Evidence map›Paper›PMID 30581393›Full record

ArticleFrontiers in psychiatry2018

A Subset of Patients With Autism Spectrum Disorders Show a Distinctive Metabolic Profile by Dried Blood Spot Analyses.

Rita Barone, Salvatore Alaimo, Marianna Messina, Alfredo Pulvirenti, Jean Bastin, MIMIC-Autism Group, Alfredo Ferro, Richard E Frye, Renata Rizzo

Open access · goldAbstract read
In one paragraph

Article in Frontiers in psychiatry, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 39 papers.

0numbers the graph read from it
0cells of the map it votes in
39citing papers in PubMed
3.0field-weighted citation impact, top 8% 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

39 citing papers in PubMed, 65 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 3 countries.

Rita BaroneChild Neurology and Psychiatry, Department of Clinical and Experimental Medicine, University of Catania, Catania, Italy.
Salvatore AlaimoBioinformatics Unit, Department of Clinical and Experimental Medicine, University of Catania, Catania, Italy.
Marianna MessinaReferral Centre for Inherited Metabolic Disorders, Department of Clinical and Experimental Medicine, University of Catania, Catania, Italy.
Alfredo PulvirentiBioinformatics Unit, Department of Clinical and Experimental Medicine, University of Catania, Catania, Italy.
Jean BastinSorbonne Paris Cité, Faculté des Sciences Fondamentales et Biomédicales, Université Paris Descartes, Paris, France.
MIMIC-Autism Group
Alfredo FerroBioinformatics Unit, Department of Clinical and Experimental Medicine, University of Catania, Catania, Italy.
Richard E FryeUniversity of Arizona College of Medicine, Phoenix, AZ, United States.
Renata RizzoChild Neurology and Psychiatry, Department of Clinical and Experimental Medicine, University of Catania, Catania, Italy.
University of Catania · ITUniversity of Arizona · USDélégation Paris 5 · FR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Autism spectrum disorder (ASD) is currently diagnosed according to behavioral criteria. Biomarkers that identify children with ASD could lead to more accurate and early diagnosis. ASD is a complex disorder with multifactorial and heterogeneous etiology supporting recognition of biomarkers that identify patient subsets. We investigated an easily testable blood metabolic profile associated with ASD diagnosis using high throughput analyses of samples extracted from dried blood spots (DBS). A targeted panel of 45 ASD analytes including acyl-carnitines and amino acids extracted from DBS was examined in 83 children with ASD (60 males; age 6.06 ± 3.58, range: 2-10 years) and 79 matched, neurotypical (NT) control children (57 males; age 6.8 ± 4.11 years, range 2.5-11 years). Based on their chronological ages, participants were divided in two groups: younger or older than 5 years. Two-sided

Indexed as

autism spectrum disordersdried blood spotsESI-MS/MSmachine learningmitochondrial fatty acid β-oxidation

Identifiers

PMID30581393
PMCPMC6292950
OpenAlexW2902358926

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.