title: Acute respiratory distress syndrome in nontrauma surgical patients: a 6-year study.
abstract: BACKGROUND
  Acute respiratory distress syndrome (ARDS) has been shown to increase morbidity but not mortality in trauma patients; however, little is known about the effects of ARDS in nontrauma surgical patients. The purpose of this study is to evaluate the risk factors for and outcomes of ARDS in nontrauma surgical patients.
  
  
  METHODS
  A prospective observational study was performed in the surgical intensive care unit (ICU) of an academic tertiary care center. From 2000 to 2005, all nontrauma surgical admissions to the surgical ICU were evaluated daily for ARDS based on predefined diagnostic criteria. Logistic regression analysis identified independent predictors for ARDS and ICU mortality.
  
  
  RESULTS
  Of 2,046 patient identified, 125 (6.1%) met criteria for ARDS. The incidence of ARDS declined annually from 12.2% to 2.1% during the study period (p < 0.001). ARDS patients were significantly older (55.4 years vs. 51.8 years, p = 0.014) and more likely to be obese (32% vs. 22%, p = 0.007) than the non-ARDS population. Independent predictors of ARDS included use of pressors (relative risk, RR = 3.30), sepsis (RR = 1.72), and body mass index >or=30 kg/m (RR = 1.57). Independent predictors of ICU mortality included ARDS (RR = 6.88), pressors (RR = 2.85), positive fluid balance (RR = 2.27), Acute Physiology and Chronic Health Evaluation II (RR = 1.04), and age (RR = 1.02).
  
  
  CONCLUSIONS
  Unlike trauma patients, ARDS was an independent predictor of ICU mortality in nontrauma surgical patients, independent of age and disease severity. Nontrauma surgical patients who developed ARDS were older, sicker, and had a longer ICU stay. Independent predictors of ARDS included use of pressors, sepsis, and obesity.
authors.affiliation: Department of Surgery, Cedars-Sinai Medical Center, 8730 Alden Drive, Thalians Bldg. W222, Los Angeles, CA 90048, USA. shirin.towfigh@cshs.org
authors.forename: Shirin
authors.initials: S
authors.lastname: Towfigh
authors.forename: Maria V
authors.initials: MV
authors.lastname: Peralta
authors.forename: Matthew J
authors.initials: MJ
authors.lastname: Martin
authors.forename: Ali
authors.initials: A
authors.lastname: Salim
authors.forename: Rebecca
authors.initials: R
authors.lastname: Kelso
authors.forename: Helen
authors.initials: H
authors.lastname: Sohn
authors.forename: Thomas V
authors.initials: TV
authors.lastname: Berne
authors.forename: Rodney J
authors.initials: RJ
authors.lastname: Mason
mesh_terms: D000704:Analysis of Variance; D015992:Body Mass Index; D016009:Chi-Square Distribution; D015897:Comorbidity; D005260:Female; D006801:Humans; D015994:Incidence; D007362:Intensive Care Units; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D011237:Predictive Value of Tests; D011446:Prospective Studies; D012128:Respiratory Distress Syndrome / Q000453:epidemiology* / Q000401:mortality; D012307:Risk Factors; D013514:Surgical Procedures, Operative