Evidence map›Paper›PMID 35094641›Full record

Trial reportBioengineered2022

Human Plasma Metabolomics Identify 9-cis-retinoic Acid and Dehydrophytosphingosine Levels as Novel biomarkers for Early Ventricular Fibrillation after ST-elevated Myocardial Infarction.

Jieying Luo, Junaid Ahmed Shaikh, Lei Huang, Lei Zhang, Shahid Iqbal, Yu Wang, Bojiang Liu, Quan Zhou, Aisha Ajmal, Maryam Rizvi and 2 more

Open access · goldAbstract readClinical TrialVideo-Audio Media
In one paragraph

Trial report in Bioengineered, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed, 1 pooled it
1.0field-weighted citation impact, top 26% 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

10 citing papers in PubMed, 1 synthesis or guideline pooled it, 12 citations in OpenAlex.

  1. Pooled it
  2. Review
  3. Review
  4. Article
  5. Article
  6. Article
  7. Progress in the Metabolomics of Acute Coronary Syndrome.Reviews in cardiovascular medicine · 2023
    Review
  8. Review
  9. Review
  10. 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

12 authors at 3 institutions in 2 countries.

Jieying LuoDepartment of Heart Center, The Third Central Hospital of Tianjin, Tianjin, China.ORCID 0000-0002-1232-8842
Junaid Ahmed ShaikhGKT School of Medical Education, Faculty of Life Science and Medicine, King's College London, London SE1 IUL, UK.ORCID 0000-0001-7025-6333
Lei HuangDepartment of Heart Center, The Third Central Hospital of Tianjin, Tianjin, China.ORCID 0000-0002-3911-0915
Lei ZhangDepartment of Clinical Laboratory, Tianjin Third Central Hospital, Tianjin, China.
Shahid IqbalGKT School of Medical Education, Faculty of Life Science and Medicine, King's College London, London SE1 IUL, UK.ORCID 0000-0001-5119-3576
Yu WangDepartment of Heart Center, The Third Central Hospital of Tianjin, Tianjin, China.
Bojiang LiuDepartment of Heart Center, The Third Central Hospital of Tianjin, Tianjin, China.
Quan ZhouDepartment of Heart Center, The Third Central Hospital of Tianjin, Tianjin, China.
Aisha AjmalSt George's Hospital Medical School, St. George's, University of London, Cranmer Terrace, London, SW17 0RE UK.ORCID 0000-0002-4212-5472
Maryam RizviGKT School of Medical Education, Faculty of Life Science and Medicine, King's College London, London SE1 IUL, UK.ORCID 0000-0001-6750-9889
Maryam AjmalGKT School of Medical Education, Faculty of Life Science and Medicine, King's College London, London SE1 IUL, UK.ORCID 0000-0002-8810-9515
Yingwu LiuDepartment of Heart Center, The Third Central Hospital of Tianjin, Tianjin, China.
Tianjin Third Central Hospital · CNKing's College London · GBUniversity of London · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The relevant metabolite biomarkers for risk prediction of early onset of ventricular fibrillation (VF) after ST-segment elevation myocardial infarction (STEMI) remain unstudied. Here, we aimed to identify these imetabolites and the important metabolic pathways involved, and explore whether these metabolites could be used as predictors for the phenotype. Plasma samples were obtained retrospectively from a propensity-score matched cohort including 42 STEMI patients (21 consecutive VF and 21 non-VF). Ultra-performance liquid chromatography and mass spectrometry in combination with a comprehensive analysis of metabolomic data using Metaboanalyst 5.0 version were performed. As a result, the retinal metabolism pathway proved to be the most discriminative for the VF phenotype. Furthermore, 9-cis-Retinoic acid (9cRA) and dehydrophytosphingosine proved to be the most discriminative biomarkers. Biomarker analysis through receiver operating characteristic (ROC) curve showed the 2-metabolite biomarker panel yielding an area under the curve (AUC) of 0.836. The model based on Monte Carlo cross-validation found that 9cRA had the greatest probability of appearing in the predictive panel of biomarkers in the model. Validation of model efficiency based on an ROC curve showed that the combination model constructed by 9cRA and dehydrophytosphingosine had a good predictive value for early-onset VF after STEMI, and the AUC was 0.884 (95% CI 0.714-1). Conclusively, the retinol metabolism pathway was the most powerful pathway for differentiating the post-STEMI VF phenotype. 9cRA was the most important predictive biomarker of VF, and a plasma biomarker panel made up of two metabolites, may help to build a potent predictive model for VF.

Indexed as

AdolescentAdultAgedAlitretinoinBiomarkersFemaleHumansMaleMiddle AgedSphingosineST Elevation Myocardial InfarctionVentricular FibrillationAlitretinoinBiomarkersphytosphingosineSphingosineacute coronary syndromeAcute myocardial infarctionmetabonomicssudden deathventricular fibrillation

Identifiers

PMID35094641
PMCPMC8974221
OpenAlexW4213111061

What Socratic 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 Socratic graph.