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

Nguile-Makao, Moliere, Zahar, Jean-Ralph, Francais, Adrien, Tabah, Alexis, Garrouste-Orgeas, Maite, Allaouchiche, Bernard, Goldgran-Toledano, Dany, Azoulay, Elie, Adrie, Christophe, Jamali, Samir, Clec'h, Christophe, Souweine, Bertrand and Timsit, Jean-Francois (2010) 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. Intensive Care Medicine, 36 5: 781-789. doi:10.1007/s00134-010-1824-6


Author Nguile-Makao, Moliere
Zahar, Jean-Ralph
Francais, Adrien
Tabah, Alexis
Garrouste-Orgeas, Maite
Allaouchiche, Bernard
Goldgran-Toledano, Dany
Azoulay, Elie
Adrie, Christophe
Jamali, Samir
Clec'h, Christophe
Souweine, Bertrand
Timsit, Jean-Francois
Title 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
Journal name Intensive Care Medicine   Check publisher's open access policy
ISSN 0342-4642
1432-1238
Publication date 2010-05
Sub-type Article (original research)
DOI 10.1007/s00134-010-1824-6
Open Access Status Not yet assessed
Volume 36
Issue 5
Start page 781
End page 789
Total pages 9
Place of publication Heidelberg, Germany
Publisher Springer
Language eng
Formatted abstract
Purpose: Methods for estimating the excess mortality attributable to ventilator-associated pneumonia (VAP) should handle VAP as a time-dependent covariate, since the probability of experiencing VAP increases with the time on mechanical ventilation. VAP-attributable mortality (VAP-AM) varies with definitions, case-mix, causative microorganisms, and treatment adequacy. Our objectives here were to compare VAP-AM estimates obtained using a traditional cohort analysis, a multistate progressive disability model, and a matched-cohort analysis; and to compare VAP-AM estimates according to VAP characteristics.

Methods: We used data from 2,873 mechanically ventilated patients in the Outcomerea® database. Among these patients from 12 intensive care units, 434 (15.1%) experienced VAP; of the remaining patients, 1,969 (68.5%) were discharged alive and 470 (16.4%) died. With the multistate model, VAP-AM was 8.1% (95% confidence interval [95%CI], 3.1-13.1%) for 120 days' complete observation, compared to 10.4% (5.6-24.5%) using a matched-cohort approach (2,769 patients) with matching on mechanical ventilation duration followed by conditional logistic regression. VAP-AM was higher in surgical patients and patients with intermediate (but not high) Simplified Acute Physiologic Score II values at ICU admission. VAP-AM was significantly influenced by time to VAP but not by resistance of causative microorganisms. Higher Logistic Organ Dysfunction score at VAP onset dramatically increased VAP-AM (to 31.9% in patients with scores above 7).

Conclusion: A multistate model that appropriately handled VAP as a time-dependent event produced lower VAP-AM values than conditional logistic regression. VAP-AM varied widely with case-mix. Disease severity at VAP onset markedly influenced VAP-AM; this may contribute to the variability of previous estimates.
Keyword Benchmarking
Critically ill
Logistic regression
Multistate models
Nosocomial pneumonia
Q-Index Code C1
Q-Index Status Provisional Code
Institutional Status Non-UQ

Document type: Journal Article
Sub-type: Article (original research)
Collection: School of Medicine Publications
 
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