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|Title:||Development and Validation of a Score to Identify Cardiac Surgery Patients at High Risk of Prolonged Mechanical Ventilation.|
|Authors:||Hessels, Lara;Coulson, Tim G;Seevanayagam, Siven;Young, Paul;Pilcher, David;Marhoon, Nada;Bellomo, Rinaldo|
|Affiliation:||Australian and New Zealand Intensive Care Research Centre, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia|
Centre of Integrated Critical Care, University of Melbourne, Melbourne, Australia
School of Medicine, University of Melbourne, Melbourne, Australia
Department of Intensive Care, Alfred Hospital, Melbourne, Australia
Department of Anaesthesia, Austin Health, Heidelberg, Victoria, Australia
Department of Cardiac Surgery, Austin Health, Heidelberg, Victoria, Australia
Data Analytics Research and Evaluation (DARE) Centre, Austin Health and The University of Melbourne, Heidelberg, Victoria, Australia
Department of Intensive Care, Austin Health, Heidelberg, Victoria, Australia
Department of Critical Care, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands..
Medical Research Institute of New Zealand, Wellington, New Zealand; Intensive Care Unit, Wellington Hospital, Wellington, New Zealand..
|Citation:||Journal of cardiothoracic and vascular anesthesia 2019; online first: 8 March|
|Abstract:||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. Retrospective analysis. Tertiary intensive care unit. Cardiac surgery patients. Observational study. 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. 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.|
|Appears in Collections:||Journal articles|
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