Literature DB >> 16671031

Use of multistate models to assess prolongation of intensive care unit stay due to nosocomial infection.

J Beyersmann1, P Gastmeier, H Grundmann, S Bärwolff, C Geffers, M Behnke, H Rüden, M Schumacher.   

Abstract

BACKGROUND: Reliable data on the costs attributable to nosocomial infection (NI) are crucial to demonstrating the real cost-effectiveness of infection control measures. Several studies investigating this issue with regard to intensive care unit (ICU) patients have probably overestimated, as a result of inappropriate study methods, the part played by NIs in prolonging the length of stay.
METHODS: Data from a prospective study of the incidence of NI in 5 ICUs over a period of 18 months formed the basis of this analysis. For describing the temporal dynamics of the data, a multistate model was used. Thus, ICU patients were counted as case patients as soon as an NI was ascertained on any particular day. All patients were then regarded as control subjects as long as they remained free of NI (time-to-event data analysis technique).
RESULTS: Admitted patients (n=1,876) were observed for the development of NI over a period of 28,498 patient-days. In total, 431 NIs were ascertained during the study period (incidence density, 15.1 NIs per 1,000 patient-days). The influence of NI as a time-dependent covariate in a proportional hazards model was highly significant (P< .0001, Wald test). NI significantly reduced the discharge hazard (hazard ratio, 0.72 [95% confidence interval, 0.63-0.82])--that is, it prolonged the ICU stay. The mean prolongation of ICU length of stay due to NI (+/- standard error) was estimated to be 5.3+/-1.6 days.
CONCLUSIONS: Further studies are required to enable comparison of data on prolongation of ICU length of stay with the results of various study methods.

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Year:  2006        PMID: 16671031     DOI: 10.1086/503375

Source DB:  PubMed          Journal:  Infect Control Hosp Epidemiol        ISSN: 0899-823X            Impact factor:   3.254


  36 in total

1.  Attributable mortality of ventilator-associated pneumonia: respective impact of main characteristics at ICU admission and VAP onset using conditional logistic regression and multi-state models.

Authors:  Molière Nguile-Makao; Jean-Ralph Zahar; Adrien Français; Alexis Tabah; Maité Garrouste-Orgeas; Bernard Allaouchiche; Dany Goldgran-Toledano; Elie Azoulay; Christophe Adrie; Samir Jamali; Christophe Clec'h; Bertrand Souweine; Jean-Francois Timsit
Journal:  Intensive Care Med       Date:  2010-03-16       Impact factor: 17.440

2.  Modeling the effect of time-dependent exposure on intensive care unit mortality.

Authors:  Martin Wolkewitz; Jan Beyersmann; Petra Gastmeier; Martin Schumacher
Journal:  Intensive Care Med       Date:  2009-01-31       Impact factor: 17.440

3.  Nested exposure case-control sampling: a sampling scheme to analyze rare time-dependent exposures.

Authors:  Jan Feifel; Madlen Gebauer; Martin Schumacher; Jan Beyersmann
Journal:  Lifetime Data Anal       Date:  2018-11-13       Impact factor: 1.588

Review 4.  [Nosocomial pneumonia from a radiological perspective].

Authors:  P Agarwal; A Wielandner
Journal:  Radiologe       Date:  2017-01       Impact factor: 0.635

5.  A competing risks approach for nonparametric estimation of transition probabilities in a non-Markov illness-death model.

Authors:  Arthur Allignol; Jan Beyersmann; Thomas Gerds; Aurélien Latouche
Journal:  Lifetime Data Anal       Date:  2013-06-27       Impact factor: 1.588

6.  Incidence in ICU populations: how to measure and report it?

Authors:  Jan Beyersmann; Petra Gastmeier; Martin Schumacher
Journal:  Intensive Care Med       Date:  2014-05-10       Impact factor: 17.440

7.  A model-informed rank test for right-censored data with intermediate states.

Authors:  Ritesh Ramchandani; Dianne M Finkelstein; David A Schoenfeld
Journal:  Stat Med       Date:  2015-01-13       Impact factor: 2.373

8.  Nosocomial infections and multidrug-resistant organisms in Germany: epidemiological data from KISS (the Hospital Infection Surveillance System).

Authors:  Christine Geffers; Petra Gastmeier
Journal:  Dtsch Arztebl Int       Date:  2011-02-11       Impact factor: 5.594

9.  A predictive model for the early identification of patients at risk for a prolonged intensive care unit length of stay.

Authors:  Andrew A Kramer; Jack E Zimmerman
Journal:  BMC Med Inform Decis Mak       Date:  2010-05-13       Impact factor: 2.796

10.  Cost-effectiveness of linezolid vs vancomycin in suspected methicillin-resistant Staphylococcus aureus nosocomial pneumonia in Germany.

Authors:  E De Cock; W A Krueger; S Sorensen; T Baker; J Hardewig; S Duttagupta; E Müller; A Piecyk; E Reisinger; A Resch
Journal:  Infection       Date:  2009-03-09       Impact factor: 3.553

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