Epidemiology of healthcare-associated Pseudomonas aeruginosa in intensive care units: are sink drains to blame?

BACKGROUND

Pseudomonas aeruginosa (PA) is a common cause of healthcare-associated infection (PA-HAI) in the intensive care unit (ICU).

AIM

To describe the epidemiology of PA-HAI in ICUs in Ontario, Canada, and to identify episodes of sink-to-patient PA transmission.

METHODS

This was a prospective cohort study of patients in six ICUs from 2018 to 2019, with retrieval of PA clinical isolates, and PA-screening of antimicrobial-resistant organism surveillance rectal swabs, and of sink drain, air, and faucet samples. All PA isolates underwent whole-genome sequencing. PA-HAI was defined using US National Healthcare Safety Network criteria. ICU-acquired PA was defined as PA isolated from specimens obtained ≥48 h after ICU admission in those with prior negative rectal swabs. Sink-to-patient PA transmission was defined as ICU-acquired PA with close genomic relationship to isolate(s) previously recovered from sinks in a room/bedspace occupied 3-14 days prior to collection date of the relevant patient specimen.

FINDINGS

Over ten months, 72 PA-HAIs occurred among 60/4263 admissions. The rate of PA-HAI was 2.40 per 1000 patient-ICU-days; higher in patients who were PA-colonized on admission. PA-HAI was associated with longer stay (median: 26 vs 3 days uninfected; P < 0.001) and contributed to death in 22/60 cases (36.7%). Fifty-eight admissions with ICU-acquired PA were identified, contributing 35/72 (48.6%) PA-HAIs. Four patients with five PA-HAIs (6.9%) had closely related isolates previously recovered from their room/bedspace sinks.

CONCLUSION

Nearly half of PA causing HAI appeared to be acquired in ICUs, and 7% of PA-HAIs were associated with sink-to-patient transmission. Sinks may be an under-recognized reservoir for HAIs.

Uncertainty in the response of terrestrial carbon sink to environmental drivers undermines carbon-climate feedback predictions

Terrestrial ecosystems play a vital role in regulating the accumulation of carbon (C) in the atmosphere. Understanding the factors controlling land C uptake is critical for reducing uncertainties in projections of future climate. The relative importance of changing climate, rising atmospheric CO2, and other factors, however, remains unclear despite decades of research. Here, we use an ensemble of land models to show that models disagree on the primary driver of cumulative C uptake for 85% of vegetated land area. Disagreement is largest in model sensitivity to rising atmospheric CO2 which shows almost twice the variability in cumulative land uptake since 1901 (1 s.d. of 212.8 PgC vs. 138.5 PgC, respectively). We find that variability in CO2 and temperature sensitivity is attributable, in part, to their compensatory effects on C uptake, whereby comparable estimates of C uptake can arise by invoking different sensitivities to key environmental conditions. Conversely, divergent estimates of C uptake can occur despite being based on the same environmental sensitivities. Together, these findings imply an important limitation to the predictability of C cycling and climate under unprecedented environmental conditions. We suggest that the carbon modeling community prioritize a probabilistic multi-model approach to generate more robust C cycle projections.