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Table 2. Time-Related Factors Associated With Ventilator-Associated Pneumonia (VAP) and Extubationa
Extubation VAP Rate Variable HR (95% CI)
(w/o VAP) Rate HR (95% CI)
Time in ICU before mechanical ventilation 1 vs 0 d 2 vs 0 d
3–4 vs 0 d >4 vs 0 d
VAP Risk sHR (95% CI)
1.17 (1.04–1.32) 0.74 (0.71–0.77) 1.60 (1.42–1.81) 1.21 (1.02–1.42) 0.65 (0.61–0.68) 1.92 (1.64–2.24) 1.39 (1.20–1.62) 0.63 (0.60–0.66) 2.17 (1.87–2.51) 0.89 (0.78–1.01) 0.61 (0.59–0.63) 1.49 (1.31–1.69)
Time in hospital before ICU admission 4–6vs 0–3 d 0.94 (0.81–1.09) 0.95 (0.92–0.99) 0.98 (0.84–1.14) 6–10 vs 0–3 d 1.02 (0.87–1.19) 0.94 (0.91–0.98) 1.06 (0.91–1.25) > 10 vs 0–3 d 0.85 (0.75–0.96) 0.95 (0.92–0.97) 0.89 (0.79–1.00) Ventilation episode Second vs first 0.99 (0.87–1.12) 0.66 (0.64–0.68) 1.52 (1.35–1.72) Third vs first
Martin Wolkewitz et al
terms of cumulative risk for VAP (see sHRs in Table 2). Thus, the cumulative risk for VAP increased by 117% for patients who stayed 3–4 days in the ICU before ventilation compared to the reference (adjusted sHR, 2.17; 95% CI, 1.87–2.51). In contrast, such a trend is not observed for the time spent in the hospital before ICU admis- sion, even though patients with longer hospitalizations before ICU admission tend to stay intubated longer without VAP development (Table 2). Figure 4 (left) shows the cumulative risks for VAP stratified
by time in the ICU before mechanical ventilation. These effects correspond to the unadjusted sHR. For instance, for patients who stayed 3–4 days in the ICU before ventilation, the sHR is 2.03 (95% CI, 1.76–2.33) compared to reference. Figure 5 shows the cumulative risks for VAP stratified by first,
0.87 (0.58–1.30) 0.54 (0.49–0.59) 1.54 (1.03–2.30)
Note. HR, hazard ratio; sHR, subdistribution hazard ratio; ICU, intensive care unit. aAll (subdistribution) hazard ratios are adjusted for APACHE II score, age, diagnosis (respi-
ratory, gastrointestinal, central nervous system, cardiovascular and other diagnoses), anti- biotic treatment 48 h before and/or after ICU admission, gender and trauma; stratified for intensive care units. Analysis is based on 48,705 ventilation episodes of 45,486 patients.
cumulative risk of extubation is estimated (Fig. 3, right, black line), and the duration-dependent proportion of ventilated patients have been extubated by duration day t. For instance, after duration day 15, ∼6% of ventilated patients have acquired a VAP whereas ∼80% have been extubated without VAP. The sum of the 2 black curves in Figure 3 do not exceed 100%; thus, the remaining∼14%is the pro- portion of ventilated patients who are still ventilated after 15 days. In contrast, the 1-Kaplan-Meier estimates predicts a biased VAP risk of ∼20% at day 15 (Fig. 3,left, gray line) and∼85%for extubation (Fig. 3, right, gray line); thus, the sumalready exceeds 100%. This commonly used approachhandles extubatedpatients asnoninformative censored observations. The estimated cumulative risk forVAPis biased upward because the underlying model of noninformative censoring assumes that extubated patients have the same VAP hazard as intubated patients. This assumption is contradicted by the definition of VAP.
Regression models
The event-specific Cox regression models provide hazard ratios (HRs) for VAP and extubation (Table 2). Regarding the VAP event, the time in ICU before mechanical ventilation is associated with an increased VAP hazard rate. For instance, the hazard for VAP increased by 39%for patientswho stayed 3–4 days in the ICUbefore ventilation compared to patients who received ventilation at the day of ICU admission (adjusted HR, 1.39; 95% CI, 1.20–1.62). In other words, the longer a patient has stayed in ICU before tube insertion the higher the daily risk to acquire a VAP (direct effect). Furthermore, the competing-risk analysis for the other event shows that the time in ICU before ventilation is also associated with an decreased extubation rate. For instance, patientswho stayed 3–4days in ICU before ventilation have a 37% lower discharge hazard com- pared to patients who received ventilation at the day of ICU admis- sion (adjustedHR, 0.63; 95%CI, 0.60–0.66). Thus, patients with long stays before tube insertion require longer intubations. Hence, this indirectprolongation of intubationincreases the at-risk time to even- tually acquire VAP. Therefore, the effect is more pronounced in
second, and third ventilation episodes and indicate the increased risk of the second and third episodes. The corresponding unad- justed sHR was 1.52 (95% CI, 1.35–1.72) comparing the second episode versus the first episode and the sHR was 1.47 (95% CI, 0.99–2.18) comparing the third episode versus the first episode. These effects remained stable after adjusting for the potential confounders APACHE II score, age, gender, trauma, diagnosis, antibiotic treatment, and calendar year of admission. The corre- sponding adjusted sHRs in Table 2 are 1.52 (95% CI, 1.35–1.72) for the second versus the first episode and 1.54 (95% CI, 1.03–2.30) for the third versus the first episode. Finally, we emphasize that it is a common practice to interpret
the HRs for VAP as risk ratios. However, as demonstrated here, risk factors have often strong indirect effects on extubation; thus, VAP hazard ratios usually differ from the sHRs, which do actually compare risks.
Discussion
To our knowledge, this is the first competing-risk analysis for VAP to study the impact of hospitalization/ICU stay, duration of ven- tilation, and multiple episodes in a large intensive care population. In competing-risks settings, the summary effect of a risk factor can be decomposed into 2 effects: a direct effect regarding the event of interest (ie, VAP) and an indirect effect regarding the competing event (ie, extubation).14 Thus, a competing-risk analysis is neces- sary to quantify the indirect effect of intubation time on the cumu- lative VAP risk. We found that time in ICU before mechanical ventilation is directly associated with an increased VAP hazard as well as indirectly with a decreased extubation hazard. No such effects have been detected for the time spent in hospital before ICU admission. We also found that multiple episodes have an indirect effect on the risk for VAP due to prolonged ventilation. Accounting for extubation as a competing event for VAP is also necessary to estimate cumulative risk of VAP depending on dura- tion of ventilation. In contrast, treating extubation as censored leads to values that could be interpreted as the hypothetical ‘prob- ability of VAP by duration of ventilation if the possibility of extu- bation could be removed.’ This is a highly controversial approach with a debatable assumption.15 We estimated the hazard rate for VAP depending on duration
of ventilation. Our findings coincide with some published results. For instance, Cook10 found that the hazard rate for VAP decreased over time: VAP rates were ∼3% per day in the first week of ven- tilation, 2% per day in the second week, and 1% per day in the third week and thereafter. In their study, early-onset VAP accounted for as many as 50% of cases of VAP. We estimated a similar shape of the VAP hazard rate. However, we emphasize that the estimation
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