ObjectivePatients 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).Methods5,186 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.Results475(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.ConclusionA prediction tool has been developed which is reliable and valid. The tool is being piloted at our institution to aid resource management.
OBJECTIVES Despite the seriousness of prolonged mechanical ventilation (PMV) as a postoperative complication, previously proposed risk prediction models were met with limited success. The purpose of this study was to identify perioperative variables associated with PMV in elective primary coronary bypass surgery. PMV was defined as the need for intubation and mechanical ventilation for >72 h, after completion of the operation. METHODS Between April 1997 and September 2010, 10 ,977 consecutive patients were retrospectively reviewed. A series of two multivariate logistic regression analyses were carried out to identify preoperative predictors of prolonged ventilation and the impact of operative variables. RESULTS PMV occurred in 215 (1.96%) patients; 119 (55.3%) of these underwent tracheostomy. At multivariate analysis, predictors included NYHA higher than class II (odds ratio [OR], 1.77; 95% confidence intervals [CI], 1.34-2.34), renal dialysis (OR, 5.5; 95% CI, 2.08-14.65), age at operation (OR, 1.04; 95% CI, 1.02-1.06), reduced FEV(1) (OR, 0.99; 95% CI, 0.98-0.99), body mass index >35 kg/m(2) (OR, 1.73; 95% CI, 1.14-2.63). On serial logistic regression analyses, operative variables added little to the discriminatory power of the model. Kaplan-Meier survival curves showed reduced survival among PMV patients (P < 0.001) with an improved survival in the tracheostomy subgroup. CONCLUSIONS PMV after coronary bypass is associated with a reduction in early and mid-term survival. Risk modelling for PMV remains problematic even when examining a more homogenous lower risk group.
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