SAPS 3 as a predictor admission of surgical patients in the ICU
© de Oliveira et al; licensee BioMed Central Ltd. 2013
Published: 19 June 2013
Owing to lack of intensive care beds, patients undergoing intermediate-risk surgery are usually sent to the ward postoperatively. However, a part from this population evolves with complications requiring intensive care (ICU). The aim of the study was to evaluate the characteristics of surgical patients who were admitted to the ICU lately and to find predictors of the need for intensive care.
We included 100 patients aged 66.4 ± 14.7 years. The SAPS 3 score average was 38.5 ± 8.6, 71% had ASA 2, women constituted 66% of casuistic. Most surgery was elective, the most frequent gynecologic (30%) and orthopedic (28%) and neuraxial regional anesthesia (49%). Of all patients, 27% required ICU admission, average on the sixth day after surgery and 3.0% died. The SAPS 3 score average was higher (45.4 ± 7.8 vs. 35.9 ± 7.4, P <0.001) and ASA 3 was more prevalent (40.7% vs. 8.2%, P = 0.001) in patients who required intensive care postoperatively. Furthermore, these patients had longer duration of surgery (4.2 ± 1.9 vs. 2.7 ± 1.5 hours, P <0.001), higher prevalence of gastrointestinal surgery (14.8% vs. 5.5%, P = 0.03) and greater need for intraoperative transfusion (18.5% vs. 5.5%, P = 0.04). In these patients admitted to the ICU mortality was 11.1% versus 0.0%, P = 0.004. In multivariate analysis, we found the value of SAPS 3 as an independent factor in determining whether the patient would need the ICU, OR = 1.25; 95% CI = 1.1 to 1.4; P = 0.001, and even the time of surgery, OR = 3.33; 95% CI = 1.7 to 6.3; P = 0.002. The ROC curve was 0.87; 95% CI = 0.78 to 0.93 for the SAPS 3 discriminating need for intensive care, rather than ASA, ROC 0.64; 95% CI = 0.54 to 0.74.
The identification of high-risk surgical patients is a difficult task, but essential for their proper treatment, surgery time together with the SAPS 3 seem to be useful tools in this differentiation and may help to better characterize this population.
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