학술논문
Prolonged ventilation post cardiac surgery - tips and pitfalls of the prediction game
Research article
Research article
Document Type
Report
Source
Journal of Cardiothoracic Surgery. November 23, 2011, Vol. 6, 158
Subject
Language
English
ISSN
1749-8090
Abstract
Authors: Piotr Knapik (corresponding author) [1]; Daniel Ciesla [1]; Dawid Borowik [1]; Piotr Czempik [1]; Tomasz Knapik [1] Background Patients whose ventilation after cardiac surgery is unexpectedly prolonged are prone [...]
Background Few available models aim to identify patients at risk of prolonged ventilation after cardiac surgery. We compared prediction models developed in ICU in two adjacent periods of time, when significant changes were observed both in population characteristics and the perioperative management. Methods We performed a retrospective review of two cohorts of patients in our department in two subsequent time periods (July 2007 - December 2008, n = 2165; January 2009 - July 2010, n = 2192). The study was approved by the Institutional Ethics Committee and the individual patient consent was not required. Patients were divided with regard to ventilation time of more or less than 48 hours. Preoperative and procedure-related variables for prolonged ventilation were identified and multivariate logistic regression analysis was performed separately for each cohort. Results Most recent patients were older, with more co-morbidities, more frequently undergoing off-pump surgery. At the beginning of 2009 we also changed the technique of postoperative ventilation. Percentage of patients with prolonged ventilation decreased from 5.7% to 2.4% (p [less than] 0.0001).Preoperative and procedure-related variables for prolonged ventilation were identified. Prediction models for prolonged ventilation were different for each cohort. Most recent significant predictors were: aortic aneurysm surgery (OR 12.9), emergency surgery (OR 5.3), combined procedures (OR 5.1), valve procedures (OR 3.2), preoperative renal dysfunction (OR 2.9) and preoperative stroke or TIA (OR 2.8). Conclusions Prediction models for postoperative ventilation should be regularly updated, particularly when major changes are noted in patients' demographics and surgical or anaesthetic technique.
Background Few available models aim to identify patients at risk of prolonged ventilation after cardiac surgery. We compared prediction models developed in ICU in two adjacent periods of time, when significant changes were observed both in population characteristics and the perioperative management. Methods We performed a retrospective review of two cohorts of patients in our department in two subsequent time periods (July 2007 - December 2008, n = 2165; January 2009 - July 2010, n = 2192). The study was approved by the Institutional Ethics Committee and the individual patient consent was not required. Patients were divided with regard to ventilation time of more or less than 48 hours. Preoperative and procedure-related variables for prolonged ventilation were identified and multivariate logistic regression analysis was performed separately for each cohort. Results Most recent patients were older, with more co-morbidities, more frequently undergoing off-pump surgery. At the beginning of 2009 we also changed the technique of postoperative ventilation. Percentage of patients with prolonged ventilation decreased from 5.7% to 2.4% (p [less than] 0.0001).Preoperative and procedure-related variables for prolonged ventilation were identified. Prediction models for prolonged ventilation were different for each cohort. Most recent significant predictors were: aortic aneurysm surgery (OR 12.9), emergency surgery (OR 5.3), combined procedures (OR 5.1), valve procedures (OR 3.2), preoperative renal dysfunction (OR 2.9) and preoperative stroke or TIA (OR 2.8). Conclusions Prediction models for postoperative ventilation should be regularly updated, particularly when major changes are noted in patients' demographics and surgical or anaesthetic technique.