主动脉夹层修复术后死亡危险因素探究及死亡预测模型构建

doi:10.3969/j.issn.1006-6233.2025.04.019

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Abstract Objective: To explore the risk factors affecting postoperative mortality in patients with Stanford type A acute aortic dissection (ATAAD) and to construct a nomogram prediction model. Methods: A retrospective analysis was conducted on 245 ATAAD patients who underwent surgical treatment at the First Affiliated Hospital with Nanjing Medical University from January 2019 to December 2022,with a maximum follow-up period of 65 months.Clinical data were recorded,and patients were divided into a survival group and a death group based on mortality during follow-up.The COX proportional hazards model was used to screen potential prognostic factors,and a nomogram prediction model was constructed.The predictive value of the model was analyzed using calibration curves and receiver operating characteristic (ROC) curves. Results: After follow-up,46 patients (18.77%) died,and 199 patients (81.22%) survived.The median time to death in the death group was 29 months (follow-up range:0–65 months).Univariate analysis identified 22 variables associated with postoperative mortality in ATAAD patients (P<0.05).After multivariate COX proportional hazards regression analysis,severe aortic valve insufficiency (AI),mesenteric ischemia,cerebral ischemia,postoperative new stroke,and a white blood cell count (WBC) ≥11.59×10<suP>9</suP>/L were independently associated with increased postoperative mortality risk (P<0.05).A nomogram prediction model was constructed based on these five variables,with a C-index of 0.817 (P<0.001).Calibration curves showed good agreement between predicted and actual values.Time-dependent ROC curves demonstrated that the model had good clinical discrimination for 1-year,3-year,and 5-year mortality risks (areas under the curve >0.7). Conclusion: Severe AI,mesenteric ischemia,cerebral ischemia,postoperative new stroke,and high preoperative WBC are independently associated with postoperative mortality risk in ATAAD patients.The nomogram model constructed using these five variables is feasible for predicting mortality.

Key words： Aortic dissection Stanford type A Death Predictive modeling Nomograms

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http://www.hbyxzzs.cn/EN/10.3969/j.issn.1006-6233.2025.04.019 OR http://www.hbyxzzs.cn/EN/Y2025/V31/I4/642

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