Abstract

Background

Patients with atrial fibrillation (AF) face an elevated risk of pulmonary embolism (PE), yet existing prediction tools demonstrate limited accuracy.

Objectives

This study aimed to develop and validate a novel predictive model integrating thromboelastography (TEG) parameters with conventional coagulation markers for PE risk assessment in AF patients.

Methods

We conducted a retrospective study of 271 hospitalized AF patients who underwent CTPA for suspected PE (41 with PE, 230 without). The mean age was 76.5 years, 56.5% were male, and hypertension was the most common comorbidity (67.5%). PE diagnosis was confirmed by computed tomography pulmonary angiography. Baseline characteristics, TEG parameters (including reaction time, maximum amplitude [MA], and α-angle), and standard coagulation markers (D-dimer, fibrinogen) were analyzed. Statistical significance was defined as a two-sided P-value < 0.05. Multivariate logistic regression identified independent predictors, which were incorporated into a nomogram. Model performance was evaluated using receiver operating characteristic (ROC) analysis, calibration curves, and decision curve analysis (DCA).

Results

The prevalence of PE was 15.1%. Patients with PE exhibited significantly higher TEG-MA, D-dimer, and fibrinogen levels compared to the non-PE group (all P<0.05). Multivariate analysis identified these three markers as independent predictors. The nomogram demonstrated excellent discrimination (AUC=0.878, 95% CI:0.806-0.949), with 87.8% sensitivity and 78.0% specificity at the optimal cutoff. The model showed good calibration (Hosmer-Lemeshow p=0.965) and significant clinical utility.

Conclusion

The TEG-based nomogram combining MA, D-dimer, and fibrinogen provides accurate, bedside-accessible PE risk stratification for AF patients. This tool may facilitate early identification of high-risk individuals and guide clinical decision-making regarding anticoagulation therapy. Further prospective studies are warranted to validate these findings.