Katherine Bianco, Henry C Lee, David K Stevenson, Gary M Shaw, Nima Aghaeepour, Karl G Sylvester

Open access · greenAbstract readObservational Study
In one paragraph

Observational study in Pediatric research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
1.3field-weighted citation impact, top 17% of its field
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

9 citing papers in PubMed, 12 citations in OpenAlex.

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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 at 3 institutions in 1 country.

Jonathan D Reiss *Division of Neonatology, Department of Pediatrics, Stanford University School of Medicine, Palo Alto, CA, USA.
Alan L Chang *Department of Anesthesiology, Pain and Perioperative Medicine, Stanford University, Palo Alto, CA, USA.
Jonathan A MayoDivision of Neonatology, Department of Pediatrics, Stanford University School of Medicine, Palo Alto, CA, USA.
Katherine BiancoDivision of Maternal-Fetal Medicine, Department of Obstetrics & Gynecology, Stanford University School of Medicine, Palo Alto, CA, USA.
Henry C LeeDivision of Neonatology, Department of Pediatrics, Stanford University School of Medicine, Palo Alto, CA, USA.
David K StevensonDivision of Neonatology, Department of Pediatrics, Stanford University School of Medicine, Palo Alto, CA, USA.
Gary M ShawDivision of Neonatology, Department of Pediatrics, Stanford University School of Medicine, Palo Alto, CA, USA.
Nima AghaeepourDepartment of Anesthesiology, Pain and Perioperative Medicine, Stanford University, Palo Alto, CA, USA.
Karl G SylvesterDivision of Pediatric Surgery, Department of Surgery, Stanford University School of Medicine, Palo Alto, CA, USA. Sylvester@Stanford.edu.
Stanford University · USStanford Medicine · USMarch of Dimes · US

Funding

Machine Learning for Integrative Modeling of the Immune System in Clinical SettingsR35GM138353 · NIGMS · STANFORD UNIVERSITY · PI AGHAEEPOUR, NIMA · 2020 to 2024
$2.2M
NIGMS NIH HHS R35 GM138353
6 · The paper itself

Abstract

backgroundHypertensive disorders of pregnancy and maternal diabetes profoundly affect fetal and newborn growth, yet disturbances in intermediate metabolism and relevant mediators of fetal growth alterations remain poorly defined. We sought to determine whether there are distinct newborn screen metabolic patterns among newborns affected by maternal hypertensive disorders or diabetes in utero.

methodsA retrospective observational study investigating distinct newborn screen metabolites in conjunction with data linked to birth and hospitalization records in the state of California between 2005 and 2010.

resultsA total of 41,333 maternal-infant dyads were included. Infants of diabetic mothers demonstrated associations with short-chain acylcarnitines and free carnitine. Infants born to mothers with preeclampsia with severe features and chronic hypertension with superimposed preeclampsia had alterations in acetylcarnitine, free carnitine, and ornithine levels. These results were further accentuated by size for gestational age designations.

conclusionsInfants of diabetic mothers demonstrate metabolic signs of incomplete beta oxidation and altered lipid metabolism. Infants of mothers with hypertensive disorders of pregnancy carry analyte signals that may reflect oxidative stress via altered nitric oxide signaling. The newborn screen analyte composition is influenced by the presence of these maternal conditions and is further associated with the newborn size designation at birth. IMPACT: Substantial differences in newborn screen analyte profiles were present based on the presence or absence of maternal diabetes or hypertensive disorder of pregnancy and this finding was further influenced by the newborn size designation at birth. The metabolic health of the newborn can be examined using the newborn screen and is heavily impacted by the condition of the mother during pregnancy. Utilizing the newborn screen to identify newborns affected by common conditions of pregnancy may help relate an infant's underlying biological disposition with their clinical phenotype allowing for greater risk stratification and intervention.

Indexed as

Diabetes, GestationalHypertension, Pregnancy-InducedPre-EclampsiaAcetylcarnitineFemaleHumansNitric OxideOrnithinePregnancyAcetylcarnitineNitric OxideOrnithine

Identifiers

PMID34671094
PMCPMC10265936
OpenAlexW3207317934

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.