Development and Validation of a Score to Identify Cardiac Surgery Patients at High Risk of Prolonged Mechanical Ventilation

Lara Hessels, Tim G. Coulson, Siven Seevanayagam, Paul Young, David Pilcher, Nada Marhoon, Rinaldo Bellomo

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7 Citations (Scopus)


Objective: To develop and validate a score for the early identification of cardiac surgery patients at high risk of prolonged mechanical ventilation (MV) who may be suitable targets for interventional trials. Design: Retrospective analysis. Setting: Tertiary intensive care unit. Participants: Cardiac surgery patients. Interventions: Observational study. Measurements and Main Results: The study comprised 1,994 patients. Median age was 67 years, and 1,457 patients (74%) were male. Median duration of MV was 9.4 hours. A total of 229 (11%), 182 (9%), and 127 (6%) patients received MV for ≥24, ≥36, and ≥48 hours, respectively. In-hospital mortality was 13%, 15%, and 17%, respectively. For the study model, all preoperative, intraoperative, and early (first 4 hours) postoperative variables were considered. A multivariable logistic regression model was developed, and a predictive scoring system was derived. Using MV ≥24 hours as the primary outcome, the model performance in the development set was good with a c-index of 0.876 (95% confidence interval 0.846-0.905) and a Brier's score of 0.062. In the validation set, the c-index was 0.907 (0.867-0.948), Brier's score was 0.059, and the model remained well calibrated. Conclusions: The authors developed a simple score to predict prolonged MV after cardiac surgery. This score, if externally validated, is potentially suitable for identifying a high-risk target population for future randomized controlled trials of postoperative care after cardiac surgery.

Original languageEnglish
Pages (from-to)2709-2716
Number of pages8
JournalJournal of Cardiothoracic and Vascular Anesthesia
Issue number10
Publication statusPublished - Oct 2019


  • cardiac surgery
  • intensive care
  • mechanical ventilation
  • risk factors
  • risk score

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