1. Estimation Model for Hypothermic Circulatory Arrest Time to Predict Risk in Total Arch Replacement
- Author
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Ryo Harada, Keitaro Nakanishi, Hiroshi Sato, Takeshi Kamada, Nobuyoshi Kawaharada, Yukihiko Tamiya, Takuma Mikami, Syuichi Naraoka, Fukada J, and Tsuyoshi Shibata
- Subjects
Male ,Pulmonary and Respiratory Medicine ,medicine.medical_specialty ,Time Factors ,Risk Assessment ,law.invention ,law ,Internal medicine ,Cardiopulmonary bypass ,Humans ,Medicine ,Aged ,Retrospective Studies ,Aged, 80 and over ,Body surface area ,Aortic Aneurysm, Thoracic ,business.industry ,Area under the curve ,Atrial fibrillation ,Odds ratio ,Middle Aged ,Models, Theoretical ,medicine.disease ,Circulatory arrest time ,Circulatory Arrest, Deep Hypothermia Induced ,Circulatory system ,Cardiology ,Female ,Surgery ,Multiple linear regression analysis ,Cardiology and Cardiovascular Medicine ,business - 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.
- Published
- 2022