Evidence map›Paper›PMID 38166811›Full record

Observational studyBMC cardiovascular disorders2024

Cut-off value for interleukin-34 as an additional potential inflammatory biomarker for estimation of slow coronary flow risk.

Mehdi Karasu, Hasan Ata Bolayır

Abstract readObservational Study
In one paragraph

Observational study in BMC cardiovascular disorders, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

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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

6 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Article
  6. 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

2 authors.

Mehdi KarasuDepartment of Cardiology, Fethi Sekin Sehir Hastanesi, Elazıg, Turkey. mehdikarasu@yahoo.com.
Hasan Ata BolayırDepartment of Cardiology, Malatya Turgut Özal Üniversitesi Kardiyoloji ABD, Malatya, Turkey.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundInflammatory markers may provide insights into the underlying mechanisms of slow coronary flow (SCF), including subclinical atherosclerosis and endothelial dysfunction. Interleukin-34 (IL-34), known for its role in immuno-inflammatory diseases, might hold significance in SCF. We aimed to explore the potential association between IL-34 and SCF in patients undergoing diagnostic elective coronary angiography.

methodsThis observational, cross-sectional study enrolled 256 participants: 124 with SCF and 132 with normal coronary flow (NCF). All participants had undergone outpatient coronary angiography for suspected coronary artery disease. SCF assessment employed the TIMI frame count (TFC) for quantifying coronary flow rate.

resultsSCF patients exhibited significantly elevated TFC in all three major coronary arteries compared to controls (p < 0.05). IL-34 displayed a noteworthy positive correlation with average TFC [for all participants: r = 0.514, p < 0.001; for SCF patients: r = 0.526, p < 0.001; for normal controls: r = -0.288, p > 0.05]. Similarly, high-sensitivity C-reactive protein (hsCRP) showed a significant and positive relationship with average TFC [for all participants: r = 0.504, p < 0.001; for SCF patients: r = 0.558, p < 0.001; for normal controls: r = -0.148, p > 0.05]. SCF patients presented coronary arteries of larger size compared to controls.

conclusionMean coronary diameter and IL-34 emerged as independent predictors of SCF. Additionally, hsCRP, mean coronary diameter, and IL-34 exhibited a positive correlation with mean TFC values. IL-34 appears to be a more effective indicator than hsCRP in SCF patients.

Indexed as

Coronary CirculationC-Reactive ProteinBiomarkersBlood Flow VelocityCoronary AngiographyCross-Sectional StudiesHumansInterleukinsBiomarkersC-Reactive ProteinIL34 protein, humanInterleukinshsCRPIL-34Slow coronary flow (SCF)

Identifiers

PMID38166811
PMCPMC10762812

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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.