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Article in English | IMSEAR | ID: sea-38448

ABSTRACT

OBJECTIVE: To determine the mortality and risk factors of mortality in a surgical intensive care unit (SICU), King Chulalongkorn Memorial Hospital. DESIGN: Review of retrospective data. SETTING: a SICU of a tertiary-care academic medical center. PATIENTS: Out of a total of 546 patients admitted to SICU during a one year period (January 1, 2000 - December 31, 2000), 458 (83.9%) had complete medical data which were analyzed. MEASUREMENTS AND MAIN RESULTS: One hundred and ninety-three variables of 6 categories of patients' characteristics, chronic disease, acute illness, physiologic variables, therapy and miscellaneous were studied. Univariate and multivariate analyses were used. The SICU and hospital mortality was 8.1 and 14.6 per cent, respectively. Multivariate logistic regression analysis identified seven variables as independent risk factors for mortality (p < 0.05): chronic renal failure (adjusted odds ratio [AOR], 7.5; 95% CI, 3.0 to 19.0; p = 0.000), coma (AOR, 11.7; 95% CI, 2.4 to 57.4; p = 0.002), Staphylococcus aureus infection (AOR, 15.4; 95% CI, 1.6 to 147.6; p = 0.018), diagnosis of systemic inflammatory response (AOR, 2.9; 95% CI, 1.2 to 7.1; p = 0.017), mechanical ventilation (AOR, 11.2; 95% CI, 2.0 to 61.4; p = 0.005), having received adrenaline (AOR, 7.1; 95% CI, 2.3 to 22.2; p = 0.001) and diuretic (AOR, 3.3; 95% CI, 1.4 to 8.1; p = 0.008). Besides weight (AOR, 0.9; 95% CI, 0.9 to 1.0; p = 0.002) and having received H2-blocker (AOR, 0.2; 95% CI, 0.1 to 0.5; p = 0.001) were two independent protective factors for mortality. CONCLUSION: Knowing the risk factors of SICU mortality will help physicians to improve patient care, educate patients and their families, optimize ICU resource planning and may decrease health care costs.


Subject(s)
Academic Medical Centers/standards , Adolescent , Adult , Age Distribution , Aged , Aged, 80 and over , Cause of Death , Confidence Intervals , Female , General Surgery , Hospital Mortality/trends , Humans , Incidence , Intensive Care Units/standards , Logistic Models , Male , Middle Aged , Multivariate Analysis , Predictive Value of Tests , Probability , Retrospective Studies , Risk Factors , Severity of Illness Index , Sex Distribution , Thailand/epidemiology
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