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Development and validation of nomogram models to discriminate between acute aortic syndromes and non-ST-elevation myocardial infarction during troponin-blind period

BACKGROUND: Blood-test-based methods of distinguishing between acute aortic syndromes (AASs) and non-ST-elevation myocardial infarction (NSTEMI) during the troponin-blind period of <2–3 h of symptom onset have not been studied previously. We aimed to explore whether routine biomarkers might facil...

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Detalles Bibliográficos
Autores principales: Tong, Fei, Wang, Yue, Sun, Zhijun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9895376/
https://www.ncbi.nlm.nih.gov/pubmed/36742067
http://dx.doi.org/10.3389/fcvm.2023.1077712
Descripción
Sumario:BACKGROUND: Blood-test-based methods of distinguishing between acute aortic syndromes (AASs) and non-ST-elevation myocardial infarction (NSTEMI) during the troponin-blind period of <2–3 h of symptom onset have not been studied previously. We aimed to explore whether routine biomarkers might facilitate differential diagnosis. 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.