Breaking the GLASS shroud around the global AMR crisis

WHO have published the first report of the Global Antimicrobial Resistance Surveillance System (GLASS) network. GLASS was launched a couple of years ago to try and address the massive black hole in our knowledge of global AMR resistance rates. The extensive report details progress to date, focussing on which countries have established surveillance systems, and how the initial data looks (which you can also view via an online database).

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Preventing S. aureus SSI: Who does what?

Pre-operative (or better peri-operative) treatment of nasal S. aureus carriage is one of the most – if not the most – effective infection prevention measure. A large double-blind randomized controlled trial convincingly confirmed the meta-analysis results of previously performed smaller studies: 5 days of nasal mupirocin ointment together with chlorhexidine showering reduced the incidence of deep-seated S. aureus surgicial site infection (SSI) with 80% among S. aureus carriers undergoing orthopaedic or cardiothoracic surgery. Eight years after publication of these findings I (and others) still have the feeling that many hospitals have not implemented this measure. Continue reading

Where does your ESBL come from?

Last Friday the results of the ESBL Attribution study (ESBLAT) were presented. After considerable media attention for ESBL-producing bacteria on our meat (especially retail chicken meat) and a 84-year old woman being “the first deadly victim of the new chicken-ESBL bacterium” a research consortium was asked to quantify the role of ESBL in animal industry for human health. The “research lab” was the Netherlands: one of the most densely populated countries in the world for both humans and animals, with the highest antibiotic use in the world for animals and the lowest for humans. If anywhere, zoonotic transmission should happen there! Continue reading

The future of infection surveillance is ….. Google

If you feel that your  hospitals’ Electronic Health Record (EHR) can do more for you, read this. Not yet peer-reviewed, but still very impressive. Using all 46 billion (!) data points in the EHR from 216.221 patients in 2 hospitals they predicted (at day 1 of admission) in-hospital mortality, long length of stay and readmission, pretty accurately, and much better than existing prediction models. How? Deep learning techniques. Who are they? The paper has 35 authors, of which 32 work at Google Inc, Mountain View, California. Continue reading

Painting the hospital room blue

This recent study from the Donskey group could provide hospital cleaning staff with a powerful visual cue to help assure adequate disinfectant coverage. The addition of a chemical widget to bleach solution gives it a bright blue hue when applied to surfaces, so allowing a cleaner to track their progress visually!

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The Truth About Hawaii

I caught the 15 minute drama on BBC R4 today (The Truth About Hawaii) and, to my surprise, it was a post-antibiotic apocalypse story. A ten year old girl gets a scratch on the knee that develops into a serious infection that without antibiotics has become life threatening. The Prime Minister is personally involved in enforcing a restriction policy for the last remaining antibiotic. And, as with pretty much every other Radio 4 drama, a happy ending seems unlikely.

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All models are wrong…..

Yesterday, our study on antibiotic cycling strategies in ICUs was published. Thanks to Joppe van Duijn, involved in all study phases, we could report that in 8 ICUs in 5 countries with 8,776 patients the unit-wide prevalence of antibiotic resistance was similar when cycling antibiotics every 6 weeks or when cycling antibiotics for every next patient treated (mixing). The study was motivated by prior mathematical models, of which most predicted that cycling would do better. So, now all can raise their voices: (1) “all models are wrong, but some are useful”; (2) “most studies are wrong, but some are useful”; or (3) “if model predictions are not confirmed, where did the study go wrong?”

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