title: Indices of surgical site infection risk and prediction of other adverse outcomes during hospitalization.
abstract: OBJECTIVE
  To assess which adverse postsurgical outcomes are best predicted by the Study on the Efficacy of Nosocomial Infection Control (SENIC) index and the National Nosocomial Infection Surveillance system (NNIS) index.
  
  
  METHODS
  Prospective cohort study.
  
  
  METHODS
  The service of general surgery at a tertiary care hospital.
  
  
  METHODS
  A consecutive series of patients hospitalized for more than 1 day (n=2,989).
  
  
  RESULTS
  The outcome best predicted by the SENIC and NNIS indices was assessed by estimating the area under the receiver operating characteristic (ROC) curve. The areas under the ROC curves for nosocomial infection and in-hospital death were higher for the NNIS index than they were for the SENIC index (P<.05). The NNIS index predicted in-hospital death better than it predicted surgical site infection (area under the ROC curve+/-SE, 0.836+/-0.022 vs 0.689+/-0.017; P=.001).
  
  
  CONCLUSIONS
  The NNIS index is superior to the SENIC index for all adverse postsurgical outcomes. Its ability to predict in-hospital mortality is clearly better than its ability to predict surgical site infection.
authors.affiliation: Division of Preventive Medicine, University of Jaen, Jaen, Spain. mdelgado@ujaen.es
authors.forename: Miguel
authors.initials: M
authors.lastname: Delgado-Rodríguez
authors.forename: Silvia
authors.initials: S
authors.lastname: Palma
authors.forename: Antonio
authors.initials: A
authors.lastname: Gómez-Ortega
authors.forename: Gabriel
authors.initials: G
authors.lastname: Martínez-Gallego
authors.forename: Marcelino
authors.initials: M
authors.lastname: Medina-Cuadros
mesh_terms: D015331:Cohort Studies; D017052:Hospital Mortality; D006760:Hospitalization; D016015:Logistic Models; D011237:Predictive Value of Tests; D011446:Prospective Studies; D018570:Risk Assessment; D012720:Severity of Illness Index; D013503:Surgery Department, Hospital / Q000706:statistics & numerical data*; D013530:Surgical Wound Infection / Q000453:epidemiology* / Q000401:mortality