A new study from Jordan has reinforced that cross-resistance between biocides and antibiotics doesn’t seem to be a problem. The study found that although multidrug-resistant E. coli were commonly identified from the environment in both hospital and community settings, there was no evidence of cross-resistance between antibiotics and biocides, and all E. coli were susceptible to in-use concentrations of biocides.
21 of 430 environmental samples from two hospitals and 10 homes grew E. coli. Almost half of the isolates were multidrug-resistant, and two thirds were ESBL-producers by phenotype. Surprisingly, there was no difference in the rate of ESBL-producers between hospital and community isolates. Also, the MIC of biocides (including ethanol, chloroxylenol, cetrimide and iodine) were all below in-use concentrations, and similar between community and hospital isolates. Perhaps most importantly, there was no association between antibiotic and biocide susceptibility.
The potential association between biocide and antibiotic resistance has been reviewed in detail before. The European Union produced a report in 2009 concluding that there was limited evidence of biocide and antibiotic cross-resistance. This is because the mechanisms of action of antibiotics and biocides are fundamentally different. Antibiotics tend to have a very specific target, in interrupting the metabolism of bacterial cells, whereas biocides tend to have multiple physical targets and do not rely on interrupting metabolism to be effective. We need to keep an eye on the potential for cross-resistance between biocides and antibiotics – but for now, it is not a problem.
Our clinical team spent some time at ECCMID in Madrid last week, and have summarised some of the key updates from our point of view.
We hope you find this summary useful – please feel free to get in touch if you have any questions!
It is clear that sharing a room or multi-occupancy bay with a patient infected or colonised with an HCAI-related pathogen is a risk factor for acquisition. Indeed, the physical segregation of patients has been a key intervention to prevent the spread of infectious diseases since the advent of germ theory! The risk of acquiring pathogens from contamination left behind by a previous occupant of the same room or bed-space is less obvious, but one that is now widely recognised. However, which is greater? The risk from a current roommate, or the risk from a previous occupant of the same bed-space? Whilst you may think it would be the current roommate, a new study suggests that the risk from the previous room occupant may be greater!
The American research team performed a large case-control study, in a population of 760,000 patients across four hospitals in New York between 2006 and 2012. More that 10,000 patients developed an HCAI during this period, and these cases were matched with uninfected controls based on time, location, and length of stay. The key finding was that both exposure to a roommate or a previous room occupant with the same pathogen that caused the HCAI were risk factors for HCAI. Interestingly, exposure to a current room occupant increased the risk of HCAI 5-fold, whereas exposure to a previous room occupant increased the risk of acquisition 6-fold! Whilst the study was not designed to compare directly the increased risk from current roommates with previous room occupants, this finding suggests that exposure to a previous room occupant could be a greater risk for HCAI than exposure to a current roommate. One possible reason for this is that a current roommate with an HCAI is a more obvious, tangible risk for transmission, and so basic IPC practice and cleaning standards are higher. In contrast, a previous room occupant is an unseen risk, so cleaning standards are lower.
These findings reinforce the need to improve cleaning and disinfection of the clinical environment both during the stay of patients, and at the time of discharge to minimise the risk of HCAI.
Norovirus is a common cause of gastrointestinal diseases in hospitals and other ‘semi-closed’ environments (like cruise ships, prisons, and schools). A new study suggests that wards whether patients share multi-occupancy bays are more likely to experience norovirus outbreaks, and that the risk of norovirus transmission increases as more patients share a bay.
The factors driving norovirus transmission are poorly understood. This is because designing studies in norovirus transmission is difficult. Norovirus usually spreads in outbreak clusters, which are often contained using bundled interventions. So, it’s very difficult to understand which part of the bundle was effective in containing an outbreak – or, indeed, whether an outbreak would have stopped without any intervention at all! A new Swedish study reviewed outbreaks and a large number of sporadic norovirus cases in almost 200 wards across southern Sweden to understand risk factors for norovirus spread.
The study found that risk factors for norovirus transmission were: sharing a multi-occupancy with a norovirus case, vomiting, older age (>80 years), comorbidity, and hospital onset of symptoms. These factors remained significantly associated with norovirus transmission even when accounting for all variables together in a multivariable model. The more patients who shared a multi-occupancy bay, the greater the risk of norovirus spread: in fact, the risk doubled for each extra patient in the bay!
These findings suggest that improving the segregation of patients who become symptomatic with norovirus-like symptoms will help to prevent the spread of norovirus in hospitals.
Since the evidence base is limited, knowledge on what really works to prevent the transmission of pathogens that cause HCAI is limited. This is the case for C. difficile and other hospital pathogens. So, we commonly apply bundles of interventions, in the hope that one or more elements of the bundle will be effective. A recent modelling study helps us to break down the bundle to understand which elements are most effective for preventing C. difficile infection. Daily cleaning with a sporicidal disinfectant was the most effective intervention, reducing hospital-onset C. difficile infection by two thirds.
The study created a virtual 200 bed acute care hospital and modelled how 9 single interventions and 8 intervention bundles interrupted the spread of C. difficile between patients. The interventions and intervention bundles were either hospital-centred (e.g. daily or terminal cleaning, contact precautions for staff, and staff hand hygiene) or patient-centred (e.g. screening for asymptomatic colonisation or patient hand hygiene). Six of the interventions had some degree of effectiveness in reducing C. difficile infection: daily and terminal cleaning, staff hand hygiene, patient hand hygiene, screening at admission, and patient transfer reduction. Surprisingly, contact precautions for staff made little impact on transmission in this model. Daily cleaning with a sporicidal disinfectant was the most effective single intervention, reducing C. difficile infection by 69%. Implementing screening to detect asymptomatic carriers was also effective, reducing C. difficile infection by 36%. All of the bundles tested reduced C. diffiicle infection, but the most effective bundle was daily cleaning with a sporicidal disinfectant combined with screening for asymptomatic carriage, which would reduce C. difficile infection by 82%. Adding staff hand hygiene and patient hand hygiene would reduce C. difficile infection further.
The main problem with a modelling study like this is that it stands or falls by the quality of the data used to parameterise the model. If the parameters for the variables going into the model are inaccurate, the findings will be unreliable – and incorrect parameter values going into the model can be compounded by the calculations to give very odd findings! In this case, however, there’s a lot of experimental data on the impact of daily and terminal cleaning relating to C. difficile, so the outcomes of the model relating to cleaning are probably reliable. There is considerably less data on the impact of screening for C. difficile asymptomatic colonisation, so outcomes related to this intervention are probably less reliable.
Overall, the modelling study supports that an intervention bundle is the best approach to preventing C. difficile infection, and that daily and terminal disinfection with a sporicidal agent should be the fundamental component of all C. difficile prevention bundles, which is reflected in the latest European guidelines.