title: Nutrition screening tools and the prediction of postoperative infectious and wound complications: comparison of methods in presence of risk adjustment.
abstract: OBJECTIVE
  We compared four nutritional screening tools, the Nutrition Risk Classification, the Mini-Nutrition Assessment-Short Form, the Malnutrition Screening Tool, and the Nutrition Risk Score in terms of their ability to predict postoperative wound and infectious complications when adjusted for the effects of other risk factors for postoperative infection.
  
  
  METHODS
  The 8-mo study was performed on 430 patients undergoing abdominal surgery. Data on the Nutrition Risk Classification, Mini-Nutrition Assessment-Short Form, Malnutrition Screening Tool, Nutrition Risk Score, and risk factors for postoperative complications were collected for all patients. Patients were followed until 30 d after surgery. Nutritional screening tools were compared for their ability to predict postoperative complications by using the area under the receiver operating characteristic curve. Multivariable adjustment for other risk factors was done with multiple logistic regression analysis.
  
  
  RESULTS
  The Mini-Nutrition Assessment-Short Form, Nutrition Risk Score, and Nutrition Risk Classification had the larger receiver operating characteristic areas. Only the Nutrition Risk Classification was significantly related to the occurrence of postoperative complications (odds ratio 2.92, 95% confidence interval 1.62 to 5.26) after adjusting for other risk factors of postoperative infection. The other remaining risk factors were serum albumin level and operative time.
  
  
  CONCLUSIONS
  The Nutrition Risk Classification seems to be the best nutritional screening tool for use in predicting postoperative infectious and wound complications.
authors.affiliation: Department of Nursing, Faculty of Medicine, Ramathibodi Hospital, Mahidol University, Bangkok, Thailand. rappw@mahidol.ac.th
authors.forename: Panwadee
authors.initials: P
authors.lastname: Putwatana
authors.forename: Pinmanee
authors.initials: P
authors.lastname: Reodecha
authors.forename: Yupapin
authors.initials: Y
authors.lastname: Sirapo-ngam
authors.forename: Panuwat
authors.initials: P
authors.lastname: Lertsithichai
authors.forename: Kanit
authors.initials: K
authors.lastname: Sumboonnanonda
mesh_terms: D000005:Abdomen / Q000601:surgery*; D016001:Confidence Intervals; D005260:Female; D006801:Humans; D016015:Logistic Models; D008297:Male; D008403:Mass Screening; D008875:Middle Aged; D015596:Nutrition Assessment; D009748:Nutrition Disorders / Q000150:complications / Q000175:diagnosis*; D016017:Odds Ratio; D011183:Postoperative Complications / Q000453:epidemiology*; D011237:Predictive Value of Tests; D012372:ROC Curve; D018570:Risk Assessment; D012307:Risk Factors; D012709:Serum Albumin / Q000032:analysis; D013530:Surgical Wound Infection / Q000453:epidemiology*
chemical_list: D012709:Serum Albumin