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中国人民解放军联勤保障部队第九六〇医院心外科,山东 济南 250031
任超,E-mail:pffalm@163.com
收稿:2025-11-18,
纸质出版:2026-06-25
移动端阅览
张波,王同建,梁家立等.Stanford B 型主动脉夹层术后主动脉重塑不良的影响因素与列线图模型[J].局解手术学杂志,2026,35(06):513-517.
ZHANG Bo,WANG Tong-jian,LIANG Jia-li,et al.Influencing factors and a nomogram model for poor aortic remodeling after thoracic endovascular aortic repair in patients with Stanford type B aortic dissection[J].JOURNAL OF REGIONAL ANATOMY AND OPERATIVE SURGERY,2026,35(06):513-517.
张波,王同建,梁家立等.Stanford B 型主动脉夹层术后主动脉重塑不良的影响因素与列线图模型[J].局解手术学杂志,2026,35(06):513-517. DOI: 10.11659/jjssx.11E025110.
ZHANG Bo,WANG Tong-jian,LIANG Jia-li,et al.Influencing factors and a nomogram model for poor aortic remodeling after thoracic endovascular aortic repair in patients with Stanford type B aortic dissection[J].JOURNAL OF REGIONAL ANATOMY AND OPERATIVE SURGERY,2026,35(06):513-517. DOI: 10.11659/jjssx.11E025110.
目的
2
探讨Stanford B型主动脉夹层(TBAD)患者胸主动脉腔内修复术(TEVAR)后主动脉重塑不良的影响因素,并构建列线图预测模型。
方法
2
将2020年1月至2025年1月于本院进行TEVAR的260例TBAD患者根据随机数字表法分为模型集(
n
=182)和验证集(
n
=78)。根据术后3个月主动脉重塑情况将模型集患者分为重塑良好组(
n
=122)和重塑不良组(
n
=60)。采用多因素
Logistic
回归法分析TBAD患者TEVAR后主动脉重塑不良的影响因素,并构建列线图风险预测模型;模型的预测区分度、一致性分别采用受试者工作特征(
ROC
)曲线、校准曲线评估。
结果
2
随访结果显示,260例TBAD患者TEVAR后主动脉重塑不良发生率为31.15%。重塑良好组与重塑不良组患者在主动脉弓长度、破口数目、假腔直径、假腔分支灌注情况、发病至手术时间、血小板计数(PLT)水平上存在显著差异(
P
<
0.05)。多因素
Logistic
回归结果显示,主动脉弓长度增加(
OR
=0.807)和PLT较高(
OR
=0.945)是TEVAR后主动脉重塑不良的保护因素(
P
<
0.05),破口数目≥3个(
OR
=3.528)、假腔直径较大(
OR
=1.492)、假腔有分支灌注(
OR
=4.021)和发病至手术时间较长(
OR
=2.094)为TEVAR后主动脉重塑不良的危险因素(
P
<
0.05)。
ROC
分析中,模型集和验证集的曲线下面积(
AUC
)分别为0.933(95%
CI
:0.899~0.967)、0.948(95%
CI
:0.904~0.992);
Hosmer
-
Lemeshow
检验显示,模型集
χ
2
=2.490、
P
=0.962,验证集
χ
2
=5.265、
P
=0.741。
结论
2
TBAD患者TEVAR后主动脉重塑不良与主动脉弓长度、破口数目、假腔直径、假腔分支灌注情况、发病至手术时间、PLT水平密切相关,基于上述6个因素构建的列线图模型预测TEVAR后主动脉重塑不良风险的效能较高。
Objective
2
To explore the influencing factors for poor aortic remodeling after thoracic endovascular aortic repair (TEVAR) in patients with Stanford type B aortic dissection (TBAD), and to construct a nomogram prediction model.
Methods
2
A total of 260 TBAD patients who underwent TEVAR in our hospital from January 2020 to January 2025 were divided into the model set (
n
=182) and the validation set (
n
=78) by random number table method. Patients in the model set were divided into the good remodeling group (
n
=122) and the poor remodeling group (
n
=60) according to the aortic remodeling situation at 3 months after surgery. Multivariate
Logistic
regression analysis was performed to identify the influencing factors for poor aortic remodeling after TEVAR in TBAD patients, and the nomogram risk prediction model was constructed. The predictive discrimination and consistency of the model were evaluated by
receiver operating characteristic
(
ROC
) curve and
calibration curve
, respectively.
Results
2
The follow-up results showed that the incidence of poor aortic remodeling after TEVAR in 260 patients with TBAD was 31.15%. There were statistically significant differences between the good remodeling group and the poor remodeling group in terms of the aortic arch length, the number of tears, the diameter of the false lumen, the false lumen branch perfusion, the time from onset to surgery,and platelet count(PLT) level (
P
<
0.05).Multivariate
Logistic
regression analysis showed that increased aortic arch length (
OR
=0.807) and higher PLT level (
OR
=0.
945) were the protective factors for poor aortic remodeling after TEVAR (
P
<
0.05), while the number of tears ≥ 3 (
OR
=3.528),the larger diameter of the false lumen (
OR
=1.492),false lumen branch perfusion (
OR
=4.021), and the longer time from onset to surgery (
OR
=2.094) were the risk factors for poor aortic remodeling after TEVAR (
P
<
0.05). In the
ROC
analysis, the
area under the curve
(
AUC
) of the model set and the validation set were 0.933 (95%
CI
: 0.899~0.967) and 0.948 (95%
CI
: 0.904~0.992), respectively. The
Hosmer-Lemeshow
test showed
χ
2
=2.490,
P
=0.962 in the model set, and
χ
2
=5.265,
P
=0.741 in the validation set.
Conclusion
2
The poor aortic remodeling after TEVAR in patients with TBAD is closely related to the aortic arch length, the number of tears, the diameter of the false lumen, the false lumen branch perfusion, the time from onset to surgery, and PLT level. The nomogram model constructed based on the above six factors has a high efficacy in predicting the risk of poor aortic remodeling after TEVAR.
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