Evidence map›Paper›PMID 30402168›Full record

ArticleDisease markers2018

Predictive Role of Urinary Metabolic Profile for Abnormal MRI Score in Preterm Neonates.

Maria Luisa Tataranno, Serafina Perrone, Mariangela Longini, Caterina Coviello, Maria Tassini, Antonio Vivi, Marco Calderisi, Linda S deVries, Floris Groenendaal, Giuseppe Buonocore and 1 more

Abstract read
In one paragraph

Article in Disease markers, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
–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

10 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. A LongitudinalMetabolites · 2022
    Article
  7. Article
  8. Review
  9. [Research advances in the biomarkers of brain damage in preterm infants].Zhongguo dang dai er ke za zhi = Chinese journal of contemporary pediatrics · 2019
    Review
  10. [Application of metabolomics in neonatal clinical practice].Zhongguo dang dai er ke za zhi = Chinese journal of contemporary pediatrics · 2019
    Review
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

11 authors.

Maria Luisa TatarannoDepartment of Neonatology, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht University, Utrecht, Netherlands.
Serafina PerroneDepartment of Molecular and Developmental Medicine, University of Siena, Siena, Italy.ORCID 0000-0001-5478-5657
Mariangela LonginiDepartment of Molecular and Developmental Medicine, University of Siena, Siena, Italy.
Caterina CovielloDivision of Neonatology, Careggi University Hospital of Florence, Florence, Italy.
Maria TassiniNMR Centre, University of Siena, Siena, Italy.
Antonio ViviNMR Centre, University of Siena, Siena, Italy.
Marco CalderisiKode srl, Pisa, Italy.
Linda S deVriesDepartment of Neonatology, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht University, Utrecht, Netherlands.
Floris GroenendaalDepartment of Neonatology, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht University, Utrecht, Netherlands.ORCID 0000-0002-9284-1637
Giuseppe BuonocoreDepartment of Molecular and Developmental Medicine, University of Siena, Siena, Italy.ORCID 0000-0002-7921-7485
Manon J N L BendersDepartment of Neonatology, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht University, Utrecht, Netherlands.ORCID 0000-0001-5491-9168

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BACKGROUND AND

objectiveEarly identification of neonates at risk for brain injury is important to start appropriate intervention. Urinary metabolomics is a source of potential, noninvasive biomarkers of brain disease. We studied the urinary metabolic profile at 2 and 10 days in preterm neonates with normal/mild and moderate/severe MRI abnormalities at term equivalent age.

methodsUrine samples were collected at two and 10 days after birth in 30 extremely preterm infants and analyzed using proton magnetic resonance spectroscopy. A 3 T MRI was performed at term equivalent age, and images were scored for white matter (WM), cortical grey matter (cGM), deep GM, and cerebellar abnormalities. Infants were divided in two groups: normal/mild and moderately/severely abnormal MRI scores.

resultsNo significant clustering was seen between normal/mild and moderate/severe MRI scores for all regions at both time points. The ROC curves distinguished neonates at 2 and 10 days who later developed a markedly less mature cGM score from the others (2 d: area under the curve (AUC) = 0.72, specificity (SP) = 65%, sensitivity (SE) = 75% and 10 d: AUC = 0.80, SP = 78%, SE = 80%) and a moderately to severely abnormal WM score (2 d: AUC = 0.71, specificity (SP) = 80%, sensitivity (SE) = 72% and 10 d: AUC = 0.69, SP = 64%, SE = 89%).

conclusionsEarly urinary spectra of preterm infants were able to discriminate metabolic profiles in patients with moderately/severely abnormal cGM and WM scores at term equivalent age. Urine spectra are promising for early identification of neonates at risk of brain damage and allow understanding of the pathogenesis of altered brain development.

Indexed as

MetabolomeBiomarkersBrainDevelopmental DisabilitiesFemaleHumansInfant, Extremely PrematureInfant, NewbornMagnetic Resonance ImagingMaleBiomarkers

Identifiers

PMID30402168
PMCPMC6191951

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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.