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 Not yet peer-reviewed, but still very impressive.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

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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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Test-negative design: the best study design ever?

To kick off the 2018 Journal Club our PhD students discussed a bewildering new trial design* to determine vaccine effectiveness (VE) published in Lancet ID, from which Meri Varkila reports.  The classical approach to quantify VE was to spend the best 5 years of your life to find 2,000 general practitioners, to invite 600,000 elderly to randomize 85.000 and to find 139 primary endpoints in 57 hospitals while all involved remain blinded. This new approach, called the test-negative design (TND) study would give you that number in a year, by just studying a few hundred patients with community-acquired pneumonia. A true Quality-of-Life enhancer for many…., if reliable. Continue reading

From collateral damage to collateral sensitivity

“Every disadvantage has an advantage” is one of the many brilliant quotes from the late Dutch philosopher Johan Cruijff. This now also seems to hold for antibiotic resistance. The conventional belief is that resistance development is unidirectional: pathogens cumulatively acquire resistance traits, until being a multidrug resistant superbug. This now seems not always true; resistance development to antibiotic A, may – at the same time – increase susceptibility to antibiotic B, a phenomenon called “collateral sensitivity” that may help us in treating chronic infections. Continue reading

What’s up for 2018?

I hope you enjoyed Christmas time and wish you all the best for this year. From my side, I will continue to reflect what I meet professionally, what surprises me, confirms what I thought to know or what confirms my ignorance. In 2017 I did that 41 times (a surprise to me!) and here are some trending topics that will most likely return in 2018. Continue reading

When quality improvement fails

In this weeks’ PhD journal club Darren Troeman discussed the paper “Effect of a multifaceted educational intervention for anti-infectious measures on sepsis mortality: a cluster randomized trial”.  The plan was to improve compliance with guidelines, thereby reducing time before start of antimicrobial therapy (AT) which should reduce 28-day mortality. The intervention was compared to conventional medical education. Disappointingly, the trial provided more lessons for trialists than for healthcare providers. Continue reading

Publish or perish

Our careers (at least partly) depend on our publications. The more, the better and to suit our needs we have a journal for any kind of publication. Sometimes, you read something and you may think “Hey, I have seen that before”. If the new study than confirms a previous finding, we apparently have a reproducible fact, which increases the likelihood that it is indeed true. Here is an example. Or not? Continue reading