Improving Prediction of Postoperative Atrial Fibrillation After Cardiac Surgery Using Multiple Pathophysiological Biomarkers: A Prospective Double-Centre Study

Peter G. Noordzij*, Maaike S.Y. Thio, Ted Reniers, Ineke Dijkstra, Gabriele Mondelli, Marloes Langelaan, Henk J.T. Ruven, Thijs C.D. Rettig

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

Background: Postoperative atrial fibrillation (POAF) is a common and serious complication after cardiac surgery. Existing clinical prediction models show limited discriminative ability. We hypothesize that incorporating biomarkers that reflect key pathophysiological pathways of POAF can enhance preoperative risk stratification. Methods: Adult cardiac surgery patients without a history of atrial fibrillation from the BIGPROMISE cohort—a prospective, observational, two-centre perioperative biobank study—were included to investigate whether biomarkers of myocardial injury, systemic inflammation, haematological status, and metabolic and neuroendocrine dysregulation improved prediction of new-onset POAF when compared with an established clinical model, the POAF Score. We evaluated the incremental value of a 13-biomarker panel added to the POAF Score using multivariable logistic regression with shrinkage (lasso), assessing model discrimination, calibration, reclassification, and net clinical benefit. Results: Among 959 cardiac surgery patients, POAF occurred in 35% (n = 339). Inflammatory, metabolic, and neuro-endocrine biomarkers remained independently associated with POAF after applying lasso regression. Adding these biomarkers to the POAF Score improved discrimination, with the C-statistic increasing from 0.60 (95% CI: 0.60–0.60) to 0.63 (95% CI: 0.63–0.64; p < 0.01). Calibration was good in both models. At a threshold of 40% for high risk of POAF, the addition of biomarkers correctly reclassified 16% of patients with POAF as high risk. However, only 2% of the patients without POAF were reclassified as low risk, while 13% were incorrectly reclassified as high risk, resulting in a net reclassification index of 0.05. Conclusions: The addition of pathophysiological biomarkers significantly improves the performance of an established risk model for POAF after cardiac surgery, although the incremental clinical benefit is small.

Original languageEnglish
Article number3737
Number of pages11
JournalJournal of Clinical medicine
Volume14
Issue number11
DOIs
Publication statusPublished - Jun 2025

Keywords

  • atrial fibrillation
  • biomarkers
  • cardiac surgery
  • risk stratification

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