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全弓置换中低温停循环时间预测风险的估算模型。

Estimation Model for Hypothermic Circulatory Arrest Time to Predict Risk in Total Arch Replacement.

机构信息

Department of Cardiovascular Surgery, Sapporo Medical University School of Medicine, Sapporo, Japan.

Department of Cardiovascular Surgery, Sapporo Medical University School of Medicine, Sapporo, Japan.

出版信息

Ann Thorac Surg. 2022 Jan;113(1):256-263. doi: 10.1016/j.athoracsur.2020.12.060. Epub 2021 Feb 3.

Abstract

BACKGROUND

We created an estimation model for hypothermic circulatory arrest time and analyzed the risk factors for major adverse outcomes in total arch replacement.

METHODS

This study involved 272 patients who underwent total arch replacement. The estimation model for hypothermic circulatory arrest time was established using multiple linear regression analysis, and the predicted hypothermic circulatory arrest time from this model was analyzed to detect risk factors.

RESULTS

Atrial fibrillation, rupture, malperfusion, saccular aneurysm, cardiopulmonary bypass time, and hypothermic circulatory arrest time were identified as independent risk factors associated with major adverse outcomes. The estimation model for hypothermic circulatory arrest time was established as follows: hypothermic circulatory arrest time = 99.3 - 0.19 × age + 0.65 × body mass index + 6.19 × previous cardiac operation + 11.7 × acute dissection + 8.9 × rupture + 0.19 × aortic angulation + 0.15 × length to the distal anastomosis site - 6.17 × total arch replacement surgeon case volume - 3.06 × surgery year. The predicted hypothermic circulatory arrest time calculated by this estimation model was evaluated using multivariate logistic analysis, which identified atrial fibrillation, rupture, malperfusion, saccular aneurysm, and predicted hypothermic circulatory arrest time as risk factors.

CONCLUSIONS

As with the actual hypothermic circulatory arrest time, the predicted hypothermic circulatory arrest time using our model detected significant factors associated with major adverse outcomes. These results indicated that this prediction model for hypothermic circulatory arrest time may be effective.

摘要

背景

我们建立了一个用于体外循环停循环时间的估计模型,并分析了全弓置换术主要不良结局的危险因素。

方法

本研究纳入 272 例接受全弓置换术的患者。使用多元线性回归分析建立体外循环停循环时间的估计模型,并对该模型预测的体外循环停循环时间进行分析,以检测危险因素。

结果

心房颤动、破裂、灌注不良、囊状动脉瘤、体外循环时间和体外循环停循环时间被确定为与主要不良结局相关的独立危险因素。体外循环停循环时间的估计模型如下:体外循环停循环时间=99.3-0.19×年龄+0.65×体重指数+6.19×既往心脏手术+11.7×急性夹层+8.9×破裂+0.19×主动脉倾斜角+0.15×远端吻合部位长度-6.17×全弓置换术医师手术量-3.06×手术年份。使用多元逻辑回归分析评估该估计模型计算的预测体外循环停循环时间,确定心房颤动、破裂、灌注不良、囊状动脉瘤和预测体外循环停循环时间为危险因素。

结论

与实际体外循环停循环时间一样,我们的模型预测的体外循环停循环时间检测到与主要不良结局相关的显著因素。这些结果表明,这种体外循环停循环时间预测模型可能有效。

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