Literature DB >> 30198195

Estimation of adjusted expected excess length-of-stay associated with ventilation-acquired pneumonia in intensive care: A multistate approach accounting for time-dependent mechanical ventilation.

Tobias Bluhmki1, Arthur Allignol2, Stephane Ruckly3, Jean-Francois Timsit3,4, Martin Wolkewitz5, Jan Beyersmann1.   

Abstract

The expected excess length-of-stay is an established concept to assess the health and economic impact of nosocomial, that is, hospital-acquired infections such as ventilation-acquired pneumonia in intensive care. Estimation must account for the timing of infection as in a multistate perspective, because common retrospective comparisons yield inflated estimates due to time-dependent bias. Since occurrence of ventilation-acquired pneumonia is closely linked to ventilation status, we suggest a multistate model incorporating time-dependent mechanical ventilation as additional states. The appeal is that the expected excess length-of-stay decomposes into extra days spent under ventilation and not under ventilation. This is not only highly relevant from a patient's perspective regarding quality of life, but also from an economic point of view, because ventilation is a major cost driver. The challenge is that estimation involves complex functionals of the matrix of transition probabilities, which in turn are based on the transition hazards. To address heterogeneity between patients, which is a common phenomenon in observational hospital epidemiology, we apply pseudovalue regression to adjust the ventilation-specific quantities for baseline confounding. The performance of our proposal is assessed by simulation and the methods are illustrated on data provided by 12 French intensive care units. Preliminary results indicate that the expected excess length-of-stay associated with ventilation-acquired pneumonia is mainly triggered by extra days spent under mechanical ventilation, and that the excess is most pronounced for intensive care patients with fewer comorbidities at baseline. We also find that such a decomposition is challenging for early times. Example code is provided.
© 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Entities:  

Keywords:  Aalen-Johansen estimator; bootstrap; multistate model; nosocomial infection; pseudovalue regression

Mesh:

Year:  2018        PMID: 30198195     DOI: 10.1002/bimj.201700242

Source DB:  PubMed          Journal:  Biom J        ISSN: 0323-3847            Impact factor:   2.207


  2 in total

1.  Estimands to quantify prolonged hospital stay associated with nosocomial infections.

Authors:  Martin Wolkewitz; Martin Schumacher; Gerta Rücker; Stephan Harbarth; Jan Beyersmann
Journal:  BMC Med Res Methodol       Date:  2019-05-31       Impact factor: 4.615

2.  Impact of mechanical ventilation on the daily costs of ICU care: a systematic review and meta regression.

Authors:  Klaus Kaier; Thomas Heister; Edith Motschall; Philip Hehn; Tobias Bluhmki; Martin Wolkewitz
Journal:  Epidemiol Infect       Date:  2019-12-05       Impact factor: 2.451

  2 in total

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