Evidence map›Paper›PMID 40436930›Full record

ArticleScientific reports2025

MicroRNA signature predicts post operative atrial fibrillation after coronary artery bypass grafting.

Srinivasulu Yerukala Sathipati, Tonia Carter, Deepa Soodi, Nwaedozie Somto, Sanjay K Shukla, John Petronovich, Glurich Ingrid, John Braxton, Param Sharma

Abstract read
In one paragraph

Article in Scientific reports, 2025. 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

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

6 citing papers in PubMed.

  1. Review
  2. Review
  3. Review
  4. Circulating miR-10b-5p as a candidate biomarker of atrial fibrillation recurrence after catheter ablation: a two-phase translational study.Europace : European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of Cardiology · 2026
    Article
  5. Review
  6. 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

9 authors.

Srinivasulu Yerukala SathipatiCenter for Precision Medicine Research, Marshfield Clinic Research Institute, Marshfield, WI, 54449, USA. sathipathi.srinivasulu@marshfieldclinic.org.
Tonia CarterCenter for Precision Medicine Research, Marshfield Clinic Research Institute, Marshfield, WI, 54449, USA.
Deepa SoodiDepartment of Cardiology, Marshfield Clinic Health System, Marshfield, WI, 54449, USA.
Nwaedozie SomtoDepartment of Cardiology, Marshfield Clinic Health System, Marshfield, WI, 54449, USA.
Sanjay K ShuklaCenter for Precision Medicine Research, Marshfield Clinic Research Institute, Marshfield, WI, 54449, USA.
John PetronovichDepartment of Cardiology, Marshfield Clinic Health System, Marshfield, WI, 54449, USA.
Glurich IngridIntegrated Research and Development Laboratory, Marshfield Clinic Research Institute, Marshfield, WI, 54449, USA.
John BraxtonDepartment of Cardiology, Marshfield Clinic Health System, Marshfield, WI, 54449, USA.
Param SharmaDepartment of Cardiology, Marshfield Clinic Health System, Marshfield, WI, 54449, USA. sharma.param@marshfieldclinic.org.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Early detection of atrial fibrillation (AFib) is crucial for altering its natural progression and complication profile. Traditional demographic and lifestyle factors often fail as predictors of AFib. This study investigated pre-operative, circulating microRNAs (miRNAs) as potential biomarkers for post-operative AFib (POAF) in patients undergoing coronary artery bypass grafting (CABG). We used an array polymerase chain reaction method to detect pre-operative, circulating miRNAs in seven patients who subsequently developed POAF after CABG (cases) and eight patients who did not develop POAF after CABG (controls). The top 10 miRNAs from 84 candidates were selected and assessed for their performance in predicting POAF using machine learning models, including Random Forest, K-Nearest Neighbors (KNN), XGBoost, and Support Vector Machine (SVM). The Random Forest and XGBoost models showed superior predictive performance, with test area under the curve (AUC) values of 0.76 and 0.83, respectively. Differential expression analysis revealed four upregulated miRNAs-hsa-miR-96-5p, hsa-miR-184, hsa-miR-17-3p, and hsa-miR-200-3p-that overlapped with the POAF-miRNA signature. The POAF-miRNA signature was significantly associated with various cardiovascular diseases, including acute myocardial infarction, hypertrophic cardiomyopathy, and heart failure. Biological pathway analysis indicated these miRNAs target key signaling pathways involved in cardiovascular pathology, such as the MAPK, PI3K-Akt, and TGF-beta signaling pathways. The identified miRNAs demonstrate significant potential as predictive biomarkers for AFib post-CABG, implicating critical cardiovascular pathways and highlighting their role in POAF development and progression. These findings suggest that miRNA signatures could enhance predictive accuracy for POAF, offering a novel, noninvasive approach to early detection and personalized management of this condition.

Indexed as

Atrial FibrillationCoronary Artery BypassMicroRNAsPostoperative ComplicationsAgedBiomarkersFemaleGene Expression ProfilingHumansMachine LearningMaleMiddle AgedBiomarkersMicroRNAs

Identifiers

PMID40436930
PMCPMC12119944

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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.