实用医学杂志 ›› 2025, Vol. 41 ›› Issue (17): 2755-2760.doi: 10.3969/j.issn.1006-5725.2025.17.021

• 医学检查与临床诊断 • 上一篇    

D-二聚体/白蛋白、白细胞介素-6、纤维蛋白降解产物联合预测A型主动脉夹层术后不良结局

张云芳,李铮,聂晓改,关赟,陈琪,袁勇()   

  1. 昆明医科大学附属延安医院医学检验科 (云南 昆明 650051 )
  • 收稿日期:2025-05-16 出版日期:2025-09-10 发布日期:2025-09-05
  • 通讯作者: 袁勇 E-mail:yuanyong1@kmmu.edu
  • 基金资助:
    昆明市卫生科技人才培养项目(编号:2024-SW(后备)-19)

D⁃dimer/Alb ratio, IL⁃6 and FDP jointly predict poor outcomes post type A dissection

Yunfang ZHANG,Zheng LI,Xiaogai NIE,Yun GUAN,Qi CHEN,Yong YUAN()   

  1. Department of Medical Laboratory,Yan'an Hospital Affiliated to Kunming Medical University,Kunming 650051,Yunnan,China
  • Received:2025-05-16 Online:2025-09-10 Published:2025-09-05
  • Contact: Yong YUAN E-mail:yuanyong1@kmmu.edu

摘要:

目的 分析并评估D-二聚体/白蛋白比值(DAR)联合白细胞介素-6(IL-6)及纤维蛋白降解产物(FDP)在急性Stanford A型主动脉夹层(ATAAD)术后不良结局的预测效能。 方法 采用回顾性队列研究设计,纳入2024年7月至2025年3月本院收治的284例接受孙氏手术的ATAAD患者。根据术后30 d内是否发生急性肾功能衰竭需透析治疗、二次开胸止血、严重神经系统并发症、多器官功能衰竭、抢救或全因死亡,将患者分为非不良结局组(n = 196)和不良结局组(n = 88)。通过电子病历系统采集术前基线资料、围术期参数及实验室指标。不符合正态分布的连续变量采用采用Mann-Whitney U检验进行组间差异比较,对于分类变量则根据频数分布特征,选择χ2检验或Fisher精确检验进行统计学差异分析。在单因素分析基础上,采用多因素logistic回归分析筛选独立危险因素。 结果 非不良结局组与不良结局组在年龄、体外循环时间、乳酸脱氢酶(LDH)、IL-6、D-二聚体(D-D)、FDP及DAR水平上差异有统计学意义(P < 0.05)。多因素分析显示,DAR、IL-6、D-D、FDP及体外循环时间延长是ATAAD术后不良结局的独立危险因素(P < 0.05),联合检测分析显示,DAR联合IL-6、FDP及体外循环时间的预测效能最优,ROC曲线下面积达0.886(95%CI:0.846 ~ 0.927)。 结论 DAR联合IL-6、FDP及体外循环时间检测可有效预测ATAAD术后不良结局,该生物标志物组合可作为术后风险分层的有效预测指标。

关键词: Stanford A型主动脉夹层, 不良结局, 生物标志物, 队列研究, logistic回归

Abstract:

Objective To analyze and evaluate the early warning efficacy of D?dimer/albumin ratio (DAR) combined with interleukin?6 (IL?6) and fibrin degradation products (FDP) in the postoperative treatment of acute Stanford type A aortic dissection (ATAAD). Methods A retrospective cohort study was conducted on 284 ATAAD patients who underwent the Sun′s procedure at our hospital from July 2024 to March 2025. Patients were divided into a non?adverse outcome group (n = 196) and an adverse outcome group (n = 88) based on the occurrence of postoperative complications within 30 days, including acute renal failure requiring dialysis, secondary thoracotomy for hemostasis, severe neurological complications, multiple organ failure, or all?cause mortality. Preoperative baseline data, perioperative parameters, and laboratory indicators were collected via the electronic medical record system. The Mann?Whitney U test was used to compare the differences between groups for continuous variables that did not conform to the normal distribution, and Chi?square test or Fisher's exact test was selected for statistical difference analysis according to the frequency distribution characteristics of categorical variables. On the basis of univariate analysis, multivariate logistic regression analysis was used to screen independent risk factors. Results Statistically significant differences were observed between the non?adverse and adverse outcome group in age, cardiopulmonary bypass time, lactate dehydrogenase (LDH), IL?6, D?dimer (D?D), FDP, and DAR levels (P < 0.05). Multivariate analysis revealed that DAR, IL?6, D?D, FDP, and prolonged cardiopulmonary bypass time were independent risk factors for adverse postoperative outcomes (P < 0.05). Combined detection analysis demonstrated that the combination of DAR, IL?6, FDP, and cardiopulmonary bypass time yielded the highest predictive efficacy, with an area under the ROC curve of 0.886 (95%CI: 0.846 ~ 0.927). Conclusion The combination of DAR, IL?6, FDP, and cardiopulmonary bypass time effectively predicts adverse postoperative outcomes in ATAAD patients. This biomarker panel may serve as a robust predictive tool for postoperative risk stratification.

Key words: stanford type A aortic dissection, adverse outcomes, biomarkers, cohort studies, logistic regression

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