Preoperative calculation of risk for prolonged intensive care unit stay following coronary artery bypass grafting

OBJECTIVE: Patients who have prolonged stay in intensive care unit (ICU) are associated with adverse outcomes. Such patients have cost implications and can lead to shortage of ICU beds. We aimed to develop a preoperative risk prediction tool for prolonged ICU stay following coronary artery surgery (CABG). METHODS: 5,186 patients who underwent CABG between 1st April 1997 and 31st March 2002 were analysed in a development dataset. Logistic regression was used with forward stepwise technique to identify preoperative risk factors for prolonged ICU stay; defined as patients staying longer than 3 days on ICU. Variables examined included presentation history, co-morbidities, catheter and demographic details. The use of cardiopulmonary bypass (CPB) was also recorded. The prediction tool was tested on validation dataset (1197 CABG patients between 1(st )April 2003 and 31(st )March 2004). The area under the receiver operating characteristic (ROC) curve was calculated to assess the performance of the prediction tool. RESULTS: 475(9.2%) patients had a prolonged ICU stay in the development dataset. Variables identified as risk factors for a prolonged ICU stay included renal dysfunction, unstable angina, poor ejection fraction, peripheral vascular disease, obesity, increasing age, smoking, diabetes, priority, hypercholesterolaemia, hypertension, and use of CPB. In the validation dataset, 8.1% patients had a prolonged ICU stay compared to 8.7% expected. The ROC curve for the development and validation datasets was 0.72 and 0.74 respectively. CONCLUSION: A prediction tool has been developed which is reliable and valid. The tool is being piloted at our institution to aid resource management

Cardiac surgery in patients with previous pneumonectomy

Abstract Severe pulmonary dysfunction is a commonly occurring postoperative complication following cardiac surgery. Resection of a lung causes major anatomical and physiological changes. Shift of the mediastinum and reduction in respiratory function following pneumonectomy makes cardiac surgery challenging not only for the surgeon but also for the anaesthetist. With improvement in life expectancy and better results following cardiac and pulmonary operations increasing number of patients are likely to be subjected to both of these operations during their lifetime. There is paucity of data in the literature on the subject of cardiac surgery subsequent to previous pneumonectomy. We report our experience on performing cardiac surgery following pneumonectomy to highlight certain important features that we think are important while managing these patients.</p

Cardiac surgery in patients with previous pneumonectomy

This is an Open Access article distributed under the terms of the Creative Commons Attribution Licens

Preoperative calculation of risk for prolonged intensive care unit stay following coronary artery bypass grafting

Abstract Objective Patients who have prolonged stay in intensive care unit (ICU) are associated with adverse outcomes. Such patients have cost implications and can lead to shortage of ICU beds. We aimed to develop a preoperative risk prediction tool for prolonged ICU stay following coronary artery surgery (CABG). Methods 5,186 patients who underwent CABG between 1st April 1997 and 31st March 2002 were analysed in a development dataset. Logistic regression was used with forward stepwise technique to identify preoperative risk factors for prolonged ICU stay; defined as patients staying longer than 3 days on ICU. Variables examined included presentation history, co-morbidities, catheter and demographic details. The use of cardiopulmonary bypass (CPB) was also recorded. The prediction tool was tested on validation dataset (1197 CABG patients between 1st April 2003 and 31st March 2004). The area under the receiver operating characteristic (ROC) curve was calculated to assess the performance of the prediction tool. Results 475(9.2%) patients had a prolonged ICU stay in the development dataset. Variables identified as risk factors for a prolonged ICU stay included renal dysfunction, unstable angina, poor ejection fraction, peripheral vascular disease, obesity, increasing age, smoking, diabetes, priority, hypercholesterolaemia, hypertension, and use of CPB. In the validation dataset, 8.1% patients had a prolonged ICU stay compared to 8.7% expected. The ROC curve for the development and validation datasets was 0.72 and 0.74 respectively. Conclusion A prediction tool has been developed which is reliable and valid. The tool is being piloted at our institution to aid resource management.</p