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.
OBJECTIVE
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).


CONCLUSIONS
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.
INSERM U823, University Grenoble 1, Albert Bonniot Institute, Grenoble, France.
Molière
M
Nguile-Makao
Jean-Ralph
JR
Zahar
Adrien
A
Français
Alexis
A
Tabah
Maité
M
Garrouste-Orgeas
Bernard
B
Allaouchiche
Dany
D
Goldgran-Toledano
Elie
E
Azoulay
Christophe
C
Adrie
Samir
S
Jamali
Christophe
C
Clec'h
Bertrand
B
Souweine
Jean-Francois
JF
Timsit
D016208:Databases, Factual; D005260:Female; D005602:France / Q000453:epidemiology; D017052:Hospital Mortality; D006801:Humans; D007362:Intensive Care Units / Q000458:organization & administration / Q000706:statistics & numerical data*; D007902:Length of Stay; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D010343:Patient Admission / Q000706:statistics & numerical data; D053717:Pneumonia, Ventilator-Associated / Q000401:mortality*; D011446:Prospective Studies; D012720:Severity of Illness Index