Predicting the Necessity for Extracorporeal Circulation During Lung Transplantation: A Feasibility Study

Journal of Cardiothoracic and Vascular Anesthesia(2017)

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摘要
Objective The factors leading to the implementation of unplanned extracorporeal circulation during lung transplantation are poorly defined. Consequently, the authors aimed to identify patients at risk for unplanned extracorporeal circulation during lung transplantation. Design Retrospective data analysis. Setting Single-center university hospital. Participants A development data set of 170 consecutive patients and an independent validation cohort of 52 patients undergoing lung transplantation. Interventions The authors investigated a cohort of 170 consecutive patients undergoing single or sequential bilateral lung transplantation without a priori indication for extracorporeal circulation and evaluated the predictive capability of distinct preoperative and intraoperative variables by using automated model building techniques at three clinically relevant time points (preoperatively, after endotracheal intubation, and after establishing single-lung ventilation). Measurements and Main Results Preoperative mean pulmonary arterial pressure was the strongest predictor for unplanned extracorporeal circulation. A logistic regression model based on preoperative mean pulmonary arterial pressure and lung allocation score achieved an area under the receiver operating characteristic curve of 0.85. Consequently, the authors developed a novel 3-point scoring system based on preoperative mean pulmonary arterial pressure and lung allocation score, which identified patients at risk for unplanned extracorporeal circulation and validated this score in an independent cohort of 52 patients undergoing lung transplantation. Conclusions The authors showed that patients at risk for unplanned extracorporeal circulation during lung transplantation could be identified by their novel 3-point score.
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关键词
lung transplantation,extracorporeal circulation,mathematical modeling,prediction model,automated model building techniques
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