Literature DB >> 31952855

Noninvasive biomarker-based risk stratification for development of new onset atrial fibrillation after coronary artery bypass surgery.

Farhan Rizvi1, Mahek Mirza2, Susan Olet3, Melissa Albrecht4, Stacie Edwards2, Larisa Emelyanova2, David Kress5, Gracious R Ross2, Ekhson Holmuhamedov2, A Jamil Tajik5, Bijoy K Khandheria5, Arshad Jahangir6.   

Abstract

BACKGROUND: Postoperative atrial fibrillation (PoAF) is a common complication after cardiac surgery. A pre-existing atrial substrate appears to be important in postoperative development of dysrhythmia, but its preoperative estimation is challenging. We tested the hypothesis that a combination of clinical predictors, noninvasive surrogate markers for atrial fibrosis defining abnormal left atrial (LA) mechanics, and biomarkers of collagen turnover is superior to clinical predictors alone in identifying patients at-risk for PoAF.
METHODS: In patients without prior AF undergoing coronary artery bypass grafting, concentrations of biomarkers reflecting collagen synthesis and degradation, extracellular matrix, and regulatory microRNA-29s were determined in serum from preoperative blood samples and correlated to atrial fibrosis extent, alteration in atrial deformation properties determined by 3D speckle-tracking echocardiography, and AF development.
RESULTS: Of 90 patients without prior AF, 34 who developed PoAF were older than non-PoAF patients (72.04 ± 10.7 y; P = 0.043) with no significant difference in baseline comorbidities, LA size, or ventricular function. Global (P = 0.007) and regional longitudinal LA strain and ejection fraction (P = 0.01) were reduced in PoAF vs. non-PoAF patients. Preoperative amino-terminal-procollagen-III-peptide (PIIINP) (103.1 ± 39.7 vs. 35.1 ± 19.3; P = 0.041) and carboxy-terminal-procollagen-I-peptide levels were elevated in PoAF vs. non-PoAF patients with a reduction in miR-29 levels and correlated with atrial fibrosis extent. Combining age as the only significant clinical predictor with PIIINP and miR-29a provided a model that identified PoAF patients with higher predictive accuracy.
CONCLUSIONS: In patients without a previous history of AF, using age and biomarkers of collagen synthesis and regulation, a noninvasive tool was developed to identify those at risk for new-onset PoAF.
Copyright © 2020 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Aging; Atrial fibrillation; Biomarkers; Fibrosis; MiR-29; Speckle-tracking echocardiography

Mesh:

Substances:

Year:  2020        PMID: 31952855      PMCID: PMC8011128          DOI: 10.1016/j.ijcard.2019.12.067

Source DB:  PubMed          Journal:  Int J Cardiol        ISSN: 0167-5273            Impact factor:   4.164


  40 in total

Review 1.  Value of plasma brain natriuretic peptide levels for predicting postoperative atrial fibrillation: a systemic review and meta-analysis.

Authors:  Guo-Long Cai; Jin Chen; Cai-Bao Hu; Mo-Lei Yan; Qiang-Hong Xu; Jing Yan
Journal:  World J Surg       Date:  2014-01       Impact factor: 3.352

2.  The persistent problem of new-onset postoperative atrial fibrillation: a single-institution experience over two decades.

Authors:  Jeanne Shen; Shelly Lall; Victoria Zheng; Patricia Buckley; Ralph J Damiano; Richard B Schuessler
Journal:  J Thorac Cardiovasc Surg       Date:  2011-02       Impact factor: 5.209

Review 3.  Atrial fibrillation: current knowledge and future directions in epidemiology and genomics.

Authors:  Jared W Magnani; Michiel Rienstra; Honghuang Lin; Moritz F Sinner; Steven A Lubitz; David D McManus; Josée Dupuis; Patrick T Ellinor; Emelia J Benjamin
Journal:  Circulation       Date:  2011-11-01       Impact factor: 29.690

4.  Left atrial reservoir function predicts atrial fibrillation recurrence after catheter ablation: a two-dimensional speckle strain study.

Authors:  Mahek Mirza; Giuseppe Caracciolo; Uzma Khan; Naoyo Mori; Samir K Saha; Komandoor Srivathsan; Gregory Altemose; Luis Scott; Partho Sengupta; Arshad Jahangir
Journal:  J Interv Card Electrophysiol       Date:  2011-03-22       Impact factor: 1.900

5.  Atrial fibrillation and plasma troponin I elevation after cardiac surgery: relation to inflammation-associated parameters.

