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. 2006 May 31:1:14.
doi: 10.1186/1749-8090-1-14.

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

Sanjay V Ghotkar  1 , Antony D Grayson, Brian M Fabri, Walid C Dihmis, D Mark Pullan
Affiliations

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

Sanjay V Ghotkar et al. J Cardiothorac Surg. .

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.

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Figures

Figure 1
Figure 1
Receiver operator characteristic curve for multivariate prediction model.
Figure 2
Figure 2
Hosmer-Lemeshow plot of observed number of patients with a prolonged intensive care unit stay (x-axis) versus predicted number of patients with a prolonged intensive care unit stay (y-axis) by decile of risk.
Figure 3
Figure 3
Comparison of multivariate prediction model for prolonged intensive care unit stay with existing risk stratification tools.
Figure 4
Figure 4
Simplified clinical risk assessment tool for prolonged intensive care unit stay.
Figure 5
Figure 5
Comparison of off-pump and on-pump coronary surgery by prolonged intensive care unit stay risk groups.
See this image and copyright information in PMC

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