Type 1 diabetes has a very high treatment burden in terms of direct costs, inconvenience and lost productivity for patients and their carers. Further, all the glucose checking, hormone replacement and consults don’t abolish the vascular complications associated with poor glycaemic control. Only in the last few years has it been possible to pharmacologically alter the course of type 1 diabetes and other auto-immune diseases without generating intolerable side effects. Teplizumab is an antibody to CD3 which was presented to the world in 2019 as delaying the onset of type 1 diabetes in high-risk ..read more

Last November an NHS Hospital Trust in Nottingham sought permission from the UK High Court to withdraw life support from a seven-month old girl called Indi Gregory. The devastated parents did not want to give up on her although they were advised there was no hope of treatment for her profound developmental disability. The family and the medical teams returned to court two more times, right up to the day that Indi was to be extubated.  Conflicts over care have always existed but their frequency has increased as medicinal advances present more options for intervention even in the sickest pa ..read more

The theory that certain fatty acids are essential to the diet and associated with reduced cardiovascular risk has been controversial since it was floated in the 1950s.   In 1971 Danish researchers published the results from a cross-sectional study of Inuit people living on the west coast of Greenland. They ate a fish-based diet rich in polyunsaturated fatty acids known as omega-3s, which were found in their tissues along with much lower levels of pre-β-lipoprotein and plasma-triglycerides when compared to controls.    That association between a fishy diet and lowered cardiovascu ..read more

Semaglutide, has become a blockbuster drug like no other, making its manufacturer Novo Nordisk the most valuable listed company in Europe. Sold under brand names Ozempic or Wegovy, it’s held up as some kind of weight loss miracle cure, but demand is so high, that it’s been hard to supply the patients with type 2 diabetes for whom it was first indicated. Semaglutide is an analog of glucagon-like peptide 1 which has direct, glucose-dependent effects on insulin secretion. In this episode we first talk about how semaglutide compares to other drugs in its class as a treatment for diabetes. The grea ..read more

We’ve known for a decade that about 50 percent of doctors meet the criteria for burnout, and the figure is up to 70 percent among trainees. But organisations have been left to come up with their own solutions to this, the result being that many simply offer band aid solutions rather than systemic ones. Unforgiving work conditions pose a problem for both recruitment and retention of staff to the health workforce. The New Zealand Health Department, Te Whatu Ora, forecasts that within ten years supply of doctors, pharmacists and nurses will fall short of demand by 14 to 18 percent. In response th ..read more

This is the final episode in a five-part series about artificial intelligence in medicine. We start by weighing up the costs and benefits of automation in a health system that’s increasingly pushed beyond capacity. One of the biggest time sinks for health practitioners is filling out and searching through medical records. Some of this could be performed by natural language processors which are becoming more accurate thanks to deep learning.     The power of large language models has been demonstrated by the meteoritic uptake of ChatGPT and doctors are among those who have used i ..read more

This is the fourth part in a series on artificial intelligence in medicine and we try and unpick the causes and consequences of adverse events resulting from this technology. Our guest David Lyell is a research fellow at the Australian Institute of Health Innovation (Macquarie University) who has published a first-of-its kind audit of adverse events reported to the US regulator, the Federal Drugs Administration. He breaks down those that were caused by errors in the machine learning algorithm, other aspects of a device or even user error.    We also discuss where these all fit in to ..read more

On the 28th of January 2022 a 75-year-old man was admitted to the regional Albury Wodonga Health Service with a high fever and Parkinsonian symptoms. The patient spent over a week in intensive care, but brain scans did not reveal an obvious aetiology and assays for a range of pathogens came up negative. When serology eventually revealed the presence of antibodies against Japanese encephalitis virus this became only the second ever locally-acquired case on Australia’s mainland. Even more startling was the fact that the previous one had been way back in 1998 in Cape York, far north Queensland.&n ..read more

This is the third part of a series on artificial intelligence in medicine. Previously we explained how to train and test machine learning models that assist in decision-making, and then how to iron out ergonomic friction points in the clinical workflow. We’ve mentioned how deep learning neural networks are more capable than classical models at dealing with big noisy data sets, but also that the reasoning they use to solve questions asked of them might be inexplainable users.    This creates a certain unease among clinicians and regulators like Australia’s Therapeutic Goods Administra ..read more

The allure of having devices and tasks assisted by artificial intelligence is that they will help overcome some of the natural limits of human cognition with regards to working memory and attention. And in helping with the mundane tasks, AI can buy clinicians back time to spend with the complex patients who really need it. But the way all this pans out will really depend on how seamlessly the machine learning devices fit in with the clinical workflow. Which aspect of clinical decision-making do they support and how are the consequences of error mitigated? Only a small fraction of research proj ..read more