Evidence map›Paper›PMID 36769570›Full record

ArticleJournal of clinical medicine2023

Gas Chromatography-Mass Spectrometry (GC-MS) Metabolites Analysis in Endometriosis Patients: A Prospective Observational Translational Study.

Stefano Angioni, Francesca Congiu, Salvatore Giovanni Vitale, Maurizio Nicola D'Alterio, Antonio Noto, Giovanni Monni, Maria Laura Santoru, Vassilios Fanos, Federica Murgia, Luigi Atzori

Abstract read
In one paragraph

Article in Journal of clinical medicine, 2023. 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.

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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

10 authors.

Stefano AngioniDivision of Gynecology and Obstetrics, Department of Surgical Sciences, University of Cagliari, 09124 Cagliari, Italy.ORCID 0000-0002-2314-0028
Francesca CongiuASSL Lanusei, ATS Sardinia, Obstetrics and Gynecology Unit, 08045 Lanusei, Italy.
Salvatore Giovanni VitaleDivision of Gynecology and Obstetrics, Department of Surgical Sciences, University of Cagliari, 09124 Cagliari, Italy.ORCID 0000-0001-6871-6097
Maurizio Nicola D'AlterioDivision of Gynecology and Obstetrics, Department of Surgical Sciences, University of Cagliari, 09124 Cagliari, Italy.ORCID 0000-0001-9874-1488
Antonio NotoDepartment of Surgical Sciences, Neonatal Intensive Care Unit, Puericulture Institute, and Neonatal Section, University of Cagliari, 09124 Cagliari, Italy.
Giovanni MonniDepartment of Prenatal and Preimplantation Genetic Diagnosis and Fetal Therapy, Ospedale Pediatrico Microcitemico A. Cao, 09124 Cagliari, Italy.ORCID 0000-0002-7386-5967
Maria Laura SantoruDepartment of Biomedical Sciences, Unit of Clinic Metabolomics, University of Cagliari, 09124 Cagliari, Italy.
Vassilios FanosDepartment of Surgical Sciences, Neonatal Intensive Care Unit, Puericulture Institute, and Neonatal Section, University of Cagliari, 09124 Cagliari, Italy.
Federica MurgiaDepartment of Biomedical Sciences, Unit of Clinic Metabolomics, University of Cagliari, 09124 Cagliari, Italy.ORCID 0000-0003-4080-9851
Luigi AtzoriDepartment of Biomedical Sciences, Unit of Clinic Metabolomics, University of Cagliari, 09124 Cagliari, Italy.ORCID 0000-0002-0606-4959

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundEndometriosis affects women of reproductive age, and its pathogenesis is still unclear. Typically, it overlaps other similar medical and surgical conditions, determining a delay in early diagnosis. Metabolomics allows studying metabolic changes in different physiological or pathological states to discover new potential biomarkers. We used the gas chromatography-mass spectrometer (GC-MS) to explore metabolic alterations in endometriosis to better understand its pathophysiology and find new biomarkers.

methodsTwenty-two serum samples of patients with symptomatic endometriosis and ten without it were collected and subjected to GC-MS analysis. Multivariate and univariate statistical analyses were performed, followed by pathway analysis.

resultsPartial least squares discriminant analysis was performed to determine the differences between the two groups (

conclusionsThe metabolomic approach identifies metabolic alterations in women with endometriosis. These findings may improve our understanding of the pathophysiological mechanisms of disease and the discovery of new biomarkers.

Indexed as

biomarkersendometriosisgas chromatography–mass spectrometrymetabolomicsmultivariate analysis

Identifiers

PMID36769570
PMCPMC9918082

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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.