Things We Like(d) These Months – July 2020
Well, that was a little unexpected. After 4 months of hibernation, drowning in a never-ending sea of new COVID-related research and articles, Norwich PEM is back, and by goodness have we missed you all. So, to ease us back into the swing of things, we thought we would announce our re-entry into the FOAMed world with another round-up of articles, blogs, twitter feeds and such that we have enjoyed over the last few months. Now, as our friends at DFTB have done such an incredible job at keeping abreast of all things COVID related (and if you haven’t seen their post, it’s an absolute triumph, where have you been?), we have decided to keep this post less COVID-19, and more NO-VID-19, and share our favourite non-coronaviral papers from the last few months. So without further ado, doff your PPE, wash your hands, settle down at least 2m apart from one another, and enjoy!
Journal Articles We Liked
Enteral Feeding during High-Flow Therapy in Bronchiolitis
It seems as though the days of “the bronchi-bay” are a sweet and distant memory, but fear not, although not the vogue respiratory virus at present, October is just around the bend. Feeding in bronchiolitis, especially the sicker bronchiolitic children is often a conundrum, and the decision to stop feeds is often made on the basis of treatment escalation. This paper was a secondary analysis of the much-discussed PARIS trial, which looked at the utility of HFNC in bronchiolitis. In this paper, the authors looked at the feeding methods from the trial, to establish whether there were any adverse outcomes from enteral feeding of the children on HFNC. The conclusion was that, with the vast majority of patients on HFNC receiving enteral feeds (orally or via NGT), no recorded aspiration events, and 1% having apnoeas (compared to 6% of IV only patients), that in the vast majority of cases, enteral feeding is safe to give in combination with HFNC.
Lower vs Traditional Treatment Thresholds for Neonatal Hypoglycaemia
Neonatal blood sugar monitoring can cause significant headaches to the post-natal SHO, as I’m sure anyone who has stepped on that side before will know. In 2017, BAPM released a new framework for the management of neonatal hypoglycaemia. Throwing the sugary cat amongst the pigeons, it recommended lowering the operational threshold defining intervention from 2.6 mmol to 2.0 mmol in healthy, asymptomatic neonates, in the absence of any evidence to it’s detriment. Following publication of the CHYLD study, which suggested that poor neurodevelopmental outcome may not be intrinsically linked to absolute blood sugar level itself, the neonatal world has been waiting for evidence to support the long term-outcomes of the lowered threshold. Enter stage right, the HypoEXIT Study Group. This randomised non-inferiority trial showed that cognitive and motor outcomes were not inferior in the lowered threshold group, when compared to the standard group. However, it also pointed to more episodes of severe hypoglycaemia in the lower threshold group, with 2 SAEs in that same group. So, what does it all mean? Well, it’s up to you to decide, but ask 2 neonatologists, and you will likely get 3 different answers.
#FOAMed We Liked
Why pretest probability is absolutely essential – First10EM
Over the last few months, the subject of testing has been pretty rife through the media. Performing tests to solidify diagnoses is a core part of medicine, but it is also one of the most misinterpreted aspects of daily practice, which brought me back this month to one of my favourite articles on EBM on the internet, brought to you by Justin Morgenstern of First10EM. Pretest probability is *the* metric to understanding and interpreting test results. It underpins exactly why we should be explicit in chosing the correct test for the correct patient population, and allows us to understand the results and apply them to the patient in front of you. For a bonus if you enjoy visualising data, Lars Mølgaard Saxhaug has designed an interactive Leaf plot for you to play with, which I would hugely encourage.
P-Value – The Bottom Line
A recent twitter thread announced that P-values were the most commonly used, and most poorly understood element of medical statistics. “Tosh”, I thought “I know what a P-value is, and how to interpret them!”. Well, reader, I was wrong. I, like many, was famously, fabulously wrong in my understanding of P-Values and their utility in medical statistics, and so I went about trying to find a way to make amends. This article from The Bottom Line is excellent, and succinctly explains the who/what/where & why of the dreaded P, and what it means in the papers we read.
Social Media Things We Liked
Gilbert’s Syndrome Tweetorial – Elliot Tapper
Jaundice is a common topic in paediatrics, but once you scratch the surface, you may find your knowledge a little rusty. Sharpen those minds with an excellent tweetorial on Gilbert’s Syndrome from Michigan-based liver specialist Elliot Tapper
Brown Skin Matters
Now, more than ever, the spotlight is being turned on the ugly issue of systemic racism that has perpetuated our society. Health inequality is a clear and unarguable fact for BAME people in this country, and it is our duty to educate ourselves so that we can eradicate this problem from its roots. This fantastic Instagram page highlights that which is missing from our dermatology textbooks – namely what common rashes look like on non-white skin. Scroll through and educate yourselves, it is a genuinely brilliant resource.
Podcasts We Liked
EBM2.0 and the Death of Statistical Significance – Broomedocs
I have to confess, a month ago, I would have belly-laughed at the thought of being the sort of person to watch an hour long video on P-values, then double down with a two part podcast on the same subject. But reader, that is what I did. I am not a stats person. I’m awful at stats. I try hard, but I end up having to google things every time I read a paper. And that’s fine, because this is exactly the sort of person that this is aimed at. The only thing I thought I understood was p-values. However, as this exceptionally well presented video showed, almost everything I thought I understood was wrong. So please, watch the video, listen to the podcast, and let us move forward from statistical significance, one ATOM step at a time.