Evidence map›Paper›PMID 35837763›Full record

ArticleESC heart failure2022

Serum microRNAs are key predictors of long-term heart failure and cardiovascular death after myocardial infarction.

Luis M Rincón, Macarena Rodríguez-Serrano, Elisa Conde, Val F Lanza, Marcelo Sanmartín, Paz González-Portilla, Marta Paz-García, José Manuel Del Rey, Miriam Menacho, María-Laura García Bermejo and 1 more

Abstract read
In one paragraph

Article in ESC heart failure, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
25citing papers in PubMed, 2 pooled it
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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

25 citing papers in PubMed, 2 syntheses or guidelines pooled it.

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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

11 authors.

Luis M RincónDepartment of Cardiology, Hospital Universitario Ramón y Cajal, Universidad de Alcalá, Instituto Ramón y Cajal de Investigación Sanitaria (IRYCIS), Centro de Investigación Biomédica en Red de Enfermedades Cardiovasculares (CIBERCV), Madrid, 28034, Spain.ORCID 0000-0003-1819-5742
Macarena Rodríguez-SerranoBiomarkers and Therapeutic Targets Laboratory and Core Facility, Instituto Ramón y Cajal de Investigación Sanitaria (IRYCIS), Spanish Renal Research Network (REDinREN), Ctra. Colmenar Km 9100, Madrid, 28034, Spain.
Elisa CondeBiomarkers and Therapeutic Targets Laboratory and Core Facility, Instituto Ramón y Cajal de Investigación Sanitaria (IRYCIS), Spanish Renal Research Network (REDinREN), Ctra. Colmenar Km 9100, Madrid, 28034, Spain.
Val F LanzaBioinformatics Core Facility, Instituto Ramón y Cajal de Investigación Sanitaria (IRYCIS), Madrid, Spain.
Marcelo SanmartínDepartment of Cardiology, Hospital Universitario Ramón y Cajal, Universidad de Alcalá, Instituto Ramón y Cajal de Investigación Sanitaria (IRYCIS), Centro de Investigación Biomédica en Red de Enfermedades Cardiovasculares (CIBERCV), Madrid, 28034, Spain.
Paz González-PortillaDepartment of Cardiology, Hospital Universitario Ramón y Cajal, Universidad de Alcalá, Instituto Ramón y Cajal de Investigación Sanitaria (IRYCIS), Centro de Investigación Biomédica en Red de Enfermedades Cardiovasculares (CIBERCV), Madrid, 28034, Spain.
Marta Paz-GarcíaBiomarkers and Therapeutic Targets Laboratory and Core Facility, Instituto Ramón y Cajal de Investigación Sanitaria (IRYCIS), Spanish Renal Research Network (REDinREN), Ctra. Colmenar Km 9100, Madrid, 28034, Spain.
José Manuel Del ReyDepartment of Biochemistry, Hospital Universitario Ramón y Cajal, Universidad de Alcalá, Instituto Ramón y Cajal de Investigación Sanitaria (IRYCIS), Madrid, Spain.
Miriam MenachoDepartment of Biochemistry, Hospital Universitario Ramón y Cajal, Universidad de Alcalá, Instituto Ramón y Cajal de Investigación Sanitaria (IRYCIS), Madrid, Spain.
María-Laura García BermejoBiomarkers and Therapeutic Targets Laboratory and Core Facility, Instituto Ramón y Cajal de Investigación Sanitaria (IRYCIS), Spanish Renal Research Network (REDinREN), Ctra. Colmenar Km 9100, Madrid, 28034, Spain.
José L ZamoranoDepartment of Cardiology, Hospital Universitario Ramón y Cajal, Universidad de Alcalá, Instituto Ramón y Cajal de Investigación Sanitaria (IRYCIS), Centro de Investigación Biomédica en Red de Enfermedades Cardiovasculares (CIBERCV), Madrid, 28034, Spain.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPatients with acute myocardial infarction (MI) are at high risk of upcoming events, in particular heart failure (HF), but reliable stratification methods are lacking. Our goal was to evaluate the potential role of circulating miRNAs as prognostic biomarkers in patients presenting with MI. METHODS AND

resultsWe conducted a prospective study among 311 consecutive patients hospitalized with MI (65% ST-segment elevation MI & median age of 55 years) with long-term follow-up. An initial screening was conducted to select candidate miRNAs, with subsequent study of 14 candidate miRNAs. The primary outcome was the composite of hospital admission for HF or cardiovascular death. During a mean follow-up of 2.1 years miR-21-5p, miR-23a-3p, miR27b-3p, miR-122-5p, miR210-3p, and miR-221-3p reliably predicted the primary outcome. Multivariate Cox regression analyses highlighted that miR-210-3p [hazard ratio (HR) 2.65 per 1 SD increase, P < 0.001], miR-23a-3p (HR 2.11 per 1 SD increase, P < 0.001), and miR-221-3p (HR 2.03 per 1 SD increase, P < 0.001) were able to accurately predict the primary outcome, as well as cardiovascular death, HF hospitalizations, and long-term New York Heart Association (NYHA) functional class. These three miRNAs clearly improved the performance of multivariate clinical models: ΔC-statistic = 0.10 [95% confidence interval (CI), 0.03-0.17], continuous net reclassification index = 34.8% (95%CI, 5.8-57.4%), and integrated discrimination improvement (P < 0.001).

conclusionsThis is the largest study evaluating the prognostic value of circulating miRNAs for HF-related events among patients with MI. We show that several miRNAs predict HF hospitalizations, cardiovascular mortality, and poor long-term NYHA status and improve current risk prediction methods.

Indexed as

Circulating MicroRNAHeart FailureMicroRNAsMyocardial InfarctionBiomarkersHumansMiddle AgedProspective StudiesBiomarkersCirculating MicroRNAMicroRNAsBiomarkerHeart failureMicroRNAMyocardial infarctionPrognosis

Identifiers

PMID35837763
PMCPMC9715833

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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.