Thromboinflammation and hemostatic activation drive early mortality risk in pulmonary embolism.

Background: Despite advances in diagnosis and treatment, pulmonary embolism (PE) remains a challenging condition with high mortality. Current prognostic models lack integration of the biological underpinnings driving adverse outcomes. Objectives: This study profiles thromboinflammation and hemostatic biomarkers in patients with PE to evaluate their association with 30-day mortality. Methods: In a prospective-specimen collection, retrospective-blinded evaluation study, plasma samples from 500 patients collected at time of diagnosis were analyzed. Biomarkers reflecting endothelial dysfunction, platelet activation, coagulation imbalance, impaired fibrinolysis, and inflammation were quantified. Hematological indices (neutrophil-to-lymphocyte ratio [NLR], platelet-to-lymphocyte ratio [PLR], and systemic immune-inflammation index [SII]) were calculated. Receiver operating characteristics analysis, multivariable logistic regression, and Chi-square automatic interaction detection (CHAID) recursive partitioning tree were used to assess predictors of mortality. Results: Of 500 patients (median age, 64 years; 52% males), 48 (9.7%) died within 30 days. Levels of von Willebrand factor, P-selectin, tissue factor, tissue-type plasminogen activator, plasminogen activator inhibitor (PAI)-1, D-dimer, C-reactive protein, interleukin 6, tumor necrosis factor (TNF)-α, NLR, PLR, and SII were significantly higher, while FVII, FX, FXIIIA, and thrombin-activatable fibrinolysis inhibitor levels were significantly lower in 30-day nonsurvivors. Multivariable analysis revealed that elevated von Willebrand factor, E-selectin, tissue factor, tissue-type plasminogen activator, PAI-1, D-dimer, C-reactive protein, interleukin 6, TNF-α, and NLR, and decreased FVII, FX, FXIIIA, and TAFI levels, were independently associated with 30-day mortality. Chi-squared automatic interaction detection analysis identified elevated NLR, PAI-1, and TNF-α as key predictors of mortality. Conclusion: Current PE scoring systems have a low positive predictive value for clinical deterioration and mortality. This study uniquely integrates endothelial, platelet, coagulation, fibrinolytic, inflammatory, and hematologic biomarkers to identify novel mortality-predictive thresholds, highlighting the value of thromboinflammation, and hemostatic activation biomarkers associated with the pathobiology of PE for enhancing risk stratification of patients with PE.