The combined use of serum Raman spectroscopy and D dimer testing for the early diagnosis of acute aortic dissection.

Objectives: Acute aortic dissection (AAD) is an extremely life-threatening medical emergency, often misdiagnosed in its early stages, resulting in prolonged wait times for rescue. This study aims to identify potential serum biomarkers that can assist in the accurate diagnosis of AAD and effectively differentiate it from other conditions causing severe chest pain. Methods: A total of 122 patients with AAD and 129 patients with other severe chest pain disorders were included in the study. Serum samples were analyzed by measuring the peak intensities of Raman spectra. For each measurement, the Raman spectrum was accumulated by two accumulations (3 s per acquisition). Logistic regression and nomogram models were developed using these peak intensities as well as D-dimer levels to predict the occurrence of AAD. The clinical utilities of these models were assessed through receiver operating characteristics (ROC) curve analysis, net reclassification improvement (NRI), integrated discrimination improvement (IDI), and decision curve analysis (DCA) in both training and internal test cohorts. Results: The D-dimer levels of AAD patients were significantly increased, as well as higher intensities at specific Raman peaks, including 505 cm Conclusions: The employment of this combination of eight potential predictors effectively rules out AAD to a greater extent. This study presents a promising diagnostic strategy for early detection using optical diagnostic techniques such as Raman spectroscopy.