Evidence map›Paper›PMID 35323670›Full record

ArticleMetabolites2022

Comparison of Two Automated Targeted Metabolomics Programs to Manual Profiling by an Experienced Spectroscopist for

Xiangyu Wang, Beata Mickiewicz, Graham C Thompson, Ari R Joffe, Jaime Blackwood, Hans J Vogel, Karen A Kopciuk

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Metabolites, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.4field-weighted citation impact, top 43% 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

1 citing paper in PubMed, 5 citations in OpenAlex.

  1. Mapping ofMagnetic resonance in chemistry : MRC · 2023
    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

7 authors at 3 institutions in 1 country.

Xiangyu WangDepartment of Mathematics and Statistics, University of Calgary, Calgary, AB T2N 1N4, Canada.
Beata MickiewiczDepartment of Pediatrics, Cumming School of Medicine and Alberta Children's Hospital Research Institute, University of Calgary, Calgary, AB T2N 4N1, Canada.ORCID 0000-0002-7842-6656
Graham C ThompsonDepartments of Pediatrics and Emergency Medicine, Cumming School of Medicine, University of Calgary, Calgary, AB T2N 4N1, Canada.ORCID 0000-0002-6781-4186
Ari R JoffeDepartment of Pediatrics, Division of Pediatric Critical Care, University of Alberta, Edmonton, AB T6G 1C9, Canada.
Jaime BlackwoodDepartment of PICU and Critical Care, Alberta Children's Hospital, Alberta Health Services, Calgary, AB T3B 6A8, Canada.
Hans J VogelDepartment of Biological Sciences, Faculty of Science, University of Calgary, Calgary, AB T2N 1N4, Canada.
Karen A KopciukDepartments of Community Health Sciences, Mathematics and Statistics, and Oncology, University of Calgary, Calgary, AB T2N 1N4, Canada.ORCID 0000-0001-7499-1861
University of Calgary · CAAlberta Health Services · CAUniversity of Alberta · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Automated programs that carry out targeted metabolite identification and quantification using proton nuclear magnetic resonance spectra can overcome time and cost barriers that limit metabolomics use. However, their performance needs to be comparable to that of an experienced spectroscopist. A previously analyzed pediatric sepsis data set of serum samples was used to compare results generated by the automated programs rDolphin and BATMAN with the results obtained by manual profiling for 58 identified metabolites. Metabolites were selected using Student's

Indexed as

1H-NMRBATMANmanual profilingMnovapediatric sepsisrDolphintargeted profiling

Identifiers

PMID35323670
PMCPMC8949809
OpenAlexW4220880648

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.