Evidence map›Paper›PMID 30360494›Full record

ArticleInternational journal of molecular sciences2018

Fingerprinting Acute Digestive Diseases by Untargeted NMR Based Metabolomics.

Panteleimon G Takis, Antonio Taddei, Riccardo Pini, Stefano Grifoni, Francesca Tarantini, Paolo Bechi, Claudio Luchinat

Open access · goldAbstract read
In one paragraph

Article in International journal of molecular sciences, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 1 pooled it
0.5field-weighted citation impact, top 36% 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

7 citing papers in PubMed, 1 synthesis or guideline pooled it, 18 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Metabonomics in Gastroenterology and Hepatology.International journal of molecular sciences · 2019
    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 4 institutions in 1 country.

Panteleimon G TakisGiotto Biotech, S.r.l, Via Madonna del Piano 6, 50019 Sesto Fiorentino, Italy. takis@giottobiotech.com.ORCID 0000-0002-7224-0412
Antonio TaddeiDepartment of Surgery and Translational Medicine, School of Medicine, Careggi University Hospital, Largo Brambilla 3, 50134 Florence, Italy. antonio.taddei@unifi.it.ORCID 0000-0003-2963-4085
Riccardo PiniDepartment of Experimental and Clinical Medicine, University of Florence, Largo Brambilla 3, 50134 Florence, Italy. riccardo.pini@unifi.it.
Stefano GrifoniDepartment of Emergency Medicine and Surgery, Careggi University Hospital, 50134 Florence, Italy. grifonis@aou-careggi.toscana.it.
Francesca TarantiniDepartment of Experimental and Clinical Medicine, University of Florence, Largo Brambilla 3, 50134 Florence, Italy. francesca.tarantini@unifi.it.
Paolo BechiDepartment of Surgery and Translational Medicine, School of Medicine, Careggi University Hospital, Largo Brambilla 3, 50134 Florence, Italy. paolo.bechi@unifi.it.
Claudio LuchinatGiotto Biotech, S.r.l, Via Madonna del Piano 6, 50019 Sesto Fiorentino, Italy. claudioluchinat@cerm.unifi.it.
Azienda Ospedaliero-Universitaria Careggi · ITUniversity of Florence · ITGiotto Biotech (Italy) · ITInteruniversity Consortium for Magnetic Resonance · IT

Funding

Region of Tuscany Ricerca di marcatori precoci di ischemia intestinale: MaPi-Int
6 · The paper itself

Abstract

Precision medicine may significantly contribute to rapid disease diagnosis and targeted therapy, but relies on the availability of detailed, subject specific, clinical information. Proton nuclear magnetic resonance (¹H⁻NMR) spectroscopy of body fluids can extract individual metabolic fingerprints. Herein, we studied 64 patients admitted to the Florence main hospital emergency room with severe abdominal pain. A blood sample was drawn from each patient at admission, and the corresponding sera underwent ¹H⁻NMR metabolomics fingerprinting. Unsupervised Principal Component Analysis (PCA) analysis showed a significant discrimination between a group of patients with symptoms of upper abdominal pain and a second group consisting of patients with diffuse abdominal/intestinal pain. Prompted by this observation, supervised statistical analysis (Orthogonal Partial Least Squares⁻Discriminant Analysis (OPLS-DA)) showed a very good discrimination (>90%) between the two groups of symptoms. This is a surprising finding, given that neither of the two symptoms points directly to a specific disease among those studied here. Actually herein, upper abdominal pain may result from either symptomatic gallstones, cholecystitis, or pancreatitis, while diffuse abdominal/intestinal pain may result from either intestinal ischemia, strangulated obstruction, or mechanical obstruction. Although limited by the small number of samples from each of these six conditions, discrimination of these diseases was attempted. In the first symptom group, >70% discrimination accuracy was obtained among symptomatic gallstones, pancreatitis, and cholecystitis, while for the second symptom group >85% classification accuracy was obtained for intestinal ischemia, strangulated obstruction, and mechanical obstruction. No single metabolite stands up as a possible biomarker for any of these diseases, while the contribution of the whole ¹H⁻NMR serum fingerprint seems to be a promising candidate, to be confirmed on larger cohorts, as a first-line discriminator for these diseases.

Indexed as

Acute DiseaseDigestive System DiseasesFemaleHumansIleusMagnetic Resonance SpectroscopyMaleMetabolomicsMultivariate AnalysisPancreatitisPrincipal Component Analysisacute digestive diseasebiliary colicileusintestinal ischemiaintestinal strangulated obstructionmetabolomicspancreatitis

Identifiers

PMID30360494
PMCPMC6274841
OpenAlexW2897286157

What OpenQuestion holds

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Registered trials

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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.