International Journal of Molecular Sciences (Nov 2022)

Circulating Levels of Ferritin, RDW, PTLs as Predictive Biomarkers of Postoperative Atrial Fibrillation Risk after Cardiac Surgery in Extracorporeal Circulation

  • Claudia Altieri,
  • Calogera Pisano,
  • Labriola Vincenzo,
  • Maria Sabrina Ferrante,
  • Valentina Pellerito,
  • Paolo Nardi,
  • Carlo Bassano,
  • Dario Buioni,
  • Ernesto Greco,
  • Giovanni Ruvolo,
  • Carmela Rita Balistreri

DOI
https://doi.org/10.3390/ijms232314800
Journal volume & issue
Vol. 23, no. 23
p. 14800

Abstract

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Postoperative atrial fibrillation (POAF) is the most common arrhythmia after cardiac surgery in conventional extracorporeal circulation (CECC), with an incidence of 15–50%. The POAF pathophysiology is not known, and no blood biomarkers exist. However, an association between increased ferritin levels and increased AF risk, has been demonstrated. Based on such evidence, here, we evaluated the effectiveness of ferritin and other haematological parameters as POAF risk biomarkers in patients subjected to cardiac surgery. We enrolled 105 patients (mean age = 70.1 ± 7.1 years; 70 men and 35 females) with diverse heart pathologies and who were subjected to cardiothoracic surgery. Their blood samples were collected and used to determine hematological parameters. Electrocardiographic and echocardiographic parameters were also evaluated. The data obtained demonstrated significantly higher levels of serum ferritin, red cell distribution width (RDW), and platelets (PLTs) in POAF patients. However, the serum ferritin resulted to be the independent factor associated with the onset POAF risk. Thus, we detected the ferritin cut-off value, which, when ≥148.5 ng/mL, identifies the subjects at the highest POAF risk, and with abnormal ECG atrial parameters, such as PW indices, and altered structural heart disease variables. Serum ferritin, RDW, and PTLs represent predictive biomarkers of POAF after cardiothoracic surgery in CECC; particularly, serum ferritin combined with anormal PW indices and structural heart disease variables can represent an optimal tool for predicting not only POAF, but also the eventual stroke onset.

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