Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/52370
Title: Bayesian analysis of nosocomial infection risk and length of stay in a department of general and digestive surgery
Authors: Sáez-Castillo, Antonio José
Olmo-Jiménez, María José
Pérez Sánchez, José María 
Negrín Hernández, Miguel Ángel 
Arcos-Navarro, Ángel
Díaz-Oller, Juan
Keywords: Hospital-Acquired Infections
Logistic-Regression
Response Data
Models
Prevalence, et al
Issue Date: 2010
Publisher: 1098-3015
Journal: Value in Health 
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.Conclusion: The results show that the asymmetric logic improves the predictive capacity of conventional logistic regressions
URI: http://hdl.handle.net/10553/52370
ISSN: 1098-3015
DOI: 10.1111/j.1524-4733.2009.00680.x
Source: Value in Health[ISSN 1098-3015],v. 13, p. 431-439
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