• Qipeng Luo, Zhanhao Su, Yuan Jia, Yiwei Liu, Hongbai Wang, Liang Zhang, Yinan Li, Xie Wu, Qiao Liu, and Fuxia Yan.
• Department of Anesthesiology, Fuwai Hospital, National Center of Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
• J. Cardiothorac. Vasc. Anesth. 2020 Apr 1; 34 (4): 940-948.

ObjectiveProlonged mechanical ventilation (PMV) is closely associated with higher morbidity and mortality after total cavopulmonary surgery. The aim of the present study was to identify the clinical risk factors for PMV.DesignA retrospective case-control study.SettingFuwai Hospital.ParticipantsThe study comprised 504 patients who underwent total cavopulmonary surgery from 2010 to 2018.InterventionsNone.Measurements And Main ResultsThe definition of PMV was derived from the Cox regression model for predicting postoperative length of hospital stay. Least absolute shrinkage and selection operator regression, logistic regression, and Cox regression were applied to identify predictors for PMV. Patients with mechanical ventilation time >9 hours were identified as having PMV. Independent predictors of PMV included age, intraoperative maximum vasoactive-inotropic score, minimal temperature during cardiopulmonary bypass, postoperative prothrombin time, alkaline phosphatase and total bilirubin levels, and postoperative fluid balance. These predictors also were achieved in the Cox regression for predicting the duration of mechanical ventilation. Patients with PMV were associated with increased blood transfusions, more consumption of vasopressin and antipulmonary hypertension medication, higher incidence of reintubation, more renal replacement treatment, longer intensive care unit stay, greater hospitalization costs, and more specialist visits.ConclusionsAge at surgery, maximal vasoactive-inotropic score and minimal temperature during cardiopulmonary bypass, postoperative prothrombin time, alkaline phosphatase and total bilirubin levels, and postoperative fluid balance were demonstrated to be independent predictors of PMV. Adopting a comprehensive strategy of perioperative management that targets the identified risk factors might significantly lower the risk of PMV and improve in-hospital outcomes, and furthermore, patients with PMV might need more specialist visits.Copyright © 2020. Published by Elsevier Inc.

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