Evidence map›Paper›PMID 39967413›Full record

Observational studyClinical cardiology2025

"A Biomarker-Based Scoring System to Assess the Presence of Obstructive Coronary Artery Disease in Patients With Myocardial Infarction".

María Jesús Espinosa Pascual, Jose Antonio Carnicero Carreño, Mariam El Assar, Renee Olsen Rodríguez, Alfonso Fraile Sanz, Paula Rodriguez Montes, Nuria Gil Mancebo, Alberto Sánchez Ferrer, Bárbara Izquierdo Coronel, María Álvarez Bello and 12 more

Abstract readObservational Study
In one paragraph

Observational study in Clinical cardiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Review
  2. Review
  3. Review
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

22 authors.

María Jesús Espinosa PascualCardiology Department, Hospital Universitario Getafe, Getafe, Spain.ORCID http://orcid.org/0000-0002-2356-3848
Jose Antonio Carnicero CarreñoAging and Frailty Department, Fundación de Investigación Biomédica del Hospital Universitario de Getafe, Getafe, Spain.ORCID http://orcid.org/0000-0002-5537-9201
Mariam El AssarAging and Frailty Department, Fundación de Investigación Biomédica del Hospital Universitario de Getafe, Getafe, Spain.
Renee Olsen RodríguezCardiology Department, Hospital Universitario Getafe, Getafe, Spain.
Alfonso Fraile SanzCardiology Department, Hospital Universitario Getafe, Getafe, Spain.
Paula Rodriguez MontesCardiology Department, Hospital Universitario Getafe, Getafe, Spain.
Nuria Gil ManceboCardiology Department, Hospital Universitario Getafe, Getafe, Spain.
Alberto Sánchez FerrerAging and Frailty Department, Fundación de Investigación Biomédica del Hospital Universitario de Getafe, Getafe, Spain.
Bárbara Izquierdo CoronelCardiology Department, Hospital Universitario Getafe, Getafe, Spain.
María Álvarez BelloCardiology Department, Hospital Universitario Getafe, Getafe, Spain.
María Martín MuñozCardiology Department, Hospital Universitario Getafe, Getafe, Spain.
Verónica Cámara HernándezDepartment of Clinical Analysis, Hospital Universitario Getafe, Getafe, Spain.
Miguel de La Serna Real de AsuaCardiology Department, Hospital Universitario Getafe, Getafe, Spain.
Silvia Humanes YbañezCardiology Department, Hospital Universitario Getafe, Getafe, Spain.
Patricia Sosa CallejasAging and Frailty Department, Fundación de Investigación Biomédica del Hospital Universitario de Getafe, Getafe, Spain.
Miguel Gutierrez MuñozCardiology Department, Hospital Universitario Getafe, Getafe, Spain.
Rebeca Mata CaballeroCardiology Department, Hospital Universitario Getafe, Getafe, Spain.
Paula Awamleh GarciaCardiology Department, Hospital Universitario Getafe, Getafe, Spain.
Jesús Ángel Perea EgidoCardiology Department, Hospital Universitario Getafe, Getafe, Spain.ORCID http://orcid.org/0000-0001-9186-7002
Javier López PaisCardiology Department, Hospital Clínico Universitario Santiago de Compostela, A Coruña, Spain.
Leocadio Rodríguez MañasDepartment of Medicine, Faculty of Biomedical and Health Sciences, Universidad Europea de Madrid, Villaviciosa de Odón, Spain.
Joaquín Jesús Alonso MartínCardiology Department, Hospital Universitario Getafe, Getafe, Spain.

Funding

This study was supported the Instituto de Salud Hospital Universitario La Paz (IdiPAZ) and the Instituto de Salud Carlos III (PI24/02079).
6 · The paper itself

Abstract

aimsApproximately 10% of patients with myocardial infarction present with non-obstructive coronary arteries (MINOCA), whose characteristics differ from those with obstructive coronary lesions (MICAD). Inflammation plays a key role in myocardial infarction. This study aims to develop a biomarker-based index for accurate differentiation between MINOCA and MICAD.

methodsA prospective, observational cohort study including 111 patients admitted for myocardial infarction: 46 with MINOCA and 65 with MICAD. Blood samples were collected within the first 24 h to measure high-sensitivity C-reactive protein, interleukin-6, asymmetric dimethylarginine, and peak high-sensitivity troponin T. The association of these biomarkers with MICAD risk was analyzed using logistic regression. Scoring systems were developed using optimization algorithms to predict the diagnosis before coronary angiography, applied to both individual biomarkers and a combined index.

resultsPatients had a mean age of 67 years (SD 13.3), with a male predominance (68.5%). Higher levels of IL-6 and high-sensitivity troponin T were significantly associated with increased MICAD risk (OR: 1.58; 95% CI: 1.01-2.46, and OR: 2.27; 95% CI: 1.61-3.26, respectively). As score increases, interleukin-6 and high-sensitivity troponin T increase the likelihood of MICAD classification, while higher asymmetric dimethylarginine levels reduce it. Each one-point increase in the combined index multiplies MICAD risk by six (OR:6.16, 95%CI: 2.72-13.95; p < 0.001). While individual indexes improved the diagnostic performance of biomarkers, the combined index demonstrated superior accuracy (AUC: 0.918).

conclusionsA biomarker-based scoring system was developed, achieving superior discriminatory capacity for differentiating MINOCA from MICAD compared to the individual analysis of biomarkers in absolute values or independent indexes.

Indexed as

Coronary Artery DiseaseInflammation MediatorsInterleukin-6MINOCAMyocardial InfarctionTroponin TAgedArginineBiomarkersCoronary AngiographyC-Reactive ProteinFemaleHumansLogistic ModelsMaleMiddle AgedArginineBiomarkersC-Reactive ProteinIL6 protein, humanInflammation MediatorsInterleukin-6N,N-dimethylarginineTroponin Tbiomarkersdiagnosisendothelial dysfunctionindexinflammationMICADMINOCAmyocardial infarctionscore

Identifiers

PMID39967413
PMCPMC11836528

What Socratic holds

Textmetadata
LicenceCC BY
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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.