| A型主动脉夹层麻醉诱导后低血压预测模型构建 |
| 投稿时间：2025-08-10 修订日期：2025-08-24 点此下载全文 |
| 引用本文：朱学文,杨春玲,崔银,宋佳.A型主动脉夹层麻醉诱导后低血压预测模型构建[J].医学研究杂志,2026,55(1):122-126, 133 |
| DOI：
10.11969/j.issn.1673-548X.2026.01.021 |
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| 基金项目:江苏省南京市卫生科技发展专项资金资助项目一般课题(YKK21084) |
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| 中文摘要:目的 探讨接受急性A型主动脉夹层(acute type A aortic dissection,ATAAD)患者麻醉诱导后低血压(post-induction hypotension,PIH)发生的危险因素及其预测模型的构建。方法 回顾性分析352例全麻下接受ATAAD急诊手术的患者,将患者分为PIH组(n=174)与非PIH组(n=178)。通过单因素分析、LASSO回归模型、多因素二元Logistic回归模型筛选PIH发生的独立危险因素。建立列线图模型,分别采用受试者工作特征(receiver operating characteristic,ROC)曲线及曲线下面积(area under the curve,AUC)评估模型区分度,校准曲线评估模型预测风险与实际风险的一致性,Hosmer-Lemeshow拟合优度检验评估模型的校准度。结果 接受ATAAD急诊手术的患者PIH发生率为49.4%,单因素分析显示,与非PIH组患者比较,PIH组患者麻醉诱导前使用艾司洛尔、乌拉地尔,麻醉诱导前下腔静脉内径减小、合并心包积液、诱导期使用更高剂量舒芬太尼及依托咪酯-丙泊酚(P<0.05)；LASSO回归模型和Logistic多因素回归分析结果显示,麻醉诱导前艾司洛尔使用(OR=4.23,95% CI:2.53~7.06,P<0.001)、合并中大量心包积液(OR=2.53,95% CI:1.54~4.13,P<0.001)、依托咪酯-丙泊酚复合用药(OR=4.89,95% CI:1.54~4.13,P<0.001)、更高剂量舒芬太尼使用(OR=10.61,95% CI:5.11~22.01,P<0.001)、诱导前下腔静脉内径缩小(OR = 0.50,95% CI:0.43~0.59,P<0.001)是PIH发生的独立危险因素。列线图模型预测接受ATAAD急诊手术的患者PIH发生风险的ROC的AUC为0.921(95% CI:0.894~0.949),表明该模型列线图模型区分度良好；该模型的校准曲线为斜率接近1的直线,表明接受ATAAD急诊手术的患者PIH的发生风险与实际发生风险一致性良好；Hosmer-Lemeshow拟合优度检验χ2=13.024,P=0.111,表明模型具有较好的校准度。结论 接受ATAAD急诊手术的患者PIH发生的独立危险因素包括麻醉诱导前艾司洛尔应用、中大量心包积液、更高剂量的舒芬太尼、依托咪酯-丙泊酚复合麻醉及下腔静脉内径减小。列线图模型具有较好的临床预测能力及临床实用性,麻醉医师可根据此预测模型在术前实施分层管理以降低PIH的发生。 |
| 中文关键词:Stanford A型主动脉夹层 麻醉诱导后低血压 危险因素 LASSO回归 列线图 |
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| Construction of A Prediction Model for Post-induction Hypotension in Patients with Acute Type A Aortic Dissection. |
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| Abstract:Objective To investigate risk factors for post-induction hypotension (PIH) in patients with acute type A aortic dissection (ATAAD) undergoing general anesthesia and construct a prediction model. Methods A retrospective analysis was conducted on 352 patients who underwent emergency surgery for ATAAD under general anesthesia. Patients were divided into PIH group (n=174) and non-PIH group (n=178). Univariate analysis, LASSO regression model, and multivariate binary Logistic regression model were used to screen independent risk factors for PIH. A nomogram prediction model was constructed. The receiver operating characteristic (ROC) curve and the area under the curve (AUC) were used to evaluate the discriminative ability of the model. The calibration curves were plotted to assess the consistency between predicted and actual risks. The calibration of model was evaluated by the Hosmer-Lemeshow goodness-of-fit test. Results The incidence of PIH in patients undergoing emergency ATAAD surgery was 49.4%. Univariate analysis showed that compared with the non-PIH group, the PIH group had higher usage of Esmolol and Urapidil before induction, smaller inferior vena cava (IVC) diameter before induction, complicated with pericardial effusion, higher Sufentanil dosage and Etomidate-Propofol combination during induction (P<0.05). LASSO regression and multivariate Logistic regression analysis indicated that pre-induction Esmolol use (OR = 4.23,95% CI:2.53-7.06, P<0.001), moderate to massive pericardial effusion (OR = 2.53,95% CI:1.54-4.13, P<0.001), Etomidate-Propofol combined anesthesia (OR = 4.89,95% CI:1.54-4.13, P<0.001), higher Sufentanil dosage(OR = 10.61,95% CI:5.11-22.01, P<0.001), smaller IVC diameter before induction (OR = 0.50,95% CI:0.43-0.59, P < 0.001). Conclusion Key independent risk factors for PIH in ATAAD patients include preoperative Esmolol use, moderate to massive pericardial effusion, higher dose of Sufentanil, Etomidate-Propofol combined anesthesia, and decreased IVC diameter before induction. The nomogram model demonstrates favorable clinical predictive ability and practicality. Anesthesiologists can implement stratified preoperative management based on this model to reduce the incidence of PIH. |
| keywords:Stanford type A aortic dissection Post-induction hypotension LASSO regression Risk factors Nomogram |
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