title: Hospital-acquired infections--appropriate statistical treatment is urgently needed!
abstract: Research on hospital-acquired infections (HAIs) requires the highest methodological standards to minimize the risk of bias and to avoid misleading interpretation. There are two major issues related specifically to studies in this area, namely the timing of infection and the occurrence of so-called competing risks, which deserve special attention. Just as a patient who acquires a serious infection during hospital admission needs appropriate antibiotic treatment, data being collected in studies on hospital-acquired infections need appropriate statistical analysis. We illustrate the urgent need for appropriate statistical treatment of hospital-acquired infections with some examples from recently conducted studies.The considerations presented are relevant for investigations on risk factors for HAIs as well as for outcome studies.
authors.affiliation: Institute of Medical Biometry and Medical Informatics, University Medical Center Freiburg, Freiburg, Germany and Institute of Statistics, Ulm University, Ulm, Germany.
authors.forename: Martin
authors.initials: M
authors.lastname: Schumacher
authors.forename: Arthur
authors.initials: A
authors.lastname: Allignol
authors.forename: Jan
authors.initials: J
authors.lastname: Beyersmann
authors.forename: Nadine
authors.initials: N
authors.lastname: Binder
authors.forename: Martin
authors.initials: M
authors.lastname: Wolkewitz
mesh_terms: D015331:Cohort Studies; D003428:Cross Infection / Q000453:epidemiology*; D006801:Humans; D007362:Intensive Care Units; D007902:Length of Stay; D015233:Models, Statistical; D018410:Pneumonia, Bacterial / Q000453:epidemiology*; D016016:Proportional Hazards Models; D012307:Risk Factors; D013223:Statistics as Topic; D013997:Time Factors
keywords: Hospital-acquired infections; cohort studies; competing risks; length bias; time-dependent bias