Diagnostic and discriminative value of inflammatory biomarkers in differentiating aortic aneurysm and dissection: A retrospective comparative study

炎症生物标志物在鉴别主动脉瘤和主动脉夹层中的诊断和鉴别价值:一项回顾性比较研究

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Abstract

Aortic dissection (AD) and aortic aneurysm (AA) are acute aortic syndromes associated with high mortality, requiring rapid recognition and accurate differentiation from each other and from healthy individuals. While imaging remains the diagnostic gold standard, hematological indices and inflammatory biomarkers may provide fast and accessible adjunctive tools in emergency settings. This retrospective comparative study, conducted at 2 tertiary centers, included 576 participants after exclusions: 213 patients with AD, 178 with AA, and 185 healthy controls. Demographic, clinical, and laboratory data were collected at admission. Hematological indices, including the neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio, platelet-to-neutrophil ratio, derived NLR (dNLR), systemic immune-inflammation index, fibrinogen-to-C-reactive protein ratio, and fibrinogen-to-d-dimer ratio, together with conventional inflammatory markers such as C-reactive protein, fibrinogen, and d-dimer, were analyzed. Receiver operating characteristic curve analysis and multivariable logistic regression were used to assess diagnostic performance. Compared with controls, patients with AD and AA exhibited significantly higher inflammatory indices (all P < .001). Neutrophil-to-lymphocyte ratio showed the highest diagnostic accuracy in distinguishing AD from controls (area under the curve [AUC] = 0.933, sensitivity 90.1%, specificity 89.7%), whereas platelet-to-neutrophil ratio and systemic immune-inflammation index also demonstrated considerable discriminative ability. For AA versus controls, NLR (AUC = 0.846) and platelet-to-neutrophil ratio (AUC = 0.838) were the most predictive parameters. For AD versus AA, fibrinogen-to-d-dimer ratio exhibited the best performance (AUC = 0.898, sensitivity 77.0%, specificity 83.7%). Multivariable logistic regression models combining clinical factors such as hypertension, sex, diabetes, and coronary artery disease with hematological indices achieved excellent discrimination (AUCs = 0.938 for AD vs controls, 0.870 for AA vs controls, and 0.944 for AD vs AA). Simple hematological ratios, particularly NLR and the novel fibrinogen-to-d-dimer ratio index, provide strong diagnostic and discriminative value in acute aortic syndromes. Integrating these biomarkers with clinical risk factors may enhance early triage and differential diagnosis, especially when advanced imaging modalities are delayed or unavailable.

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