Temporal airway microbiome changes related to ventilator-associated pneumonia in children

Abstract

We sought to determine whether temporal changes in the lower airway microbiome are associated with ventilator-associated pneumonia (VAP) in children.Using a multicentre prospective study of children aged 31 days to 18 years requiring mechanical ventilation support for >72 h, daily tracheal aspirates were collected and analysed by sequencing of the 16S rRNA gene. VAP was assessed using 2008 Centers for Disease Control and Prevention paediatric criteria. The association between microbial factors and VAP was evaluated using joint longitudinal time-to-event modelling, matched case-control comparisons and unsupervised clustering.Out of 366 eligible subjects, 66 (15%) developed VAP at a median of 5 (interquartile range 3-5) days post intubation. At intubation, there was no difference in total bacterial load (TBL), but Shannon diversity and the relative abundance of Streptococcus, Lactobacillales and Prevotella were lower for VAP subjects versus non-VAP subjects. However, higher TBL on each sequential day was associated with a lower hazard (hazard ratio 0.39, 95% CI 0.23-0.64) for developing VAP, but sequential values of diversity were not associated with VAP. Similar findings were observed from the matched analysis and unsupervised clustering. The most common dominant VAP pathogens included Prevotella species (19%), Pseudomonas aeruginosa (14%) and Streptococcus mitis/pneumoniae (10%). Mycoplasma and Ureaplasma were also identified as dominant organisms in several subjects.In mechanically ventilated children, changes over time in microbial factors were marginally associated with VAP risk, although these changes were not suitable for predicting VAP in individual patients. These findings suggest that focusing exclusively on pathogen burden may not adequately inform VAP diagnosis.

Figure 1:

CONSORT diagram

Figure 2:. Comparison of beta diversity between VAP and non-VAP subjects in the supervised analytic cohort.

Plots A and C present the raw Morisita Horn (MH) values for each individual (grey lines) and the average trends for the VAP groups using smoothing splines (colored curves). Plots B and D include the estimates and the 95% confidence intervals from the mixed model. The solid lines are included in the CI for the other group, indicating there is no significant difference between groups. Plots A and B correspond to the MH between consecutively collected samples within an individual. Plots C and D correspond to the MH between each sample and the intubation sample for each subject. All plots exclude samples collected after VAP diagnosis for VAP subjects.

Figure 3.. Parameter estimates from the three joint models, each of which includes time to VAP and a microbial factor modeled over time as outcomes.

The joint model assumes a linear trend over time for the longitudinal outcomes and the current or sequential values for the microbial factor is included into the time to VAP diagnosis component of the model. Antibiotic exposure was measured in 4 ways: cumulative antibiotic coverage score indicates the overall broadest spectrum antibiotic coverage the patient received throughout the period of intubation up until the time the sample was collected, total antibiotic coverage score by day indicates the broadest spectrum coverage of antibiotic the patient received on the day the sample was collected, cumulative days of antibiotic exposure indicates number of antibiotics given during the time of intubation up until the sample was collected, and number of antibiotics by day indicates number of drugs given on the day of sample collection. A forest plot displaying the (A) parameter estimates from the longitudinal outcome component of the joint model for each of the microbial factors and (B) the hazard ratios from the time to VAP component of the joint model. These model estimates indicate that microbial factors change over time and with antibiotic exposure. Time to VAP diagnosis is associated with TBL. In the subset of subjects with sequencing data, younger age is associated with shorter time to VAP after adjusting PRISM III and microbial factors. After adjustment for time, antibiotic exposure, age and PRISM III score, only TBL was associated with development of VAP. Error bars correspond to 95% credible intervals from the joint model, intervals that exclude values of 0 in A or 1 in B are significantly associated with the variables listed on the y-axis. CrI: credible interval.

Figure 4:. Average trajectories of change in microbial factors reveal subtle statistical differences between subjects who developed VAP compared to subjects who did not develop VAP in the matched cohort.

Day 0 denotes day of diagnosis in VAP cases (n = 66) and the reference day of mechanical ventilation in controls (n=227; see supplement for details). Comparisons are displayed for Shannon Diversity (A) and Total Bacterial Load (B), Shannon Evenness not shown, for up to 3 days preceding Day 0. Comparison of diversity between VAP cases and controls at each of three days prior to Day 0 indicated a lower diversity in the VAP cases at day −2 prior to VAP diagnosis compared to controls (* indicate p-value < 0.05), however, significant differences were not present on days −3, −1 or 0.

Figure 5:. Clustering analysis does not reveal high-risk VAP phenotypes.

The patient clusters represented in Figure S8 are displayed by the dendrogram at the top of the figure. Outcomes (VAP, length of mechanical ventilation, mortality) for each subject are indicated using color bars underneath the corresponding terminal end of the dendrogram. The heatmap displays the relative abundance for the taxa identified in the sample either at VAP diagnosis for cases or 48 hours prior to extubation for non-VAP subjects. Subjects clustered together based on their clinical and microbial factors at intubation are displayed next to each other, the distance between subjects is indicated by the dendrogram at the top. There are no discernable differences in any clinical, treatment (antibiotic score; see supplementary material for details), or microbial factors that might explain why subjects in the same cluster develop VAP while others did not. Total bacterial load, richness, diversity, and evenness are presented for day of VAP diagnosis or 48 hours prior to extubation in non-VAP subjects. Abbreviations LOS: length of hospital stay, TBL: total bacterial load, Length MV: Length of mechanical ventilation, Mortality: in-hospital mortality, VAP: ventilator associated pneumonia, RA: relative abundance.