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Intensive Care Med. 2009 May;35(5):826-32. doi: 10.1007/s00134-009-1423-6. Epub 2009 Jan 31.

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

Author information

1
Institute of Medical Biometry and Medical Informatics, University Medical Center Freiburg, Stefan-Meier-Strasse 26, 79104 Freiburg, Germany. wolke@fdm.uni-freiburg.de

Abstract

PURPOSE:

To illustrate modern survival models with focus on the temporal dynamics of intensive care data. A typical situation is given in which time-dependent exposures and competing events are present.

METHODS:

We briefly review the following established statistical methods: logistic regression, regression models for event-specific hazards and the subdistribution hazard. These approaches are compared by showing advantages as well as disadvantages. All methods are applied to real data from a study of day-by-day ICU surveillance.

RESULTS:

Standard logistic regression ignores the time-dependent nature of the data and is only a crude approach. Cumulative hazards and probability plots add important information and provide a deep insight into the temporal dynamics.

CONCLUSION:

This paper might help to encourage researchers working in hospital epidemiology to apply adequate statistical models to complex medical questions.

PMID:
19183943
DOI:
10.1007/s00134-009-1423-6
[Indexed for MEDLINE]

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