title: Risk factors for predicting mortality in a surgical intensive care unit in the year 2000.
abstract: OBJECTIVE
  To determine the mortality and risk factors of mortality in a surgical intensive care unit (SICU), King Chulalongkorn Memorial Hospital.
  
  
  METHODS
  Review of retrospective data.
  
  
  METHODS
  a SICU of a tertiary-care academic medical center.
  
  
  METHODS
  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.
  
  
  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.
  
  
  CONCLUSIONS
  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.
authors.affiliation: Department of Anesthesiology, Faculty of Medicine, Chulalongkorn University, Bangkok 10330, Thailand.
authors.forename: Pavena
authors.initials: P
authors.lastname: Bunburaphong
authors.forename: Phornlert
authors.initials: P
authors.lastname: Chatrkaw
authors.forename: Pin
authors.initials: P
authors.lastname: Sriprachittichai
authors.forename: Kaew
authors.initials: K
authors.lastname: Supleornsug
authors.forename: Pornthip
authors.initials: P
authors.lastname: Ultchaswadi
authors.forename: Nareerat
authors.initials: N
authors.lastname: Sumetha-Aksorn
mesh_terms: D000046:Academic Medical Centers / Q000592:standards / Q000706:statistics & numerical data; D000293:Adolescent; D000328:Adult; D017677:Age Distribution; D000368:Aged; D000369:Aged, 80 and over; D002423:Cause of Death; D016001:Confidence Intervals; D005260:Female; D013502:General Surgery; D017052:Hospital Mortality / Q000639:trends*; D006801:Humans; D015994:Incidence; D007362:Intensive Care Units / Q000592:standards / Q000706:statistics & numerical data*; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D015999:Multivariate Analysis; D011237:Predictive Value of Tests; D011336:Probability; D012189:Retrospective Studies; D012307:Risk Factors; D012720:Severity of Illness Index; D017678:Sex Distribution; D013785:Thailand / Q000453:epidemiology