Sepsis-induced coagulopathy is associated with new episodes of atrial fibrillation in patients admitted to critical care in sinus rhythm

Sandra Ortega-Martorell; Ivan Olier; Brian W Johnston; Ingeborg D Welters

doi:10.3389/fmed.2023.1230854

Sepsis-induced coagulopathy is associated with new episodes of atrial fibrillation in patients admitted to critical care in sinus rhythm

Front Med (Lausanne). 2023 Sep 15:10:1230854. doi: 10.3389/fmed.2023.1230854. eCollection 2023.

Authors

Sandra Ortega-Martorell^{1

2}, Ivan Olier^{1

2}, Brian W Johnston^{2

3

4}, Ingeborg D Welters^{2

3

4}

Affiliations

¹ School of Computer Science and Mathematics, Liverpool John Moores University, Liverpool, United Kingdom.
² Liverpool Centre for Cardiovascular Science, Liverpool, United Kingdom.
³ Institute of Life Course and Medical Sciences, University of Liverpool, Liverpool, United Kingdom.
⁴ Liverpool University Hospitals NHS Foundation Trust, Liverpool, United Kingdom.

Abstract

Background: Sepsis is a life-threatening disease commonly complicated by activation of coagulation and immune pathways. Sepsis-induced coagulopathy (SIC) is associated with micro- and macrothrombosis, but its relation to other cardiovascular complications remains less clear. In this study we explored associations between SIC and the occurrence of atrial fibrillation (AF) in patients admitted to the Intensive Care Unit (ICU) in sinus rhythm. We also aimed to identify predictive factors for the development of AF in patients with and without SIC.

Methods: Data were extracted from the publicly available AmsterdamUMCdb database. Patients with sepsis and documented sinus rhythm on admission to ICU were included. Patients were stratified into those who fulfilled the criteria for SIC and those who did not. Following univariate analysis, logistic regression models were developed to describe the association between routinely documented demographics and blood results and the development of at least one episode of AF. Machine learning methods (gradient boosting machines and random forest) were applied to define the predictive importance of factors contributing to the development of AF.

Results: Age was the strongest predictor for the development of AF in patients with and without SIC. Routine coagulation tests activated Partial Thromboplastin Time (aPTT) and International Normalized Ratio (INR) and C-reactive protein (CRP) as a marker of inflammation were also associated with AF occurrence in SIC-positive and SIC-negative patients. Cardiorespiratory parameters (oxygen requirements and heart rate) showed predictive potential.

Conclusion: Higher INR, elevated CRP, increased heart rate and more severe respiratory failure are risk factors for occurrence of AF in critical illness, suggesting an association between cardiac, respiratory and immune and coagulation pathways. However, age was the most dominant factor to predict the first episodes of AF in patients admitted in sinus rhythm with and without SIC.

Keywords: Sepsis-induced coagulopathy; atrial fibrillation; coagulopathy; database analysis; machine learning; sepsis.

Grants and funding

IW was an employee of the University of Liverpool. BJ was an employee of Liverpool University Hospitals NHS Foundation Trust. SO-M and IO were employed by the Liverpool John Moores University.