Simple Death Risk Models to Predict In-hospital Outcomes in Acute Aortic Dissection in Emergency Department - Xing, Lingyu; Zhou, Yannan; Han, Yi; Chen, Chen; Dong, Zegang; Zheng, Xinde; Chen, Dongxu; Yu, Yao; Liao, Fengqing; Guo, Shuai; Yao, Chenling; Tang, Min; et al. (Frontiers in Medicine, 2022)
Objective: We sought to find a bedside prognosis prediction model based on clinical and image parameters to determine the in-hospital outcomes of AAD in ED. Methods: Patients presented with AAD from January 2010 to December 2020 were recruited in our derivation and validation cohort. We collected the demographics, medical history, treatment option and in-hospital outcomes. All enrolled patients underwent computed tomography angiography (CTA). The image data were reviewed for anatomic criteria in a retrospective fashion systematically by three professional radiologists, then a series of radiological parameters including the extent of dissection, the site of the intimal tear, entry tear (ET) diameter, aortic diamater at each level, maximum false lumen diameter (MFL), and presence of pericardial effusion were collected. Results: Of the 449 patients in the derivation cohort, 345 (76.8 %) were male, the mean age was 61 years, and 298 (66.4 %) had a history of hypertension. Surgical repair was performed in 327 (72.8 %) cases in derivation cohort, and the overall crude in-hospital mortality of AAD was 10.9 %. Age, Marfan syndrome, type A AAD, surgical repair, MFL diameter and pericardial effusion were independent predictors of mortality in AAD. A nomogram incorporating these six predictors showed good calibration and discrimination in the derivation and validation cohorts. As for type A AAD, 3-Level Type A Aortic Dissection Clinical Prognosis Score (3ADPS) including 5 clinical and image variables scored from -2 to 5 was established: (1) moderate risk of death if 3ADPS is less than 0; (2) high risk of death if 3ADPS is 1 to 2; (3) very high risk of death if 3ADPS is more than 3. In the validation cohorts, the area under the receiver operator characteristic curves was 0.833 (95% CI, 0.700 to 0.967). Conclusion: Age, Marfan syndrome, type A AAD, surgical repair, MFL diameter and pericardial effusion can significantly affect the in-hospital outcomes of AAD. And 3ADPS contributes to the prediction of in-hospital prognosis of typeA AAD rapidly and effctively. As multivariable risk prediction tools, the risk models were easily available for emergency doctors to predict in-hospital mortality of AAD patients in extreme clinical risk.