Unveiling the role of risk factors and predictive models in acute type-a aortic dissection surgery: OI downregulation and its association with immune disorders.
Fuyan Ding, Jianyang Liu, Hong Wang, Ying Tan, Zhidong Zhang, Gang Qiao, Taibing Fan
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引用次数: 0
Abstract
Background and Objective: Acute type A aortic dissection (ATAAD) represents a critical and life-threatening condition requiring urgent surgical intervention, which is often life-saving. However, postoperative acute lung injury (ALI) has emerged as a prominent complication that significantly impacts patient outcomes and prognosis. This study aims to systematically analyze the risk factors associated with the development of severe ALI following ATAAD surgery, providing insights to improve postoperative management strategies. Methods: A retrospective analysis was conducted using a comprehensive database comprising 483 patients diagnosed with ATAAD. Patients were stratified into two groups based on the severity of postoperative ALI: severe ALI group (n = 182) and non-severe ALI group (n = 301). Clinical data were systematically collected and compared between the two cohorts. Binary logistic regression analysis was employed to identify independent predictors of severe ALI following ATAAD surgery. The diagnostic accuracy of these risk factors was assessed using receiver operating characteristic (ROC) curve analysis, with the area under the curve (AUC) serving as the metric for prognostic performance. Results: The severe ALI group exhibited a higher prevalence of preoperative oxygenation index (OI) ≤ 200 mmHg, smoking history, and coronary artery disease compared to the non-severe ALI group (P < 0.001, P = 0.032, and P = 0.039, respectively), while the prevalence of Marfan syndrome was lower (P = 0.033). Moreover, significant differences were observed in several clinical and intraoperative parameters, including body mass index (BMI), C-reactive protein (CRP), procalcitonin (PCT), D-dimer, white blood cell count (WBC), aortic cross-clamp time, moderate hypothermic circulatory arrest (MHCA) time, cardiopulmonary bypass (CPB) duration, and ICU length of stay (all P < 0.05). Multivariate logistic regression identified preoperative OI [P = 0.008, OR (95% CI): 0.002 (0.000-0.183)], BMI [P = 0.037, OR (95% CI): 1.569 (1.027-2.397)], CRP [P = 0.022, OR (95% CI): 1.292 (1.037-1.609)], D-dimer [P < 0.001, OR (95% CI): 3.841 (1.820-8.108)], MHCA time [P = 0.001, OR (95% CI): 3.306 (1.670-6.544)], and CPB duration [P = 0.017, OR (95% CI): 1.117 (1.020-1.223)] as independent predictors of severe ALI. ROC curve analysis revealed the diagnostic performance of preoperative OI, BMI, CRP, D-dimer, MHCA time, and CPB duration, with AUC values of 0.715, 0.844, 0.871, 0.955, 0.944, and 0.833, respectively (all P < 0.001). Conclusion: Preoperative oxygenation index, BMI, CRP, D-dimer levels, MHCA time, and CPB duration are independent risk factors for the development of severe ALI following ATAAD surgery. These findings underscore the importance of preoperative risk assessment and perioperative optimization to mitigate the risk of severe ALI and improve patient outcomes.
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