title: Landmark prediction of nosocomial infection risk to disentangle short- and long-stay patients.
abstract: Length of stay is one of the key determinants for the risk of nosocomial infections. The distribution of this at-risk time is heavily skewed and depends on discharge or death. This study applied landmark competing risk prediction models to account for a large proportion of short-stay patients and a small proportion of long-stay patients.
authors.affiliation: Institute for Medical Biometry and Statistics, Medical Centre, University of Freiburg, Freiburg, Germany; Freiburg Centre of Data Analysis and Modelling, Albert-Ludwigs University Freiburg, Germany. Electronic address: wolke@imbi.uni-freiburg.de.
authors.forename: M
authors.initials: M
authors.lastname: Wolkewitz
authors.affiliation: Institute for Medical Biometry and Statistics, Medical Centre, University of Freiburg, Freiburg, Germany.
authors.forename: M
authors.initials: M
authors.lastname: Zortel
authors.affiliation: Hospital Universitari Arnau de Vilanova, Lleida, Universitat Autonoma de Barcelona, Spain.
authors.forename: M
authors.initials: M
authors.lastname: Palomar-Martinez
authors.affiliation: Service of Intensive Care Medicine, Parc de Salut Mar, Barcelona, Spain.
authors.forename: F
authors.initials: F
authors.lastname: Alvarez-Lerma
authors.affiliation: Service of Intensive Care Medicine, Hospital de Galdakao-Usansolo, Bizkaia, Spain.
authors.forename: P
authors.initials: P
authors.lastname: Olaechea-Astigarraga
authors.affiliation: Institute for Medical Biometry and Statistics, Medical Centre, University of Freiburg, Freiburg, Germany.
authors.forename: M
authors.initials: M
authors.lastname: Schumacher
mesh_terms: D003428:Cross Infection / Q000453:epidemiology* / Q000401:mortality; D006305:Health Status Indicators; D017052:Hospital Mortality / Q000639:trends; D006801:Humans; D007362:Intensive Care Units; D007902:Length of Stay / Q000706:statistics & numerical data / Q000639:trends*; D010351:Patient Discharge / Q000706:statistics & numerical data; D012121:Respiration, Artificial / Q000009:adverse effects / Q000401:mortality; D012307:Risk Factors; D012720:Severity of Illness Index; D013030:Spain / Q000453:epidemiology
keywords: Competing risks; Hospital mortality; Hospital-acquired infections; Length of stay; Time-to-event analysis