Predictors and outcome of ICU readmission after cardiac surgery
- PMID: 19795324
- DOI: 10.1055/s-0029-1185852
Predictors and outcome of ICU readmission after cardiac surgery
Abstract
Objective: Readmission to the intensive care unit (ICU) after cardiac surgery is associated with higher costs and may be correlated with an increased mortality. We wanted to evaluate predictors of ICU readmission and to analyze the outcome of those patients.
Methods: 3523 patients who underwent CABG and/or valve surgery between 2004 and 2007 were reviewed retrospectively. The reasons for readmission and the postoperative course were analyzed. Furthermore, perioperative risk factors for readmission were determined by multivariate regression analysis.
Results: Of the 3374 patients discharged from the ICU, 5.9 % (198) of patients required a second stay in the intensive care (group r). The readmission rate was 4.8 % following CABG and 8.9 % following valve +/- CABG ( P < 0.05). The mean interval from ICU discharge to readmission was 3.3 +/- 6.2 days. Of the patients who were not readmitted, 1.3 % died in hospital, compared to 14.4 % in group r ( P < 0.05). After readmission, the mean length of stay in the ICU and in hospital was 7.1 +/- 5.9 and 21.3 +/- 11.1 days (3.1 +/- 1.2 and 13.1 +/- 5.1 days for all other patients [ P < 0.05]). Main reasons for readmission were respiratory failure (59 %), cardiovascular instability (25 %), renal failure (6.5 %), cardiac tamponade/bleeding (6 %), gastrointestinal complications (2 %) and sepsis (1.5 %). Multivariate logistic regression analysis revealed that preoperative renal failure, mechanical ventilation > 24 h, reexploration for bleeding and low cardiac output state were independent predictors for readmission.
Conclusions: Patients after valve/combined surgery are more likely to require readmission to the ICU. Respiratory complications were the most common reasons for readmission. To reduce the readmission rate, it is necessary to treat cardio-respiratory problems early, particularly in patients showing predictive risk factors.
Georg Thieme Verlag KG Stuttgart. New York.
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