Prognostic prediction of long-term survival in patients with type A aortic dissection undergoing surgical repair: development of a novel prognostic index - Hao Cai; Yue Shao; Zheng-Hao Li; Xuan-Yu Liu; Xiao-Zhao Zhao; Chang-Ying Li; Hao-Yu Ran; Rui-Qin Zhou; Hao-Ming Shi; Sun Shuangling; Chang-Zhu Duan; Qing-Chen Wu; et al. (BMC Cardiovascular Disorders)
Abstract Background This study developed and investigated the prognostic significance of a comprehensive biomarker for postoperative type A aortic dissection (TAAD) patients. Methods A retrospective cohort of 175 TAAD patients who underwent open surgery at the First Affiliated Hospital of Chongqing Medical University, China, between September 2017 to December 2020, was included in the analysis. The least absolute shrinkage and selection operator (LASSO) method was employed to select indicators, thereby constructing a comprehensive biomarker, termed the comprehensive physiological response indicator (CPRI). The prognostic significance of the CPRI was assessed employing the Kaplan-Meier method and log-rank test. Univariate and multivariate Cox regression model were applied to identify independent prognostic factors for TAAD. A prognostic nomogram was constructed based on the CPRI and other nine blood and clinical indicators. The predictive performance of prognostic models and individual indicators was evaluated by determining the area under the curve (AUC) of the receiver operating characteristic (ROC) analysis. Results A comprehensive prognostic biomarker (CPRI) was developed, incorporating cardiac troponin T (cTnT), red blood cell count (RBC), white blood cell count (WBC), absolute neutrophil count (ANC), and absolute lymphocyte count (ALC). In the cohort of type A aortic dissection (TAAD) patients who underwent open surgery, those with lower preoperative CPRI values exhibited significantly poorer overall survival, with a HR of 2.325 (95% CI: 1.126–4.802) in a multivariate Cox regression analysis. The CPRI was identified as an independent prognostic factor for TAAD patients. Additionally, a nomogram constructed based on the CPRI demonstrated superior predictive accuracy compared to other models, with an area under the curve (AUC) of 0.874 versus 0.592, 0.514, and 0.577 for the respective models. Conclusion Our study suggested that CPRI may be a useful comprehensive prognostic biomarker for predicting the long-term survival of TAAD patients. The nomogram based on CPRI can be considered a valuable tool to identify high risk TAAD patients with poor prognosis.