title: Bayesian analysis of nosocomial infection risk and length of stay in a department of general and digestive surgery.
abstract: OBJECTIVE
  Nosocomial infection is one of the main causes of morbidity and mortality in patients admitted to hospital. One aim of this study is to determine its intrinsic and extrinsic risk factors. Nosocomial infection also increases the duration of hospital stay. We quantify, in relative terms, the increased duration of the hospital stay when a patient has the infection.
  
  
  METHODS
  We propose the use of logistic regression models with an asymmetric link to estimate the probability of a patient suffering a nosocomial infection. We use Poisson-Gamma regression models as a multivariate technique to detect the factors that really influence the average hospital stay of infected and noninfected patients. For both models, frequentist and Bayesian estimations were carried out and compared.
  
  
  RESULTS
  The models are applied to data from 1039 patients operated on in a Spanish hospital. Length of stay, the existance of a preoperative stay and obesity were found the main risk factors for a nosomial infection. The existence of a nosocomial infection multiplies the length of stay in the hospital by a factor of 2.87.
  
  
  CONCLUSIONS
  The results show that the asymmetric logit improves the predictive capacity of conventional logistic regressions.
authors.affiliation: Department of Statistics and Operational Research, University of Jaén, Spain.
authors.forename: Antonio José
authors.initials: AJ
authors.lastname: Sáez-Castillo
authors.forename: María José
authors.initials: MJ
authors.lastname: Olmo-Jiménez
authors.forename: José María
authors.initials: JM
authors.lastname: Pérez Sánchez
authors.forename: Miguel Angel
authors.initials: MA
authors.lastname: Negrín Hernández
authors.forename: Angel
authors.initials: A
authors.lastname: Arcos-Navarro
authors.forename: Juan
authors.initials: J
authors.lastname: Díaz-Oller
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D001499:Bayes Theorem; D002648:Child; D003428:Cross Infection / Q000453:epidemiology*; D005260:Female; D006801:Humans; D007902:Length of Stay; D016013:Likelihood Functions; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D015233:Models, Statistical; D015999:Multivariate Analysis; D015203:Reproducibility of Results; D018570:Risk Assessment / Q000706:statistics & numerical data*; D013030:Spain / Q000453:epidemiology; D013514:Surgical Procedures, Operative / Q000009:adverse effects