Development and validation of nomogram models to discriminate between acute aortic syndromes and non-S

Background: Blood-tes Methods: Data were retrospectively collected from 178 patients with AASs and 460 patients with NSTEMI within 3 h of onset. Differential risk factors related to AASs were identified by univariate and multivariate logistic regression analyses for patients with onset <2 h and onset ≥2 h, respectively, in the cardiac troponin (cTn) cohort. Nomograms were established in the cTn cohort as a training set and validated in the high-sensitivity cTn cohort. To assess the utility of the models in clinical practice, decision curve analyses were performed. Results: D-dimer, fibrinogen, and age were identified as differential risk factors for AASs with the onset of <2 h. D-dimer at an optimal cutoff level of 281 ng/mL for AASs had a sensitivity of 86.4% and a specificity of 91.3%. A nomogram was developed and validated with areas under the curve (AUC) of 0.934 (95% CI: 0.880-0.988) and 0.952 (95% CI: 0.874-1.000), respectively. D-dimer, neutrophil, bilirubin, and platelet were the differential risk factors for AASs with the onset of ≥2 h. D-dimer at an optimal cutoff level of 385 ng/mL has a sensitivity of 91.8% and a specificity of 91.3%. The AUC of the second nomogram in the training set and the validation set were 0.965 (95% CI: 0.942-0.988) and 0.974 (95% CI: 0.944-1.000), respectively. Conclusion: Time-dependent quality of D-dimer should be considered for discriminating AASs from NSTEMI. Both nomogram models may have a clinical utility for evaluating the probability of AASs.