Journal of cardiac surgery · 2022
Predicting postoperative hypoxemia risk factors in the patients after triple-branched stent graft implantation surgery with acute type A aortic dissection: A retrospective study.
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Wang Hanyu, Xu Zheng, Dai Xiaofu, Chen Liangwan
Аннотация
OBJECTIVE: To evaluate the risk factors of postoperative hypoxemia in patients after triple-branched stent graft implantation surgery with acute type A aortic dissection by conducting a nomogram.
METHODS: We evaluated 97 patients with acute type A aortic dissection (2020-2021), who underwent triple-branched stent graft implantation surgery. The independent risk factors were screened using univariate and multivariate logistic regression. We integrated significant factors as well as potential interference factors to build the nomogram model. The accuracy of the nomogram model was determined by using receiver operating characteristic curves (ROC), decision curve analyses (DCA), and calibration plots. Internal verification was evaluated using bootstrap validation.
RESULTS: Logistic regression analysis illustrated that the postoperative lactic acid, postoperative creatinine, and intraoperative aortic occlusion time were all independent risk factors for hypoxemia. Age, sex, and body mass index (BMI) were clinically relevant for predicting postoperative hypoxemia. We established a nomogram based on these six risk factors. The ROC (area under the curve [AUC] = 0.765), DCA, and calibration confirmed good discriminatory applicability and accuracy of the nomogram. Bootstrap validation (AUC = 0.76) verified the applicability of the nomogram.
CONCLUSIONS: The nomogram model could serve as a tool for the prediction of postoperative hypoxemia in patients after modified triple-branched stent graft implantation surgery with acute type A aortic dissection.
METHODS: We evaluated 97 patients with acute type A aortic dissection (2020-2021), who underwent triple-branched stent graft implantation surgery. The independent risk factors were screened using univariate and multivariate logistic regression. We integrated significant factors as well as potential interference factors to build the nomogram model. The accuracy of the nomogram model was determined by using receiver operating characteristic curves (ROC), decision curve analyses (DCA), and calibration plots. Internal verification was evaluated using bootstrap validation.
RESULTS: Logistic regression analysis illustrated that the postoperative lactic acid, postoperative creatinine, and intraoperative aortic occlusion time were all independent risk factors for hypoxemia. Age, sex, and body mass index (BMI) were clinically relevant for predicting postoperative hypoxemia. We established a nomogram based on these six risk factors. The ROC (area under the curve [AUC] = 0.765), DCA, and calibration confirmed good discriminatory applicability and accuracy of the nomogram. Bootstrap validation (AUC = 0.76) verified the applicability of the nomogram.
CONCLUSIONS: The nomogram model could serve as a tool for the prediction of postoperative hypoxemia in patients after modified triple-branched stent graft implantation surgery with acute type A aortic dissection.