Authors:  Boris Knayzer; Dan Abramov; Bilenko Natalia; David Tovbin; Amir Ganiel; Amos Katz
Journal:  J Card Surg       Date:  2007 Mar-Apr       Impact factor: 1.620

6.  Left atrial strain and strain rate in patients with paroxysmal and persistent atrial fibrillation: relationship to left atrial structural remodeling detected by delayed-enhancement MRI.

Authors:  Suman S Kuppahally; Nazem Akoum; Nathan S Burgon; Troy J Badger; Eugene G Kholmovski; Sathya Vijayakumar; Swati N Rao; Joshua Blauer; Eric N Fish; Edward V R Dibella; Rob S Macleod; Christopher McGann; Sheldon E Litwin; Nassir F Marrouche
Journal:  Circ Cardiovasc Imaging       Date:  2010-02-04       Impact factor: 7.792

7.  A multicenter risk index for atrial fibrillation after cardiac surgery.

Authors:  Joseph P Mathew; Manuel L Fontes; Iulia C Tudor; James Ramsay; Peter Duke; C David Mazer; Paul G Barash; Ping H Hsu; Dennis T Mangano
Journal:  JAMA       Date:  2004-04-14       Impact factor: 56.272

8.  Extracellular matrix alterations in patients with paroxysmal and persistent atrial fibrillation: biochemical assessment of collagen type-I turnover.

Authors:  Eleftherios M Kallergis; Emmanuel G Manios; Emmanuel M Kanoupakis; Hercules E Mavrakis; Dimitris A Arfanakis; Niki E Maliaraki; Chrisovalantis E Lathourakis; Gregory I Chlouverakis; Panos E Vardas
Journal:  J Am Coll Cardiol       Date:  2008-07-15       Impact factor: 24.094

Review 9.  Post-operative atrial fibrillation: a maze of mechanisms.

Authors:  Bart Maesen; Jan Nijs; Jos Maessen; Maurits Allessie; Ulrich Schotten
Journal:  Europace       Date:  2011-08-06       Impact factor: 5.214

10.  Galectin-3 as a marker of interstitial atrial remodelling involved in atrial fibrillation.

Authors:  Diana Hernández-Romero; Juan Antonio Vílchez; Álvaro Lahoz; Ana I Romero-Aniorte; Eva Jover; Arcadio García-Alberola; Rubén Jara-Rubio; Carlos M Martínez; Mariano Valdés; Francisco Marín
Journal:  Sci Rep       Date:  2017-01-12       Impact factor: 4.379

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  6 in total

Review 1.  RNAs and Gene Expression Predicting Postoperative Atrial Fibrillation in Cardiac Surgery Patients Undergoing Coronary Artery Bypass Grafting.

Authors:  Muhammad Shuja Khan; Kennosuke Yamashita; Vikas Sharma; Ravi Ranjan; Derek James Dosdall
Journal:  J Clin Med       Date:  2020-04-16       Impact factor: 4.241

Review 2.  Molecular Mechanisms, Diagnostic Aspects and Therapeutic Opportunities of Micro Ribonucleic Acids in Atrial Fibrillation.

Authors:  Allan Böhm; Marianna Vachalcova; Peter Snopek; Ljuba Bacharova; Dominika Komarova; Robert Hatala
Journal:  Int J Mol Sci       Date:  2020-04-15       Impact factor: 5.923

3.  Comprehensive analysis of the ceRNA network in coronary artery disease.

Authors:  Weikang Bian; Xiao-Xin Jiang; Zhicheng Wang; Yan-Rong Zhu; Hongsong Zhang; Xiaobo Li; Zhizhong Liu; Jing Xiong; Dai-Min Zhang
Journal:  Sci Rep       Date:  2021-12-20       Impact factor: 4.379

Review 4.  Strain Echocardiography to Predict Postoperative Atrial Fibrillation.

Authors:  Francisco Javier Sánchez; Esther Pueyo; Emiliano Raúl Diez
Journal:  Int J Mol Sci       Date:  2022-01-25       Impact factor: 5.923

Review 5.  Diagnostic and Prognostic Value of miRNAs after Coronary Artery Bypass Grafting: A Review.

Authors:  Ewelina Błażejowska; Tomasz Urbanowicz; Aleksandra Gąsecka; Anna Olasińska-Wiśniewska; Miłosz J Jaguszewski; Radosław Targoński; Łukasz Szarpak; Krzysztof J Filipiak; Bartłomiej Perek; Marek Jemielity
Journal:  Biology (Basel)       Date:  2021-12-19

Review 6.  Circulating MicroRNAs as Novel Biomarkers in Risk Assessment and Prognosis of Coronary Artery Disease.

Authors:  Chiara Vavassori; Eleonora Cipriani; Gualtiero Ivanoe Colombo
Journal:  Eur Cardiol       Date:  2022-03-07
  6 in total

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